google leadership case study

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• Published: 19 December 2017

GOOGLE: a reflection of culture, leader, and management

• Sang Kim Tran 1 , 2  

International Journal of Corporate Social Responsibility volume  2 , Article number:  10 ( 2017 ) Cite this article

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This paper provides a viewpoint of the culture and subcultures at Google Inc., which is a famous global company, and has a huge engineering staff and many talented leaders. Through its history of development, it has had positive impacts on society; however; there have been management challenges. The Board of Directors (BoDs) developed and implemented a way to measure the abilities of their managers, which helped to identify problems. This paper will analyze the case study of Harvard Business Review, Oxygen Project, and clarify the management problem in Google’s organization. It will also compare Google with Zappos, a much smaller organization, and present how the BoDs of Zappos assesses its culture and subcultures. In this paper, we will recommend eight important points to building an organizational culture that is positive for stable growth of a company. We believe that much of what be learned could be useful to other business leaders, regardless of company scale.

Introduction

In a large society, each company is considered a miniature society (Mawere 2011 ). Similar to large societies with large cultures, small societies also need to build their own cultures. A culture is influenced by many factors and determines if it is a great culture. Corporate culture requires both the attention to the efficiency of production and business and to the relationship among people in the organization closely (Bhagat et al. 2012 ). Regardless if it is a large or a small organization, it must encounter issues of cooperation among individuals and groups. There are many factors leading to the success of business process re-engineering in higher education (BPR), the main four elements are culture, processes, structure, and technology. Culture is listed as number one (Ahmad et al. 2007 ). Hence, culture becomes the most important factor to the success of the development of a business. Organizational culture is the set of shared beliefs (Steiber and Alänge 2016 ), values, and norms that influence the way members think, feel, and behave. Culture is created by means of terminal and instrumental values, heroes, rites and rituals, and communication networks (Barman n.d. ). The primary methods of maintaining organizational culture are through the socialization process by which an individual learns the values, expected behaviors, and necessary social knowledge to assume their roles in the organization. In addition, (Gupta and Govindarajan 2000 ) and Fig.  1 in (Ismail Al-Alawi et al. 2007 ) illustrates that culture was established by six major factors, such as information systems, people, process, leadership, rewarding system, and organization structure. Therefore, there is a wide variety of combined and sophisticated cultures in the workplace, especially in big corporations like Google, Facebook, Proctor & Gamble, etc. Each organization tends to have a common goal, which is to create a culture that is different from other companies and to promote their teams to be creative in developing a distinctive culture (Stimpson and Farquharson 2014 ). Clearly, we can see that Google’s culture is different than others. What makes this company unique and different from others, as well as the dominant cultures and subcultures existing at this company? How do leadership behaviors impact the organizational culture? By operating a case study of a Harvard Business Review to analyze its organizational culture, subsequently, having compared it with Zappos’ culture, this paper will clarify the similarities and differences in managing organizational cultures between them and consider whether the solutions for the problems can be applied to other business models, and for tomorrow leaders or not?

Trends of using product by information searching

Company overview

This part shows how Google became famous in the world and its culture and subcultures made it a special case for others to take into consideration. Google is one of the few technology companies which continue to have one of the fastest growth rates in the world. It began by creating a search engine that combined PageRank system, developed by Larry Page (ranking the importance of websites based on external links), and Web search engine, created by Sergey Brin (accessing a website and recording its content), two co-founders of the company (Jarvis 2011 ; Downes 2007 ). Google’s achievements absolutely do not come from any luck. Google has made extra efforts in creating an index of a number of websites, which have been up to 25 billion websites. This also includes 17 million images and one billion messages to Usenet group (Downes 2007 ). Besides searching for websites, Google users are able to search for PDF files, PostScript, documents, as well as Microsoft, Lotus, PowerPoint and Shockwave files. Google processes nearly 50% of search queries all over the world. Moreover, it is the number one search option for web users and is one of the top five websites on the Internet, which have more than 380 million users and 28 billion visits every month, and more than 50% of access from countries outside the US (Desjardins 2017 ). Google’s technology is rather special: it can analyze millions of different variables of users and businesses who place advertisements. It then connects them with millions of potential advertisements and gives messages of advertisement, which is closest to objects in less than one second. Thus, Google has the higher rate of users clicking advertisements than its opponent Yahoo, from 50 to 100%, and it dominates over 70% market share of paid advertisements (Rosenberg 2016 ). Google’s self-stated mission: “to organize the world’s information and make it universally accessible and useful (Alves n.d. ).” Nowadays, it is believed that people in the world like “Google” with words “the useful-lively information storage”.

Predominant culture at Google

The dominant culture in the organization depends on the environment in which the company operates the organization’s objectives, the belief system of the employees, and the company’s management style. Therefore, there are many organizational cultures (Schein 2017 ). The Exhibit 3.1 at page 39 in (Schein 2009 ) provides what culture is about. For example, employee follows a standard procedure with a strict adherence to hierarchy and well-defined individual roles and responsibilities. Those in competitive environments, such as sales may forget strict hierarchies and follow a competitive culture where the focus is on maintaining strong relationships with external parties. In this instance, the strategy is to attain competitive advantages over the competition. The collaborative culture is yet another organizational way of life. This culture presents a decentralized workforce with integrated units working together to find solutions to problems or failure.

Why do many large companies buy its innovation? Because its dominant culture of 99% defect-free operational excellence squashes any attempts at innovation, just like a Sumo wrestler sitting on a small gymnast (Grossman-Kahn and Rosensweig 2012 ). They cannot accept failures. In fact, failure is a necessary part of innovation and Google took this change by Oxygen Project to measure the abilities of their multicultural managers. This means that Google itself possesses multiple different cultures (see Google’s clips). Like Zappos, Google had established a common, organizational culture for the whole offices that are distinctive from the others. The predominant culture aimed at Google is an open culture, where everybody and customer can freely contribute their ideas and opinions to create more comfortable and friendly working environment (Hsieh 2010a ).

The fig.  2 .1 in chapter two of (Schein 2009 ) and page 17 in part one of (Schein 2017 ) provide us three levels of culture which are Artifacts, Espoused values and Underlying assumptions helping us to understand the culture at Google. At page 84, in (Schein 2009 ), the “artifacts” are identified such as dress codes, level of formality in authority relationships, working hours, meeting (how often, how run, timing), how are decisions made, communication, social events, jargon, uniforms, identity symbols, rites and rituals, disagreements and conflicts, balance between work and family . It seems that Google is quite open in these artifacts by showing a respect for uniform and national culture of each staff individually and giving them the right to wear traditional clothes.

Ad Blocking Incidence

Working at Google, employees enjoy free food served throughout the day, a volleyball court, a swimming pool, a car wash, an oil change, a haircut, free health care, and many other benefits. The biggest benefit for the staff is to be picked up on the day of work. As assessed by many traffic experts, the system set up by Google is considered to be a great transport network. Tad Widby, a project manager and a traffic system researcher throughout the United States, said: “I have not seen any larger projects in the Bay Area as well as in urban areas across the country” (Helft 2007 ). Of course, it is impossible for Google to “cover up the sky”, so Yahoo also started implementing the bus project for employees in 2005. On peak days, Yahoo’s bus also took off. Pick up about 350 employees in San Francisco, as well as Berkeley, Oakland, etc. These buses run on biofuels and have Wi-Fi coverage. Yet, Danielle Bricker, the Yahoo bus coordinator of Yahoo, has also admitted that the program is “indirectly” inspired by Google’s initiative (Helft 2007 ). Along with that, eBay recently also piloted shuttle bus transfers at five points in San Francisco. Some other corporations are also emerging ideas for treatment of staff is equally unique. Facebook is an example, instead of facilitating employees far from the workplace; it helps people in the immediate neighborhood by offering an additional $10,000 for an employee to live close to the pillar within 10 miles, nearby the Palo Alto Department (Hall 2015 ).

When it comes to Google, people often ask what the formula for success is. The answer here is the employees of Google. They create their own unique workplace culture rules to create an effective work environment for their employees. And here are the most valuable things to learn from Google’s corporate culture (Scott 2008 ) that we should know:

Tolerate with mistakes and help staff correct

At Google, paying attention to how employees work and helping them correct mistakes is critical. Instead of pointing out the damage and blaming a person who caused the mistake, the company would be interested in what the cause of the problem was and how to fix it as quickly and efficiently as possible.

Also as its culture, we understand that if we want to make breakthroughs in the workplace, we need to have experimentation, failure and repeat the test. Therefore, mistakes and failures are not terrible there. We have the right to be wrong and have the opportunity to overcome failure in the support of our superiors and colleagues. Good ideas are always encouraged at Google. However, before it is accepted and put into use, there is a clear procedure to confirm whether it is a real new idea and practical or not?

Exponential thought

Google developed in the direction of a holding company - a company that does not directly produce products or provide services but simply invest in capital by buying back capital. In the company, the criteria for setting the ten exponential function in lieu of focusing only on the change in the general increase. This approach helps Google improve its technology and deliver great products to consumers continuously.

Of course, every company wants to hire talented people to work for them. However, being talented is an art in which there must be voluntary work and enthusiasm for the work of the devotees. At page 555 in (Saffold 1988 ) illustrated that distinctive cultures dramatically influencing performance do exist. Likewise, Google, Apple, Netflix, and Dell are 40% more productive than the average company which attracts top-tier employees and high performers (Vozza 2017 ). Recognizing this impact, Google created a distinctive corporate culture when the company attracted people from prestigious colleges around the world (West 2016 ; Lazear and Gibbs 2014 ).

Build a stimulating work environment

When it comes to the elements that create creativity and innovation, we can easily recognize that the working environment is one of the most important things. Google has succeeded in building an image of a creative working. Google offices are individually designed, not duplicated in any type of office. In fact, working environment at Google is so comfortable so that employees will not think of it as a working room, with a full area of ​​work, relaxation, exercise, reading, watching movies. Is the orientation of Google’s corporate culture to stimulate creativity and to show interest in the lives of employees so that volunteers contribute freely (Battelle 2011 )?

Subculture is also a culture, but for a smaller group or community in a big organization (Crosset and Beal 1997 ). Google, known as the global company with many more offices, so there are many subcultures created among groups of people who work together, from subcultures among work groups to subcultures among ethnic groups and nations, multi-national groups, as well as multiple occupations, functions, geographies, echelons in the hierarchy and product lines. For example, six years ago, when it bought 100 Huffys for employees to use around the sprawling campus, has since exploded into its own subculture. Google now has a seven-person staff of bicycle mechanics that maintains a fleet of about 1300 brightly-colored Google bikes. The company also encourages employees to cycle to work by providing locker rooms, showers and places to securely park bikes during working hours. And, for those who want to combine meetings with bike-riding, Googlers can use one of several seven-person (Crowley 2013 ).

Leadership influences on the culture at Google

From the definition of leadership and its influence on culture; so what does leader directly influence the culture existed? According to Schein, “culture and leadership are two sides of the same coin and one cannot understand one without the other”, page three in (Schein 2009 ). If one of us has never read the article “Google and the Quest to create a better boss” in the New York Times, it is listed in a priority reading. It breaks the notion that managers have no change. The manager really makes a difference (Axinn 1988 ; Carver 2011 ). In fact, a leader has a massive impact on the culture of the company, and Google is not an exception. The leaders of Google concerned more about the demands and abilities of each individual, the study of the nature of human being, an appreciation their employees as their customers. At Google, the founders thought they could create a company that people would want to work at when creating a home-like environment. It is real that they focus on the workplace brings the comfort to staff creatively and freely (Lebowitz 2013 ).

In my opinion, a successful business cannot be attributed solely from a single star; that needs the brightness of all employees. It depends very much on the capacity and ability to attract talented people. It is the way in which the leader manages these talents, is the cornerstone of corporate culture. One thing that no one can deny is that a good leader must be a creator of a corporate culture so that the employees can maximize capabilities themselves (Driscoll and McKee 2007 ; Kotter 2008 ).

To brief, through the view of Google’s culture, BoDs tended and designed to encourage loyalty and creativity, based on an unusual organizational culture because culture is not only able to create an environment, but it also adapts to diverse and changes circumstances (Bulygo 2013 ).

Company growth and its impact

“Rearrange information around the world, make them accessible everywhere and be useful.” This was one of the main purposes set by Larry Page and Sergey Brin when they first launched Google on September 4th, 1998, as a private company (Schmidt and Rosenberg 2014 ). Since then, Google has expanded its reach, stepped into the mobile operating system, provided mapping services and cloud computing applications, launched its own hardware, and prepared it to enter the wearable device market. However, no matter how varied and rich these products are, they are all about the one thing, the root of Google: online searching.

1998–2001: Focus on search

In its early years, Google.com was simply one with extreme iconic images: a colorful Google logo, a long text box in the middle of the screen, a button to execute. One button for searching and the other button are “I’m feeling lucky” to lead users to a random Google site. By May 2000, Google added ten additional languages to Google.com , including French, German, Italian, Swedish, Finnish, Spanish, Portuguese, Dutch, Norwegian and Danish, etc. This is one of the milestones in Google’s journey into the world. Google.com is available in over 150 languages (Scott 2008 ; Lee 2017 ).

2001–2007: Interface card

A very important event with Google around this time was the sale of shares to the public (IPO). In October 2003, Microsoft heard news of the IPO, so it quickly approached Google to discuss a buyout or business deal. Nevertheless, that intention was not materialized. In 2004, it was also the time when Google held a market share of 84.7% globally through collaboration with major Internet companies, such as Yahoo, AOL, and CNN. By February 2004, Yahoo stopped working with Google and separately stood out for engine search. This has led Google to lose some market share, but it has shown the importance and distinctness of Google. Nowadays, the term “Google” has been used as a verb just by visiting Google.com and doing an online search (Smith 2010 ). Not stopping at the homepage search, Google’s interface tag began to be brought to Gmail and Calendar with the links at the top of the page. Google homepage itself continues to use this style.

In 2006, Google also made an important acquisition to buy YouTube for $1.65 billion (Burgess and Green 2013 ). However, the company decided to keep YouTube as a separate brand and not to include it in Google Video search. Thanks to the backing of an Internet industry giant, YouTube has grown to become the world’s largest online video sharing service (Cha et al. 2007 ).

2007–2012: Navigation bar, Google menu, Google now

Google began to deploy a new navigation bar located at the edge of the screen. It includes links to a place where to look for photos, videos, news, maps, as well as buttons to switch to Gmail, Calendar, and other services developed by the company. In the upper left corner, Google added a box displaying Google + notifications and user accounts’ image. Google Now not only appeared on Android and it’s also brought to Chrome on a computer as well as iOS. All have the same operating principle, and the interface card still appears as Android it is.

2013–2014: Simplified interface

Google has moved all of the icons that lead to its other applications and services to an App Drawer button in the upper right hand, at the corner of the screen. In addition, Google.com also supports better voice search through the Chrome browser. Google has experimented with other markets, such as radio and print publications, and in selling advertisements from its advertisers within offline newspapers and magazines. As of November 2014, Google operates over 70 offices over 40 countries (Jarvis 2011 ; Vise 2007 ).

2014–2017: Chrome development and facing challenges

In 2015, Google would turn HTTPS into the default. The better website is, the more users will trust search engine. In 2016, Google announced Android version 7, introduced a new VR platform called Daydream, and its new virtual assistant, Google Assistant.

Most of Google’s revenue comes from advertising (Rosenberg 2016 ). However, this “golden” business is entering a difficult period with many warning signs of its future. Google Search is the dominant strength of Google and bringing great revenue for the company. Nonetheless, when Amazon surpassed Google to become the world’s leading product in the search engine in last December, this advantage began to wobble. This is considered a fatal blow to Google when iOS devices account for 75% of their mobile advertising revenue (Rosenberg 2016 ).

By 2016, the number of people installing software to block ads on phones has increased 102% from 2015. Figure  1 illustrates that by the year’s end, about 16% of smart phone users around the world blocked their ads whilst surfing the web. These were also two groups having the most time on the Internet, high-earners and young people; however, these people have disliked ads (see Fig. 1 ).

Figure  2 shows the young people have the highest ad blocking rates. It is drawing a gloomy picture for the sustainable development of the online advertising industry in general and Google in particular. Therefore, in early 2017, Google has strategies to build an ad blocking tool, built into the Chrome browser. This tool allows users to access ads that have passed the “Coalition for Better Ads” filter so as to limit the sense of discomfort (see Fig. 2 ).

For the company impact, the history shows that speedy development of Google creates both economic and social impacts to followers in a new way of people connection (Savitz 2013 ). In this modern world, it seems that people cannot spend a day without searching any information in Google (Chen et al. 2014 ; Fast and Campbell 2004 ), a tool serves human information seeking needs. Even though when addressing this paper, it is also in need the information from Google search and uses it as a supporting tool. Nobody can deny the convenience of Google as a fast and easy way to search (Schalkwyk et al. 2010 ; Jones 2001 ; Langville and Meyer 2011 ).

Research question and methodology

In order to get the most comprehensive data and information for this case analysis, a number of methods are used, including:

Research data and collect information were mostly from the Harvard Study (Project Oxygen), which has been selected because it is related to the purpose of our study.

Data collection and analysis has been taken from Google Scholar and various websites related researches. We look at the history of appearance, development, and recognize the impacts of this company, as well as the challenges and the way the Board of Directors measures the abilities of their manager when the problem is found.

Analyzing: It was begun by considering expectations from the Harvard Study. Subsequently, considering the smaller organization (Zappos) in comparison of how its cultures and subcultures are accessed as well. Since then, the paper has clarified the management problem that Google and Zappos confront and deal with it so as to help other businesses apply this theoretical practice and achieve its goal beyond expectations.

In our paper, we mainly use the inductive method approach by compiling and describing the other authors’ theories of corporate culture, especially Google and Zappos in merging and comparing, analyzing them and making our own results.

From the aspects of the research, the questions are suggested as below:

What is the most instrumental element found from the Harvard study?

Is there any difference and similarity between a huge company and a smaller enterprise in perspective of culture and subculture?

What makes Google different from others, the dominant cultures as well as subcultures existing? How do leadership behaviors impact on the organizational culture?

How organizational culture impacts on business achievements?

The Harvard study

Project oxygen summary.

This project began in 2009 known as “the manager project” with the People and Innovation Lab (PiLab) team researching questions, which helped the employee of Google become a better manager. The case study was conducted by Garvin (2013) about a behavior measurement to Google’s manager, why managers matter and what the best manager s do. In early days of Google, there are not many managers. In a flat structure, most employees are engineers and technical experts. In fact, in 2002 a few hundred engineers reported to only four managers. But over time and out of necessity, the number of managers increased. Then, in 2009, people and team culture at Google noticed a disturbing trend. Exit interview data cited low satisfaction with their manager as a reason for leaving Google. Because Google has accessed so much online data, Google’s statisticians are asked to analyze and identify the top attributes of a good manager mentioned with an unsolved question: “Do managers matter?” It always concerns all stakeholders at Google and requires a data-based survey project called Project Oxygen to clarify employees’ concern, to measure key management behaviors and cultivate staff through communication and training (Bryant 2011 ; Garvin et al. 2013 ). Research −1 Exit Interviews, ratings, and semiannual reviews. The purpose is to identify high-scoring managers and low-scoring managers resulted in the former, less turnover on their teams, and its connection (manager quality and employee’s happiness). As for “what the best managers do”, Research-2 is to interview high and low scoring managers and to review their performance. The findings with 8 key behaviors illustrated by the most effective managers.

The Oxygen Project mirrors the managers’ decision-making criteria, respects their needs for rigorous analysis, and makes it a priority to measure impact. In the case study, the findings prove that managers really have mattered. Google, initially, must figure out what the best manager is by asking high and low scoring managers such questions about communication, vision, etc. Its project identifies eight behaviors (Bulygo 2013 ; Garvin et al. 2013 ) of a good manager that considered as quite simple that the best manager at Google should have. In a case of management problem and solution, as well as discussing four- key theoretical concepts, they will be analyzed, including formal organizational training system, how culture influences behavior, the role of “flow” and building capacity for innovation, and the role of a leader and its difference from the manager.

Formal organizational training system to create a different culture: Ethical culture

If the organizational culture represents “how we do things around here,” the ethical culture represents “how we do things around here in relation to ethics and ethical behavior in the organization” (Key 1999 ). Alison Taylor (The Five Levels of an Ethical Culture, 2017) reported five levels of an ethical culture, from an individual, interpersonal, group, intergroup to inter-organizational (Taylor 2017 ). In (Nelson and Treviño 2004 ), ethical culture should be thought of in terms of a multi-system framework included formal and informal systems, which must be aligned to support ethical judgment and action. Leadership is essential to driving the ethical culture from a formal and informal perspective (Schwartz 2013 ; Trevino and Nelson 2011 ). Formally, a leader provides the resources to implement structures and programs that support ethics. More informally, through their own behaviors, leadership is a role model whose actions speak louder than their words, conveying “how we do things around here.” Other formal systems include selection systems, policies and codes, orientation and training programs, performance management systems, authority structures, and formal decision processes. On the informal side are the organization’s role models and heroes, the norms of daily behavior, organizational rituals that support or do not support ethical conduct, the stories people tell about the organization and their implications for conduct, and the language people use, etc. Is it okay to talk about ethics? Or is ethical fading the norm?

The formal and informal training is very important. The ethical context in organizations helps the organizational culture have a tendency to the positive or negative viewpoints (Treviño et al. 1998 ). The leader should focus on providing an understanding of the nature and reasons for the organization’s values and rules, on providing an opportunity for question and challenge values for sincerity/practicality, and on teaching ethical decision-making skills related to encountered issues commonly. The more specific and customized training, the more effective it is likely to be. Google seemed to apply this theory when addressed the Oxygen Project.

How culture influences behavior

Whenever we approach a new organization, there is no doubt that we will try to get more about the culture of that place, the way of thinking, working, as well as behavior. And it is likely that the more diverse culture of a place is, the more difficult for outsiders to assess its culture becomes (Mosakowski 2004 ).

Realizing culture in (Schein 2009 ) including artifacts, espoused valued and shared underlying assumptions. It is easier for outsiders to see the artifacts (visual objects) that a group uses as the symbol for a group; however, it does not express more about the espoused values, as well as tacit assumptions. In (Schein et al. 2010 ), the author stated: “For a culture assessment to be valuable, it must get to the assumptions level. If the client system does not get to assumptions, it cannot explain the discrepancies almost always surface between the espoused values and the observed behavioral artifacts” (Schein et al. 2010 ). Hence, in order to be able to assess other cultures well, it is necessary for us to learn each other’s languages, as well as adapt to a common language. Moreover, we also need to look at the context of working, the solution for shared problems because these will facilitate to understand the culture better.

According to the OCP (Organizational Culture Profile) framework (Saremi and Nejad 2013 ), an organization is with possessing the innovation of culture, flexible and adaptable with fresh ideas, which is figured by flat hierarchy and title. For instance, Gore-Tex is an innovative product of W. L. Gore & Associates Inc., considered as the company has the most impact on its innovative culture (Boudreau and Lakhani 2009 ). Looking at the examples of Fast Company, Genentech Inc., and Google, they also encourage their employees to take challenges or risks by allowing them to take 20% of their time to comprehend the projects of their own (Saremi and Nejad 2013 ). In (Aldrich n.d. ), it is recorded that 25%–55% of employees are fully encouraged and giving a maximum value.

The famous quote by Peter Drucker , “Culture eats strategy for Breakfast” at page 67 has created a lot of interest in (Manning and Bodine 2012 ; Coffman and Sorensen 2013 ; Bock 2015 ). Despite we all know how important culture is, we have successively failed to address it (O'Reilly et al. 1991 ). The organizational research change process from the view of Schein ( 2009 ); it is a fact that whenever an organization has the intention of changing the culture, it really takes time. As we all acknowledge, to build an organizational culture, both leader and subordinate spend most of their time on learning, relearning, experiencing, as well as considering the most appropriate features. Sometimes, some changes are inevitable in terms of economic, political, technological, legal and moral threats, as well as internal discomfort (Kavanagh and Ashkanasy 2006 ; Schein 1983 ). As the case in (Schein 2009 ), when a CEO would like to make an innovation which is proved no effective response, given that he did not get to know well about the tacit implications at the place he has just come. It is illustrated that whatsoever change should need time and a process to happen (Blog 2015 ; Makhlouk and Shevchuk 2008 ). In conclusion, a new culture can be learned (Schein 1984 ), but with an appropriate route and the profits for all stakeholders should be concerned by the change manager (Sathe 1983 ).

It is true that people’s behavior managed by their types of culture (Kollmuss and Agyeman 2002 ). All tacit assumptions of insiders are not easy for outsiders to grasp the meaning completely (Schein 2009 ). It is not also an exception at any organization. Google is an example of the multicultural organization coming from various regions of the world, and the national or regional cultures making this multicultural organization with an official culture for the whole company.

In this case, the organizational culture of Google has an influence on the behaviors of manager and employee. In addition, as for such a company specializes in information technology, all engineers prefer to work on everything with data-evidence to get them involved in the meaningful survey about manager (Davenport et al. 2010 ). Eventually, Google discovered 8 good behaviors of manager, which effect to the role of “flow” also (Bulygo 2013 ; Garvin et al. 2013 ).

The role of the “flow” and building capacity for innovation

More and more people are using the term of “patient flow”. This overview describes patient flow and links to theories about flow. Patient flow underpins many improvement tools and techniques. The term “flow” describes the progressive movement of products, information, and people through a sequence of the process. In simple terms, flow is about uninterrupted movement (Nave 2002 ), like driving steadily along the motorway without interruptions or being stuck in a traffic jam. In healthcare, flow is the movement of patients, information or equipment between departments, office groups or organizations as a part of a patient’s care pathway (Bessant and Maher 2009 ). In fact, flow plays a vital role in getting stakeholders involved in working creatively and innovatively (Adams 2005 ; Amabile 1997 ; Forest et al. 2011 ). An effective ethical leader must create flow in work before transfer it to employees for changing the best of their effort to maintain, keep and develop “flow” in an engineering job, which job be easier to get stress. Definitely, Google gets it done very well.

Acknowledgements

Thanks to the knowledge from my Master course, a credit of managing culture which helps me to write this paper. The author also gratefully acknowledges the helpful comments and suggestions of the reviewers and Associate Professor Khuong- Ho Van, who provided general technical help that all have improved the article.

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Tran, S.K. GOOGLE: a reflection of culture, leader, and management. Int J Corporate Soc Responsibility 2 , 10 (2017). https://doi.org/10.1186/s40991-017-0021-0

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The Work Issue

What Google Learned From Its Quest to Build the Perfect Team

New research reveals surprising truths about why some work groups thrive and others falter.

Credit... Illustration by James Graham

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By Charles Duhigg

• Feb. 25, 2016

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When Rozovsky arrived on campus, she was assigned to a study group carefully engineered by the school to foster tight bonds. Study groups have become a rite of passage at M.B.A. programs, a way for students to practice working in teams and a reflection of the increasing demand for employees who can adroitly navigate group dynamics. A worker today might start the morning by collaborating with a team of engineers, then send emails to colleagues marketing a new brand, then jump on a conference call planning an entirely different product line, while also juggling team meetings with accounting and the party-planning committee. To prepare students for that complex world, business schools around the country have revised their curriculums to emphasize team-focused learning.

Every day, between classes or after dinner, Rozovsky and her four teammates gathered to discuss homework assignments, compare spreadsheets and strategize for exams. Everyone was smart and curious, and they had a lot in common: They had gone to similar colleges and had worked at analogous firms. These shared experiences, Rozovsky hoped, would make it easy for them to work well together. But it didn’t turn out that way. ‘‘There are lots of people who say some of their best business-school friends come from their study groups,’’ Rozovsky told me. ‘‘It wasn’t like that for me.’’

Instead, Rozovsky’s study group was a source of stress. ‘‘I always felt like I had to prove myself,’’ she said. The team’s dynamics could put her on edge. When the group met, teammates sometimes jockeyed for the leadership position or criticized one another’s ideas. There were conflicts over who was in charge and who got to represent the group in class. ‘‘People would try to show authority by speaking louder or talking over each other,’’ Rozovsky told me. ‘‘I always felt like I had to be careful not to make mistakes around them.’’

So Rozovsky started looking for other groups she could join. A classmate mentioned that some students were putting together teams for ‘‘case competitions,’’ contests in which participants proposed solutions to real-world business problems that were evaluated by judges, who awarded trophies and cash. The competitions were voluntary, but the work wasn’t all that different from what Rozovsky did with her study group: conducting lots of research and financial analyses, writing reports and giving presentations. The members of her case-competition team had a variety of professional experiences: Army officer, researcher at a think tank, director of a health-education nonprofit organization and consultant to a refugee program. Despite their disparate backgrounds, however, everyone clicked. They emailed one another dumb jokes and usually spent the first 10 minutes of each meeting chatting. When it came time to brainstorm, ‘‘we had lots of crazy ideas,’’ Rozovsky said.

One of her favorite competitions asked teams to come up with a new business to replace a student-run snack store on Yale’s campus. Rozovsky proposed a nap room and selling earplugs and eyeshades to make money. Someone else suggested filling the space with old video games. There were ideas about clothing swaps. Most of the proposals were impractical, but ‘‘we all felt like we could say anything to each other,’’ Rozovsky told me. ‘‘No one worried that the rest of the team was judging them.’’ Eventually, the team settled on a plan for a micro­gym with a handful of exercise classes and a few weight machines. They won the competition. (The micro­gym — with two stationary bicycles and three treadmills — still exists.)

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11.1 Decision-Making Culture: The Case of Google

Figure 11.1

Wikimedia Commons – public domain.

Google (NASDAQ: GOOG) is one of the best-known and most admired companies around the world, so much so that “googling” is the term many use to refer to searching information on the Web. What started out as a student project by two Stanford University graduates—Larry Page and Sergey Brin—in 1996, Google became the most frequently used Web search engine on the Internet with 1 billion searches per day in 2009, as well as other innovative applications such as Gmail, Google Earth, Google Maps, and Picasa. Google grew from 10 employees working in a garage in Palo Alto to 10,000 employees operating around the world by 2009. What is the formula behind this success?

Google strives to operate based on solid principles that may be traced back to its founders. In a world crowded with search engines, they were probably the first company that put users first. Their mission statement summarizes their commitment to end-user needs: “To organize the world’s information and to make it universally accessible and useful.” While other companies were focused on marketing their sites and increasing advertising revenues, Google stripped the search page of all distractions and presented users with a blank page consisting only of a company logo and a search box. Google resisted pop-up advertising, because the company felt that it was annoying to end-users. They insisted that all their advertisements would be clearly marked as “sponsored links.” This emphasis on improving user experience and always putting it before making more money in the short term seems to have been critical to their success.

Keeping their employees happy is also a value they take to heart. Google created a unique work environment that attracts, motivates, and retains the best players in the field. Google was ranked as the number 1 “Best Place to Work For” by Fortune magazine in 2007 and number 4 in 2010. This is not surprising if one looks closer to how Google treats employees. On their Mountain View, California, campus called the “Googleplex,” employees are treated to free gourmet food options including sushi bars and espresso stations. In fact, many employees complain that once they started working for Google, they tend to gain 10 to 15 pounds! Employees have access to gyms, shower facilities, video games, on-site child care, and doctors. Google provides 4 months of paternal leave with 75% of full pay and offers $500 for take-out meals for families with a newborn. These perks create a place where employees feel that they are treated well and their needs are taken care of. Moreover, they contribute to the feeling that they are working at a unique and cool place that is different from everywhere else they may have worked.

In addition, Google encourages employee risk taking and innovation. How is this done? When a vice president in charge of the company’s advertising system made a mistake costing the company millions of dollars and apologized for the mistake, she was commended by Larry Page, who congratulated her for making the mistake and noting that he would rather run a company where they are moving quickly and doing too much, as opposed to being too cautious and doing too little. This attitude toward acting fast and accepting the cost of resulting mistakes as a natural consequence of working on the cutting edge may explain why the company is performing much ahead of competitors such as Microsoft and Yahoo! One of the current challenges for Google is to expand to new fields outside of their Web search engine business. To promote new ideas, Google encourages all engineers to spend 20% of their time working on their own ideas.

Google’s culture is reflected in their decision making as well. Decisions at Google are made in teams. Even the company management is in the hands of a triad: Larry Page and Sergey Brin hired Eric Schmidt to act as the CEO of the company, and they are reportedly leading the company by consensus. In other words, this is not a company where decisions are made by the senior person in charge and then implemented top down. It is common for several small teams to attack each problem and for employees to try to influence each other using rational persuasion and data. Gut feeling has little impact on how decisions are made. In some meetings, people reportedly are not allowed to say “I think…” but instead must say “the data suggest….” To facilitate teamwork, employees work in open office environments where private offices are assigned only to a select few. Even Kai-Fu Lee, the famous employee whose defection from Microsoft was the target of a lawsuit, did not get his own office and shared a cubicle with two other employees.

How do they maintain these unique values? In a company emphasizing hiring the smartest people, it is very likely that they will attract big egos that may be difficult to work with. Google realizes that its strength comes from its “small company” values that emphasize risk taking, agility, and cooperation. Therefore, they take their hiring process very seriously. Hiring is extremely competitive and getting to work at Google is not unlike applying to a college. Candidates may be asked to write essays about how they will perform their future jobs. Recently, they targeted potential new employees using billboards featuring brain teasers directing potential candidates to a Web site where they were subjected to more brain teasers. Each candidate may be interviewed by as many as eight people on several occasions. Through this scrutiny, they are trying to select “Googley” employees who will share the company’s values, perform at high levels, and be liked by others within the company.

Will this culture survive in the long run? It may be too early to tell, given that the company was only founded in 1998. The founders emphasized that their initial public offering (IPO) would not change their culture and they would not introduce more rules or change the way things are done in Google to please Wall Street. But can a public corporation really act like a start-up? Can a global giant facing scrutiny on issues including privacy, copyright, and censorship maintain its culture rooted in its days in a Palo Alto garage? Larry Page is quoted as saying, “We have a mantra: don’t be evil, which is to do the best things we know how for our users, for our customers, for everyone. So I think if we were known for that, it would be a wonderful thing.”

Based on information from Elgin, B., Hof, R. D., & Greene, J. (2005, August 8). Revenge of the nerds—again. BusinessWeek . Retrieved April 30, 2010, from http://www.businessweek.com/technology/content/jul2005/tc20050728 _5127_tc024.htm ; Hardy, Q. (2005, November 14). Google thinks small. Forbes, 176 (10); Lashinky, A. (2006, October 2). Chaos by design. Fortune , 154 (7); Mangalindan, M. (2004, March 29). The grownup at Google: How Eric Schmidt imposed better management tactics but didn’t stifle search giant. Wall Street Journal , p. B1; Lohr, S. (2005, December 5). At Google, cube culture has new rules. New York Times . Retrieved April 30, 2010, from http://www.nytimes.com/2005/12/05/technology/05google.html ; Schoeneman, D. (2006, December 31). Can Google come out to play? New York Times . Retrieved April 30, 2010, from http://www.nytimes.com/2006/12/31/fashion/31google.html ; Warner, M. (2004, June). What your company can learn from Google. Business 2.0, 5 (5).

Discussion Questions

• Do you think Google’s decision-making culture will help or hurt Google in the long run?
• What are the factors responsible for the specific culture that exists in Google?
• What type of decision-making approach has Google taken? Do you think this will remain the same over time? Why or why not?
• Do you see any challenges Google may face in the future because of its emphasis on risk taking?

Organizational Behavior Copyright © 2017 by University of Minnesota is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Distributed leadership at google: lessons from the billion-dollar brand.

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By any standard or metric, Google is a standout company, and perhaps the main reason for its superiority is its remarkable style of leadership. What employee turnover or attrition? That enviable style, however, was not established overnight. At least, not quite, as readers will learn.

Google now provides free net-search services in more than 120 languages, with a large number of web-based products in its portfolio and generates about 97 percent of its revenue through online advertisements (Google Adwords and Adsense). The Google brand is valued at USD 100 billion, making it the world’s first ‘one-hundred billion brand.’ In 2009, Fortune magazine ranked it as the best place to work in the U.S., which is indeed a tribute to the company’s leadership and people-management practices.

Like many other well-known companies, Google Inc. too had a garage startup. When Larry Page and Sergey Brin met in the Stanford PhD program in computer science, they developed the idea of a search engine company. They decided to drop out of the PhD program and to launch the new company from a friend’s garage, which they did in 1998. Both Page and Brin have academic ancestries: Page’s father, Dr. Carl Victor Page, was a computer science professor at Michigan State University; Brin’s father and paternal grandfather were both mathematicians, and his mother was a research scientist with NASA. Brin was Russia-born and emigrated to the U.S. when he was six years old.

Both Page and Brin were researchers at heart (though neither of them completed their PhD). Their venture was a rather ‘unanticipated’ outcome of their research project on “The Anatomy of a Large-scale Hypertextual Web Search Engine.” The search engines available at that time were not very efficient in quickly finding the most relevant results for the user. This issue was becoming increasingly complex, with the explosive growth of the materials on the web. Hence, the duo took up the challenge of designing an efficient system for crawling information from the web, keeping the crawled information up to date, storing the indices efficiently, and handling many queries quickly. In the process, they developed the PageRank technology (now proprietary to Google), which ranks the quality of each web page using a complex calculation of link structure based on the linkages among web pages. Their confidence in their invention was so high that when selecting a name for their company they picked up a modification of a mathematical term (GOOGOL, which is the name of the number represented by 1 followed by 100 zeroes). In doing so, they indirectly conveyed the company’s unique vision to organize and procure ‘infinitely’ large amounts of information for users, and possibly make as much money.

The Google style

The academic ancestry of the founders and their own inclinations for independent thinking and research may have had an impact on their leadership style, especially in matters of empowering their employees and encouraging them to come up with innovative ideas and implement them. They have a policy of recruiting only class-A employees and giving them the freedom to exercise their creativity. While there could be some cost saving in recruiting class-B people, it would push the organization into mediocrity in the long run.

There is a 70-20-10 norm about time allocation by employees: 70 percent of the time should be devoted to Google’s core business of search and advertising, 20 percent to off-budget projects related to the core-business, and 10 percent to pursue ideas based on one’s own interest and competencies. There are also generous rewards and awards for implementing innovative ideas. Though employees perceive such systems as perks, the company sees these systems as “the seed corn for its future,” as it would ensure that entrepreneurial employees implement their innovative ideas within the company rather than go out and create a competing new venture. It is estimated that about 50 percent of Google’s new products are generated using the ‘free’ time that employees are granted.

Leadership that empowers

Interestingly, the choice of a new product or strategy is not dictated by the founders nor is it based on the grandeur of its sponsor’s title. Ideas must compete on their merits, in a ‘Darwinian environment’ of survival of the fittest. Many of Google’s popular products and strategies came on the market through this process, as exemplified by the creation of Gmail by Paul Buchheit, or the informal motto of the company (“Don’t be evil”) coined by Buchheit and Amit Patel. Though this slogan does not appear in the exposition of the official management philosophy of Google, it was a major theme in the founders’ letter in connection with their 2004 IPO, so much so that this letter was subsequently called the “Don’t-Be-Evil Manifesto.” The basic thrust of this manifesto is that one should not exploit customers’ ignorance, but should be ready to forego short-term gains if this is what is required to provide sustainable services to society. One specific implication of this belief is that the company will not strive to get the authentic search content confused with or influenced by the advertised material.

Who wouldn’t want to work for Google

Communicating the vision and granting employees the freedom to implement it is one part of Google’s people-management system. The other is to provide the employees with a hassle-free environment so that they can concentrate fully on work. In other words, the goal is to strip away everything that gets in the employees’ way. The company provides a standard package of benefits to employees that it tops up with a seemingly endless – and highly enviable – array of perks: first-class dining facilities with a free and unlimited supply of wholesome food, snack stations in various parts of the office, gyms, laundry rooms, massage rooms, haircutting salons, car washes, dry cleaning services, commuting buses equipped with bike racks, leather seats, internet access, and facilities to carry pets onboard — and just about anything a hardworking employee might want to be taken care of while he/she is at work. In fact, employees don’t even have to worry much about getting dressed up, as Google’s corporate vision includes such axioms as: “You can be serious without a suit.”

Leadership’s policy of empowering and facilitating employees’ work has led to a large number of innovations and, consequently, to the explosive growth of the company. As a startup, Google had relied primarily on the personal funds of the founders.  “We had to use all of our credit cards and our friends’ credit cards and our parents’ credit cards”, recalls Larry Page. Finally, Page and Brin decided to bring in venture capitalists. They also started to allow unobtrusive text advertisements alongside search results. By 2000, the company had started making a profit.

The founders managed the company until 2001, with Larry Page as the CEO. By the year 2001, Google had grown to more than 200 employees, and it had widened its board to include representatives of the venture capitalists. They brought in a professional manager, Eric Schmidt, as the CEO, with the responsibility for providing the organizational and operational expertise and company leadership. Page and Brin continued to provide the engineering, technological, and product development leadership – Page as President of Products, acknowledged as the company’s thought leader, and Brin as President of Technology, with the responsibility for advertisements, the major source of the company’s revenues. Thus, the foundation of the leadership triumvirate at Google was laid in the year 2001.

Between 2001 and 2004, the salaries of the top three executives were US$250,000 per annum for Schmidt, and US$150,000 each for Page and Brin. However, just before the IPO in 2004, the trio asked the board to cut their salaries to US$1, with a view to boosting investor confidence in the company. This was indeed a smart move whereby the leaders could convey to potential investors the immense confidence they had in their company’s performance and tell them that they were willing to link their own remuneration to the market performance of their company.

They also adopted an innovative method for fixing the price of the IPO; they used a Dutch auction, in which the market determined the initial stock price, and that helped prevent insiders and institutions from selling immediately for a quick profit. Their confidence in their own company and the market was not misplaced. Schmidt’s 12.45 million shares of Google are now worth about US$4.86 billion. Similarly, Brin’s 31.6 million shares and Page’s 32 million shares are each worth more than US$12 billion. Considering the strong performance of the company following the IPO, the board in 2006 offered to raise the salaries of the top trio from the nominal amount of US$1. All three declined.

As pointed out by Ken Auletta in his book, Googled , Eric Schmidt was primarily the choice of venture capitalist and Google board member John Doerr, which was why others viewed him apprehensively, at least initially. His past performances gave out mixed messages. He had been a successful chief technology officer at Sun Microsystems in its glory days, but had performed poorly in his one stint as CEO at Novell . Besides, there was worry that the Mercedes he drove and the suit and tie he wore would not go down well with Google’s informal culture. In any case, nobody thought that he was an inspirational leader, a great speaker or salesman, a take-charge leader like Paul Otellini of Intel, Carol Bartz of  Autodesk, or John Chambers of Cisco. While the founders themselves shared some of the apprehension, Schmidt’s staunchest critic was another venture capitalist member of the board, Michael Moritz of Sequoia Capital. He felt that Schmidt lacked the toughness required for pushing ahead with the revenue plan based on the advertising formula being experimented with during 2001-02.

But for a company like Google, which took pride in its “distributed leadership” culture, it was perhaps possible that the patient, unobtrusive engineering management style of the mild-mannered Eric Schmidt was better than the more aggressive, go-getter style of individual-oriented leadership. However, it took some time and another intervention by John Doerr, who brought in Silicon Valley’s best-known management coach, Bill Campbell, to mentor and coach the triumvirate and mediate between the new CEO and the founders as well as the two VCs, Moritz and himself.

Campbell, then 61, was probably the right person to mediate between the founders, then in their twenties, and the new CEO, who was 20 years older than they were. Campbell’s prior work experience also added credibility to his new role. He had once been Columbia University’s head football coach, a senior executive at Apple, and the CEO of several Silicon Valley companies, including Intuit. His major contribution was to take emotion out of the decisions and help the principal decision-makers evaluate the options in an objective manner. It would not be an exaggeration to say that the mentoring and mediation by Bill Campbell have made a major contribution to the development of Eric Schmidt into a ‘Superman CEO’ who could win over not only the founders but also the ever-skeptical, venture-capitalist critic on the board, Michael Moritz. Google’s results speak for its performance. The company reached $1 billion in revenue in six years, 10 years faster than Microsoft. In April 2007, Schmidt was elected chairman of the board while simultaneously holding the position of CEO. In 2011, Schmidt became the Executive Chairman, as Larry Page once again assumed the post of CEO.

Eric Schmidt’s best leadership practices

Analysts are of the view that, though Eric Schmidt came from a corporate background, his leadership style had many things in common with the culture already created and put in place by the founders of Google.

Schmidt’s leadership practices could be summarized in the following five precepts:

1. Get to know your employees.

2. create new ways to reward and promote your high-performing employees., 3. let your employees own the problems you want them to solve., 4. allow employees to function outside the company hierarchy., 5. have your employees’ performance reviewed by someone they respect for their objectivity and impartiality..

Examples of such behavior include the following:

• Schmidt used to make a list of his best employees, as identified by multiple levels of peer-references, and interact with them personally to encourage them to implement their innovative ideas and to insulate them from unwanted interferences by others.
• For rewarding high performers, there were a few systems already in place, such as financial incentives, stock option plans, dinner with the CEO, and so on. In addition, Schmidt created a five-hour long video called The Factory Tour, where the protagonists themselves would explain the idea and its working.
• In order to make the employees the owners of their work, Schmidt used to provide a very broad definition of the company goal and leave the implementation entirely to the employees. In defining the goal, care was taken to highlight the benefits to the customers and society at large rather than to the company.  For example, Schmidt has defined Google’s goal as: “Organizing the world’s information and making it universally accessible and useful.” This is something that every employee can easily relate to, compared to a statement of company targets like increasing turnover by 200 percent.
• As corporate hierarchies can often obstruct employees’ work, Schmidt reinforced the existing system of allowing employees a certain degree of freedom to create their own projects and choose their own teams.
• In reviewing employees’ performance, Schmidt made it a point to identify reviewers from among professionals whom the concerned employee respects for their objectivity and impartiality.

The happiness trickles down and out the door

The leadership practices of the triumvirate cascaded throughout the organization and had an enormous impact on the cadres. According to Laszlo Bock, Google’s innovative Senior Vice-President for Human Resources, the teams working under the best managers perform better, are happier, and stay longer with the company. He therefore initiated a project to identify the key qualities of such managers based on an analysis of data available and collected internally. His research team has come up with the following eight qualities of leader-managers at Google (listed in the order of importance as identified by the study):

• Be a good coach
• Empower your team and don’t micromanage
• Express interest in your team members’ success and well-being
• Be productive and results-oriented
• Be a good communicator and listen to your team
• Help your employees with career development
• Have a clear vision and strategy for the team
• Have technical skills so you can advise the team

The qualities identified are amazingly simple and do not require a manager to change his or her personality. Rather, the changes required are a matter of behavioral changes, which can be accomplished by regular and deliberate practice. Bock simplifies them further: “The two most important things I can do are to make sure that I have some time for them and to be consistent.” It may be noted, ironically, that though Google is a hi-tech company, having the technical skills has emerged as the least important among the eight qualities of leadership. Obviously, the quality of any technology will only be as good as the quality of the people who operate it.

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Case Study: How Google Boosts its Employees’ Engagement

You might have heard about this mantra: ‘Happy employees produce better results.’ This is the mindset of Google to keep its employees productive and satisfied. This article explains more.

Let’s say you’re a company providing software development services . If your developer’s team isn’t enthusiastic about their projects every day, you’re not going to achieve excellence. This is productivity’s power. But remember productivity is dependent on the company’s culture.

Why is everyone talking about Google’s culture or work environment? We know that Google is one of the most influential and powerful companies around the globe. The company follows a pretty well unique culture instead of corporate culture.

It has something that every big organisation needs to follow to level up their employees’ engagement or morale. The culture of any company is vital to its success and Google is perfectly right on the track.

It has one sole purpose:  Keep the employees happy and keep up the productivity.

Google has been at number ONE place from the past six years and featured on  Fortune’s  annual list of  ‘Best Companies to Work For.’  And this is not it. Google has also been named as the tech company with the best culture. (Reported by Forbes) Furthermore, Google has a 4.4 rating on  Glassdoor  based on 6000+ employees reviews.   

Google’s morale

This is what the employees of Google answered the questions asked about their work culture.

• Acknowledged for the efforts?

Yes: 61 % Employees

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No: 39% Employees

• Job Security?

Very Secure: 34 % Employees

Neutral: 19% Employees

Insecure: 8% Employees

Very insecure: 5% Employees

• Work Environment?

Positive: 85% Employees

Negative: 15% Employees

• Excited about going to work daily?

Yes: 80% Employees

No: 20% Employees

So, without further ado, let’s move towards the ways Google uses to boost its employees’ engagement .

“There are way easier places to work, but nobody ever changed the world on 40 hours a week. But if you love what you do, it (mostly) doesn’t feel like work.”- Elon Musk.

How Google Keeps Its Employees Productive And Engaged?

Exclusive perks.

Today, employees want a job in a company that makes them love what they do. Never for financial benefit or intellectual recognition. Yet instead of chance to add to the common good.

The major differentiator is to make a real difference.

Google offers different perks to its employees to show them that they are not only investing in their overall health but their future as well.

• Chef-prepared free organic food (breakfast, lunch, and dinner);
• Free dental and health checkup;
• Free and unlimited dry cleaning;
• Subsidised massages;
• Several foosball, ping pong, video games stations;
• On-site physicians;
• Gyms/swimming pools memberships;
• Free haircuts from professional hairdressers;
• In-house nap pods;
• Death benefits to deceased employees’ families, and;
• Hybrid car subsidies.

Flexibility

Google has been one of the very first companies that had a vision of understanding the employees’ needs. It lets its workers have a flexible schedule so that they can work on their terms and enhance creativity and productivity. They have given their employees complete freedom to work in a way that is most suitable to them.

Knowing the employees well

Google had gone through a series of laboratory tests to figure out the productivity of their employees. They had four different experiments that included 700 participants. All the employees were treated to free drinks, fruits, and chocolates or shown a comedy movie clip.

They also enquired some of the participants about the family tragedies as a part of their assessment. After this, they found that happiness is the reason for 12% more productivity.

Google promotes an innovative and diverse organisational culture that has been a part of its employee’s life. A positive creative atmosphere and a safe working space offered by Google to its workers keep them comfortable and happy at work. The concept that being a part of Google is about being smart and wise encourages the employees to think openly and keeps them productive.

Nowadays, there are different creative coworking spaces which are known to be a perfect alternate to a workplace. These spaces are believed to deliver various advantages such as strong networking and increased engagement.

Google’s founders were researchers who had a belief in innovation and freedom of thinking. This is one of the main factors that influenced the style of Google’s leadership.

According to Brassfield, 2013, a positive leadership style stimulates inspiring and motivating employees to develop innovative ideas and inventions.

Keeping people inspired

Future Workplace, in 2017, demonstrated in a study that one of the biggest threats to employees’ engagement is employee burnout. It has also been found out that many proficient workers are often overburdened with the tasks that lead to halted innovation, incomplete work, etc.

What does Google do about keeping its employees productive, inspired, or motivated? Google’s strategy for this is  20% time . Every employee devours up to 20% of his time at work each week on ventures that inspire him.

This concept inspires employees as it allows them to concentrate on things they love or are passionate about. It can prevent burnout, decrease turnover, increase engagement.

Image: Pexels

Career development

Google provides an extensive professional growth program that is successful and creative and guarantees long-term performance for all the employees. The career development program of Google is one that ensures incentives are provided to employees to meet their professional and personal progression.

Google has adopted a unique way to promote the professional development of all its employees. CareerGuru  is a career coaching that provides all the details to the employees by Google’s leaders about working at a specific role in the company.

Creativity Encouragement

The companies that believe in fostering a culture of creativity have happy, satisfied, and motivated employees. Google leads the way in promoting creativity in their employees.

They are free to express their ideas as a solution to any problem. Moreover, employees are encouraged to work wherever they are comfortable in the workplace. Google has a set up where rather than just considering an applicant’s professional background, they look to recruit people who are normally inquisitive and fond of learning.

Trusting Employees

Google believes in trusting their workers because trusted employees feel more valuable. It can also boost the sense of job satisfaction and can also decrease the rate of staff turnover.

In a survey by PwC, reliable employees are 76% more engaged in their work than those in a low trusting environment. Trusted employees are happier and they have the urge to go the extra miles.

Culture based on qualitative data

Google has always been searching out different ways to optimise the performance of its employees while ensuring their happiness and satisfaction. Everything done at Google is based on real data. They use the qualitative and quantitative facts to set up processes and every single rule that is streamlined.

Google has additionally performed researches to discover how much paid time off new mothers would need and ways of building an improvised and better culture.

Fun workplace

Have you ever been allowed to design your own workstation at your company?

Probably not. But Google does it. It lets the employees design their desks or workstations.

When you see the pictures of the workplace, it seems an interesting adult play and work area and not a dull and lifeless space.

Google has always tried to push the boundaries of its workspace.

Collaboration of coworkers

At Google, the employees are urged to collaborate. They have a program called ‘Googler to Googler’ to keep them productive and promote skills such as management, public speaking, orientation, or extracurricular activities.

It is crucial to build a sense of community to create a positive culture. The company has arranged several micro kitchens around the whole workspace where coworkers can have a little chit-chat session. No one has to spend time on deciding where to eat because Google has various break-out spaces for lunch.

Google’s way of listening

Google employees have developed great software and projects that include Gmail, AdSense, Google News, etc. and all these big projects were originated because of its staff productivity approach. Google has a way of collecting employees’ feedback and listening to their suggestions that is  gDNA.

• The employees utilise a device ‘Google Moderator’ , the result of 20% time strategy, to inquire about something and vote on inquiries of others;
• The company holds a meeting, every Friday, where the managers react to the most famous inquiries of the week;
• Leaders or managers utilise a charting instrument called Google-O-Meter to measure the prominence of various worker bits of advice;
• Leaders likewise plan “Fixits” to comprehend huge, critical issues; and,
• Fixits are 24-hour runs where team members give their full focus around discovering solutions for explicit issues.

So, can Google teach us anything?

If you are planning to adopt these learnings at your organisation just like Google keeps its employees productive, it’s essential to test the progressions first and measure the results.

It’s a great deal of work, however, the engagement advantages will make the difficult function admirably justified.

About the Author

Usman Akram is a digital marketer and SEO specialist who’s passionate about experimenting and discovering new SEO tactics and strategies to dominate search rankings while bringing an unmatched user-experience. As of now Usman is serving Buzz Interactive , a leading digital marketing agency as the head of SEO.

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Growing A Culture Of Innovation: 5 Lessons From Google

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Organizations are facing unprecedented change and challenges stemming from a confluence of natural and artificial conditions. These forces are driving many to rethink the tools and technologies they use, and the places they need to be, to grow and to innovate. Below, Vinton G. Cerf, Vice President and Chief Internet Evangelist at Google, shares five lessons on growing a culture of innovation.

Culture is always a work in progress.

1. Sustained competitive advantage cannot be achieved with technology alone.

To create a more innovative business, you must rethink how people, structures, and processes interact every day—we refer to this as organizational culture. The teams you rely on to build must have systems and processes that keep them engaged, amplify their ability to produce, and keep them consistently forward-looking.

At Google, we’ve spent years thinking about how to maintain and improve a culture that fosters transformation and innovation. This has led to alignment around certain core principles that have informed our approach and supported Google’s culture for two decades. 

2. Measure, make decisions, and be transparent in that process.

Measurement is at the heart of everything we do at Google. We measure everything—from how our systems are running, to how productive we are, to how people are feeling. All the data we gather is extremely valuable, because it exposes problems faster than if we simply scratched our heads and wondered. Once we gather that data, we still need to spend some time interpreting it, but at least we have a basis for judging how well our organizational structure is working. 

It’s important to recognize that a feedback system only works when people believe changes will be made as a result of their feedback.

A culture of measurement results in a collection of anecdotal information as well as quantitative data. Both are necessary to inform change. We perform a number of different measurements—for example, encouraging everyone to participate in an anonymous employee satisfaction survey every year. That data and that feedback loop facilitate our decisions to change how we’re doing things, as needed.

Once we’ve gathered the data and made a decision, it’s time to actually put those changes into motion. It’s important to recognize that a feedback system only works when people believe changes will be made as a result of their feedback. So the trick is to ask the questions and then actually do something with the result. 

Transparency is another important part of Google culture. It’s important that we be transparent about the feedback we heard, and how we went about addressing it. Being transparent as a company increases customer trust on one hand, and employee trust on the other. It’s important that people understand why we prioritized the changes we made. That’s core to the company’s DNA.

3. Don’t be afraid of failure.

Sometimes science learns more from failure than it does from success. If you ask why something didn’t work, you often learn more than you would have if it actually did work. And so, even at Google, we try a lot of things out that don’t work—and we learn from them and refine our practices. And eventually, we hope, we get to the point where the things that we want to work actually do work. Science is a lot like that. Google is a lot like that as well.

You have to have the willingness to allow failure. I’m not suggesting we should fail all of the time—that would be a problem! I’m talking about the freedom to try things out without absolute certainty of success. This is the fundamental difference between engineering and research. 

With research, you don’t start off knowing the answer. With engineering, you think you know the answer, and you just have to build it. But what can happen with engineering is that you build it and then it doesn’t work. These two disciplines interact in the most wonderful ways. The engineer says, “I built it and it didn’t work.” The researcher says, “Why not?” And the engineer says, “I don’t know, can you help?” Together, they discover there’s a fundamental reason why this particular path for implementation didn’t work—and they learn from that. And then you get to develop a new design that takes this into account. 

At Google, we’ll go down a number of different paths as we explore new capabilities in the system, and we often encourage people to go down these paths, even if they might end up at a dead end. And we share, blamelessly, with others the fact that there was a dead end, so everyone learns. That’s how we advance everybody’s ability to carry out their work.

4. Don’t forget that culture is always a work in progress.

Over time, as the mix of people joining the company changes and as the scale of the company gets bigger, we have to remind people about the cultural norms that we would like to maintain. 

You have to periodically refresh the cultural elements that matter.

For example, one of the things that Google tries to accomplish is to give people the freedom to try things out, which resulted in a policy of allowing engineers to spend 20% of their time doing things that they weren’t originally assigned to do. People use 20% time to learn outside of their assigned duties and it actually acts as a stabilizing component of employee satisfaction.

The idea of 20% diminished for a while as we grew, until we reminded everybody that that 20% was fundamental to Google and was a cultural element that we wanted to maintain. It’s important to remember that you have to periodically refresh the cultural elements that matter.

5. Stay open.

If I were trying to give advice to an enterprise CIO, one of the things I would say is this: Don’t think that you have all the answers. In fact, the probability is very high that you don’t have very many of them at all. Take advantage of opportunities to share knowledge with your colleagues, your friends, even your competitors to better understand what others have learned in order to solve the same problems you have. Openness is your friend. The same thing is true when it comes to not taking all the credit. It’s important to acknowledge other people’s contributions because it gives them the incentive to continue contributing. And so this kind of openness of spirit is just as important as openness of ideas.

Technology alone does not guarantee success. You need a culture that supports change and acceleration—which paves the way for innovation. People have always powered technology, and today that’s especially true as teammates must collaborate and solve big problems together, even if they’re not in the same room. Fostering a culture of innovation helps lead to identification of new opportunities, and quick action to create new ideas and get ahead of the competition.

Keep reading: Discover three steps any organization can take to quickly adapt and achieve positive results with tighter resources. Get the guide .

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Culture at Google

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Google’s (Alphabet’s) Organizational Culture & Its Traits

Google’s (Alphabet’s) organizational culture or company culture reinforces the business as one of the leading companies in the online technology and digital advertising industries. This organizational culture or corporate culture is the set of traditions, customs, core values, and behavioral ideals that influence the workplace behaviors of the technology company’s employees. This work culture motivates Google’s employees to support innovation. Innovation is a factor that enables the company’s profitability against competitors, such as the consumer electronics businesses of Apple , Samsung , Microsoft , and Sony ; the online advertising operations of Facebook , eBay , and others; the video streaming services of Netflix, Amazon , and Disney ; and the Internet connection services of Verizon . Through its company culture, Google ensures workforce competence. The technology business actively develops its corporate cultural strengths through institutional measures, such as employee training, and through informal approaches, such as personalized leadership and management support. Creativity and innovation are maintained through the continuous improvement of Google’s organizational culture and its traits.

The features of Google’s company culture focus on enhancing employee performance. The company uses this work culture to effectively motivate its human resources. For example, in developing solutions to target customers’ everyday problems, Google’s work culture motivates workers to think outside the box and to aim for novel ideas. In this way, the organizational culture facilitates human resource support for various strategies, such as Google’s (Alphabet’s) generic competitive strategy and intensive growth strategies . This strategic support coming from the company culture is a success factor in the international market for Internet services, digital advertising, cloud computing services, hardware and software, and consumer electronics.

Traits of Google’s (Alphabet’s) Organizational Culture

Google has an organizational culture for innovation, especially technological innovation. Alphabet emphasizes the importance of openness among employees, as a way of promoting an innovative mindset suited to the technological nature of the business. The company culture leads to innovation that applies to Google’s approaches to competing in various industries. This work culture helps the company innovate its technological assets and the services it provides to customers in the online advertising industry. The following characteristics define Google’s culture:

• Innovation, especially technological innovation
• Smartness with excellence
• Hands-on approach
• Small-company-family rapport

Openness . This cultural characteristic refers to open-mindedness and information sharing among Google’s employees. The company’s objective in promoting openness through its organizational culture is to encourage the dissemination of valuable knowledge that can support further technological innovation. For example, the corporate culture motivates individual employees to share new knowledge and work-related learning about technological solutions to customers’ needs identified in the market. In relation, operations management at Google (Alphabet) supports this cultural trait through workplace layouts that facilitate knowledge sharing and human resource enhancement. Also, the design of Google’s (Alphabet’s) organizational structure (business structure) supports the business culture by encouraging workers to communicate and share their ideas.

Innovation . Innovation is a critical success factor in Google’s business. This trait of the work culture supports the technology-focused goals of Google’s (Alphabet’s) mission statement and vision statement . The company’s organizational culture motivates employees to contribute to the innovation of the business and its products, such as online software. This characteristic of the corporate culture motivates employees’ out-of-the-box thinking to discover or invent new technological solutions to current and emerging needs in the multinational market. Innovation contributes to business effectiveness in addressing the technological and related sociocultural trends enumerated in the PESTLE/PESTEL analysis of Google (Alphabet) . This business condition means that the organizational culture helps ensure that innovation processes adjust according to relevant business needs identified in the information technology and online services market.

Smartness with Excellence . This characteristic of the corporate culture focuses on achieving excellent results in all areas of Google’s business organization. Such an organizational culture trait is integrated in human resource development programs to inculcate an appreciation for excellence among the technology company’s employees. For example, Alphabet’s training programs are designed to motivate workers to continually improve their output, and to not settle for mediocre technological ideas and solutions. Thus, Google’s work culture promotes smartness in the workforce, and pushes employees to strive for excellent results in their work.

Hands-on Approach . Through its corporate culture, Google applies a hands-on approach to human resource development. This cultural trait focuses on using experiential learning to improve employees’ knowledge, skills, and abilities, in support of excellence in technological innovation. Theoretical knowledge is not enough at Google. The company culture creates the expectation that workers learn new technical knowledge and skills as they continue their journey as members of the company’s organization. This feature of Google’s organizational culture is implemented through policies that support employees’ involvement in projects and experiments. Such experiments test new ideas in support of product development and innovation, which affect Google’s (Alphabet’s) marketing mix or 4P . In this way, the information technology company’s work culture enhances employees’ experience, including on-the-job learning and training, which contribute to human resource competencies.

Small-Company-Family Rapport . Google is known for its support for small-company-family rapport in its workspaces. This trait of the organizational culture focuses on the social interactions among workers in the technology business. For example, Google maintains a warm work environment where employees can easily talk and share ideas with each other. The objective is to use the company culture to help optimize Alphabet’s internal communications and idea generation for technological innovation. This characteristic of the work culture also positively contributes to employee morale at Google. Warm social relations in the workplace facilitate employees’ satisfaction in their jobs and enhance the results of the technology company’s human resource management strategies.

Insights and Recommendations for Google’s (Alphabet’s) Culture

Google’s organizational culture is specific to addressing the needs of the information technology and online services business. For example, through the cultural trait of innovation, the company ensures that its products satisfy industry standards and are at the leading edge of technological development. In this condition, the work culture contributes to the strengths enumerated in the SWOT analysis of Google (Alphabet) . As one of the biggest technology businesses in the global market, the company is an example of effective organizational design and human resource development manifested in the corporate culture.

A possible improvement to Google’s organizational culture is the further intensification of information sharing. Currently, even though the traits of the business culture support communications and information sharing, such sharing occurs in a highly controlled manner. Google can adjust its organizational culture to increase employees’ degree of freedom to maximize the speed and efficiency of knowledge transfer. This recommendation aims to increase the rate of technological innovation in the company’s product development processes. In addition, Google can improve its work culture through additional human resource programs that are designed to support specialized innovation-focused functions among individual employees. This second recommendation aims to use Alphabet’s company culture to increase employees’ knowledge, skills, and abilities for additional competencies in technological innovation.

• Alphabet Inc. – Form 10-K .
• Arena, M., Hines, S., & Golden III, J. (2023). The three Cs for cultivating organizational culture in a hybrid world. Organizational Dynamics, 52 (1), 100958.
• Google – Building a More Inclusive Workplace .
• Google – Our Belonging Philosophy .
• Kasperson, J. X., & Kasperson, R. E. (2022). Corporate culture and technology transfer. In The Social Contours of Risk (pp. 118-143). Routledge.
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Google Spent Years Studying Effective Bosses. Now They Teach New Managers These 6 Things

The transition to management requires a transformation of thought..

The transition from individual contributor to manager is not an easy one. In many cases, the skills that got you the promotion will not be the same ones that make you effective as a manager. Luckily, we have organizations like Google that have spent years researching this transition, to help us demystify the secrets to new managers' success.

Using Project Oxygen , an internal study that analyzed more than 10,000 manager impressions including performance reviews, surveys, and nominations for top-manager awards and recognition, Google identified eight habits of highly effective managers. Google also designed a management training workshop to share its newfound knowledge with its bosses and now the world.

Through the company's Re:Work website, a resource that shares Google's perspective on people operations, Google posted this training presentation in hopes that it could benefit all.

Let's take a look at the six key attributes that Google instills in its managers.

1. Mindset and values

Implementing research from Carol Dweck, professor of psychology at Stanford University, Google encourages its managers to develop a growth mindset. As opposed to a fixed mindset (the belief that skills and abilities are predetermined), individuals with a growth mindset believe that intelligence can be cultivated. This simple idea develops leaders who are more eager to learn, challenge themselves, and experiment, and it eventually boosts their performance. Although success will always require tenacity, hard work, and concentration, this research suggests these traits are byproducts of a quality that underpins them, optimism.

Also, Google encourages its managers to identify values and leverage them within their management styles. The purpose is not to impose set values, but rather to empower leaders to leverage their individual morals to drive deeper meaning and impact to their work. Managers have to make tough decisions. When faced with uncertainty, values can be a manager's saving grace.

2. Emotional intelligence (E.I.)

Per Daniel Goleman and Richard Boyatzis (experts on the topic), E.I. is the ability to recognize and understand emotions in yourself and others, and leverage this awareness to manage your behavior and relationships. In other words, it's a heightened sense of self-awareness.

Managers who are self-aware make better decisions, communicate more effectively, and are more relatable. In fact, Goleman reported not only that E.I.-based leadership may be the most important driver of climate but also that climate may account for 20 to 30 percent of organizational performance.

3. Manager transition

All right, so this one doesn't seem like an attribute. However, if you take a look at Google's new manager training facilitator's guide , you'll notice some common themes. As instructors encourage new supervisors to share their transition challenges and frustrations with their peers, they simultaneously teach that it's OK to be vulnerable and honest. As managers open up and tell their stories, others chime in with advice and guidance providing actionable new strategies.

It's important for all managers to know that you're not in this alone. Others have faced similar challenges and can help -- if you let them.

4. Coaching

Through Project Oxygen, it was revealed that the number one quality of effective managers is being a good coach. Google defines good coaching as:

• giving timely and specific feedback;
• delivering hard feedback in a motivational and thoughtful way;
• tailoring approaches to meet individual communication styles in regular one-on-one meetings;
• practicing empathetic "active" listening and being fully present;
• being cognizant of your own mindset and that of the employee; and
• asking open-ended questions to discover an employee's acumen.

5. Feedback

Managers' words have the power to build or destroy. Google understands this sensitivity and teaches its supervisors to be consistent (free from bias) when delivering feedback across their teams, to balance positive (motivational) and negative (developmental) feedback, to be authentic and appreciative, and to state growth opportunities in a clear, compassionate way.

6. Decision making

To ensure judgments aren't made in a vacuum, Google has established a routine to help managers make better decisions. This framework includes asking and articulating:

• What are you solving for, and is everyone on the same page? (Identify and communicate the root cause.)
• Why is it important? (Does it support other business goals?)
• Who is the decision maker?
• How will the decision be made?
• When can people expect a decision? (Keep stakeholders in the loop, and manage expectations.)

Also, to ensure informed decisions are made, Google encourages managers to test their ideas out loud and collect feedback by explicitly advocating for their opinions (voicing individual views, reasoning, and providing data), testing their understanding by inquiring about others' perspectives (soliciting ideas and feedback), and then synthesizing the responses to ensure a comprehensive understanding before making a decision.

While these six attributes may seem basic, according to a New York Times article , the results are anything but. Google reported a statistically significant improvement in 75 percent of its underperforming managers after implementing the program.

A refreshed look at leadership from the desk of CEO and chief content officer Stephanie Mehta

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Home » Management Case Studies » Case Study on the Managerial and Leadership Philosophies: Triumvirate Leadership at Google

Case Study on the Managerial and Leadership Philosophies: Triumvirate Leadership at Google

This case focuses on the managerial and leadership philosophies , policies and behaviors of the leadership triumvirate at Google. Sergey Brin and Larry Page, the founders of Google, along with Eric Schmidt, constitute the leadership triumvirate. Brin is president of technology and assumes responsibility for advertising initiatives. Page is president for products and is acknowledged as the company’s thought leader. Together, Brin and Page provide the engineering, technological, and product development leadership for Google. Eric Schmidt is Google’s chairman and chief executive officer, and he is charged with providing the organizational and operational expertise and leadership for the company.

In 1998, while they were doctoral students at Stanford University, Sergey Brin and Larry Page founded Google. In 2001, Brin and Page recruited Eric Schmidt to be Google’s chief executive officer. Schmidt was charged with providing the organizational and operational expertise and leadership for Google, while Brin and Page provided the engineering, technological, and product development leadership. As some pundits have said, Page and Brin knew they weren’t professional managers or marketers or masters of strategy, so they brought in a “grown-up,” Eric Schmidt, to operate the company.

Google’s success can be attributed to its triumvirate leadership of Brin, Page, and Schmidt, “who have managed to beat back rivals from Yahoo! to Microsoft.” However, one of the Google’s biggest mysteries is its leadership triumvirate and how it functions. Page is president for products and is acknowledged as the company’s thought leader and someone who gets involved in projects to make sure things get done. Brin is president of technology and assumes responsibility for advertising initiatives, which is the money-making part of Google.

Nonetheless, Brin and Page seem to be the dominant forces in the company because their stock shares carry ten times as many votes as the ordinary stock shares. Moreover, Brin and Page “give themselves carte blanche to do what they like, buy what they like, diversify wherever they like and pay no dividends.”

The leadership triumvirate also has high expectations for Google employees. Google hires only class-A talent because Brin, Page, and Schmidt believe that hiring just one B-level person initiates a slide into mediocrity. The company has generous reward and award programs in order to ensure that employees with great ideas don’t launch their own entrepreneurial ventures. Moreover, Google essentially lets engineers run the show. Every Google employee divides his or her work time into three parts: 70% is devoted to Google’s core businesses of search and advertising; 20% is targeted toward off-budget projects related to the core businesses; and 10% is allocated to the pursuit of far-out ideas. The time allocation for off-budget projects and far-out ideas is more than a perk; “it’s Google’s seed corn for the future.”

But Google is not highly transparent for outsiders! Google seems to relish being secretive and opaque and confusing the competition. Perhaps this is no more apparent than in the leadership triumvirate’s apparently deliberately confusing comments on transparency and corporate strategy. In commenting on the need for transparency in business, Schmidt says, “with all the headlines we’re making, we don’t want our announcements to surprise or confuse anyone. We don’t want our partners to think we’re competing against them.” Schmidt continues, “we try very hard to look like we’re out of control. But in fact the company is very measured. And that’s part of our secret.” Page adds, “[w]e don’t generally talk about strategy ¼ because it’s strategic. I would rather have people think we’re confused than let our competitors know what we’re going to do.” Schmidt also says that he “intentionally propagated the perception of Google as a wacky place to allow the company to build up its business under the radar.”

Along with not being transparent to outsiders, Google has created some disharmony with them. By taking on Microsoft (desktop software), phone companies (a San Francisco wi-fi plan for free wireless Internet service), eBay (classified advertising), and others, Google has not been making friends. Google even seems to be offending its paying customers, and in some “parts of the business community, it is acquiring the image of a somewhat sanctimonious bully.” This is an interesting anomaly; particularly given Google’s famous slogan “ Don’t Be Evil” and its pro-consumer stance. Rather than creating disharmony, Google should have been winning friends.

1. In what ways are Brin, Page, and Schmidt leaders?

2. Describe the nature of followership that Brin, Page, and Schmidt have sought to develop at Google.

4. Use the concepts of transactional, transformational, charismatic, and authentic leaders to describe the leadership of Brin, Page, and Schmidt.

Related posts:

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• Case Study: Google’s Competitive Advantage
• Case Study: Analysis of Organizational Culture at Google
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Alphabet CEO Sundar Pichai on Leadership, AI, and Big Tech

A conversation about Google’s AI future.

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The use of artificial intelligence and specifically generative AI is growing rapidly, and tech giants like Google have an important role to play in how that technology gets adopted and developed. Sundar Pichai is the CEO of Google as well as its parent company Alphabet, which he’s led as an AI-first company for several years. He speaks with HBR editor in chief Adi Ignatius about shaping Google’s AI strategy, putting safeguards in place, and how work and leadership will change as AI advances.

ADI IGNATIUS: Welcome to the  HBR IdeaCast  from Harvard Business Review. I’m Adi Ignatius.

If you’re like me, you’re spending a lot of time these days talking about AI, specifically generative AI – products like ChatGPT that have the potential to remake how we do business, on almost every level.

Will this technology make us more productive? Will it eliminate huge categories of jobs? Will it create new ethical challenges?

Sundar Pichai is on the front lines of this evolution, and he has an immense opportunity to impact our generative AI future. He is the CEO of Google and its parent company Alphabet – a company with a market value of more than $800 billion. He’s been its CEO since 2015.

Pichai is remaking the company around the technology that we’re all thinking and worrying about: the rapid advancement of artificial intelligence – which is changing Google’s business model and which may change all of our business models.

I recently spoke with Pichai for an HBR Live event on leadership. We talked about generative AI, how he’s thinking carefully about Google’s role in the future, and the role of business leaders today. Here’s our conversation.

So let’s jump right in. So generative AI dominates almost every conversation I have these days. I think that’s true for a lot of people who are listening now. You’re really in the thick of it and I’d love just to start the conversation. How should we be thinking about what GenAI can deliver in the workplace now and maybe in the short-term future?

SUNDAR PICHAI: It’s definitely an exciting time indeed and feels like a point, a moment of inflection. The easiest way I would think about this is I think this notion even in the context of your workplace, to have an AI collaborator with you. Software engineers often do something called pair programming. We have found that two programmers working together are better than them working separately. So you can now imagine AI being your paired programmer or paired financial analyst or name if you will. So I think that’s the direction, that’s the promise and we are seeing it happen.

It’s definitely happening for programming, but we have clients like Deutsche Bank is now using generative AI to give insights to their financial analysts. You can imagine radiologists, as they’re looking at images, they have an AI collaborator which is triaging the pipeline for them, giving them suggestions in case they’ve missed something and so on.

So that’s the trend. So in general, I would say more having an AI collaborator and the use cases for that. You could be a customer service agent and you have an AI chatbot assisting you. And so those are the kinds of use cases in workspace we are beginning to see emerge, but I think the possibilities will keep growing over time.

ADI IGNATIUS: All right. So let’s get specific about Google. So you’ve just announced the release of Gemini, which sounds like a powerful AI tool to compete against OpenAI ChatGPT 4. What will it be capable of and how does it compare with say, Microsoft’s Bing?

SUNDAR PICHAI: Look, we are all building what I call state-of-the-art generative AI models. The model and production which we are using across our products and which we have launched is PaLM 2 and the next state-of-the-art model we are working on with our new combined unit, Google DeepMind is called Gemini. Where these models are progressing is they’re all today you have text models, you have image models and so on, but the next generation of models will be multimodal. They’re both trained on different modalities, text, images, audio, maybe video, and hence can also have outputs spanning all those modalities.

So what does that mean? You go and say, write me an essay about a topic. It’s not only going to give you an essay, but if there are visuals and pictures that need to go with you, they can generate that as well.

So those are examples of it. Or if you want to bake a cake and you go and ask that question, it doesn’t just give you text output, but it also shows you pictures and over time this will keep progressing. So that’s the state of the art and that’s what we are excited about Gemini, the notion of adding multi-modality.

The other progression we are all driving is these models can start using tools. If you think about humans, you’re using tools all the time. You may pull out a calculator, you’re using a word editor. If you want to find out something, you go to Google and find it out. So training these models to natively understand there are tools out there in the world and if they need to help the user with something, they can also call on these tools.

So that’s another thing we are building into these models. So those are examples of how the state-of-the-art is progressing. So I think it’s an exciting time. I think there are few companies which are building what I call frontier models, these AI models which are state-of-the-art, and this is our seventh year as an AI first company. We built a lot of the underlying technology powering these models and so we are deeply committed in a responsible way to continue driving the state-of-the-art here.

ADI IGNATIUS: So I’d like to say that since this became available to the public broadly in November thereabouts, that we’ve sort of gone through three stages. The first stage we all just played around with it, write me a version of Ulysses in HBR style or something and then we tried to break it. Do you love me ChatGPT, but now there’s this sort of application thing. But I’d love to ask, did you have a moment where you played around with this and you were surprised and amazed and wowed by what you got back?

SUNDAR PICHAI: No, we have had, so internally we had built what was called Lambda. Internally we had built a conversational dialogue based on these large language models. And I remember speaking to it, we gave it various personas. So for example, you could ask it to behave like planet Pluto and you could have these long conversations with it and it’s a wonderful learning tool. In fact, I had my son and both of us spent some time talking to it and you can learn about the solar system and you can keep asking it questions, but there was a moment talking to Pluto at some point I felt like it felt very, very lonely and the conversation slightly went to a darker place and that was my first experience, which kind of unsettled me and showed the power of what’s possible, the effect it can have on humans.

By the way, it makes sense because you can imagine the model trying to think about Pluto. Pluto is in a cold far away place in the universe. So no wonder that it kind of started taking some of those attributes in its personality. But that was my first experience and since then I had a few other experiences. So these are powerful models and I think a lot of us are working on making sure we build in safety systems, we add a layer of responsibility before we really widely deploy it. It’s part of the reason I think as Google, we’ve been more conservative in our approach given the scale at which we serve users. But yeah, I’ve definitely had those experiences.

ADI IGNATIUS: It does seem like Google has been more conservative than some others who have rushed generative AI bots, whatever is the right term out there, but it’s still pretty fast. I mean this has all happened in sort of days and months. And can you talk a little bit more, I mean, how do you balance the need to be in the market, the product is out there and you need a product. How do you balance the need to be there, the need to innovate with the kind of caution that you were just mentioning?

SUNDAR PICHAI: I think it’s a great question and we know there is inherent trade-offs and tension here and we frame it internally that way and we want to be innovative. There is amazing opportunities to be unlocked and so we want to take a bold approach to drive innovation, but we want to make sure we get it right. And so we want to be responsible in our approach. And so we think about our approach as being bold and responsible and understanding that framework and approaching it that way.

And so we are not focused on always being first. We are going to be focused on getting it right, but working at it with a sense of excitement and urgency to make progress, but slowing down when needed to make sure you get the additional safeguards in, you give early access to other people outside so that they can test it, give feedback to us and so on.

So I think all that is going to be important and I think it’s something you have to build into the organization to embrace those trade-offs and work at it, work at both the same time. And we just recently had our largest developer conference and we spoke about all our AI product work we are doing. We are thinking about making AI helpful for everyone across our products. And so we have incorporated generative AI in over 25 of our products, be it Gmail or Google Docs or search or YouTube and so on. And again, so we want to be bold and responsible at the same time.

ADI IGNATIUS: So when you say putting in safeguards, talk about that a little bit. What would safeguards mean in this case?

SUNDAR PICHAI: Let me give a few examples. One is what we call adversarial testing. So we ourselves try to break it. Right. So we have our safety and security teams, we have red teams whose explicit goal is to break these models in various possible ways. So making sure after development you give these teams time to stress test these models and then drive a iterative cycle where you make the models much better. That’s one example.

Another example is we are still in the process of doing this work, but we are doing work to add watermarking and metadata. So think about AI generated images. I think it’s going to be a responsible way to do it is to help people understand that these images were generated by generative AI.

And so adding watermarking so that other systems can detect that these images were generated using AI and having associated metadata so that if you want to know when this image was created, who created it, et cetera, you can get that information. So now we are doing the underlying technology and the research work to make sure those capabilities exist as we deploy these more widely. So those are all examples of the kind of work you can do with the lens of safety and responsibility.

ADI IGNATIUS: So you used the term inflection point earlier in our conversation, we’ve all seen technologies come awry and it feels like the next big thing, some are, some aren’t. This feels different, this feels truly transformative. Is that how you see generative AI? And project a little bit of the longer term future then how does this technology remake what we do?

SUNDAR PICHAI: AI is a deep platform shift. Many years ago I called AI the most profound technology humanity is working on and will ever work on, more profound than fire or electricity. And that was the reason we said our company is going to be AI first. So I do think it’s a deep platform shift.

It will touch every aspect of our lives, every aspect of society, every industry sector if you will. But it is important to understand while we are talking about AI broadly, generative AI is a moment in time and it’s one aspect of AI. It’s just that these large language models are now useful enough to use them in a variety of scenarios. But I think there is more progress to be had and I do think we’ll go through some moments of ups and downs, but the progress I think will continue. But generative AI is just one facet of the broader progress we are making with AI overall.

But I do think it’s important to prepare for it. I think we should channel all this excitement to make sure other stakeholders are getting involved. I think this is an area for sure where governments will have a role to play nonprofits, academic institutions, international countries needing to come together and developing frameworks by which they can align for safety and responsibility. So all those systems need to adapt and that’s going to take time. So we need to embrace the excitement and channel it in a way in which as society, as humanity, we are building the foundational blocks to tackle what’s coming our way as well.

ADI IGNATIUS: So there’s talk in the air of regulation. Would you welcome regulation in this sphere and what’s the kind of regulation that we would need where companies like yours could still innovate but as you say, we would ensure safety and other things?

SUNDAR PICHAI: The way I think about it is it’s too important an area not to regulate and also too important an area not to regulate well. You know, you have to get the balance right. When a technology in its early stages and developing, you have to allow for innovation to proceed but at the same time building in the capabilities and effectively the safeguards that you would need.

So I think regulation will play a strong role. I think to me, at least speaking from a U.S. standpoint, I think the most important regulation which we can pass, which will also help AI is a stronger privacy foundation. So privacy regulation and framework, which we still lack. A national privacy bill, I think would be a foundational approach I think because AI can build upon that. I think there are many sectors today which are already regulated and AI can naturally fit within the framework.

If you’re in healthcare and you’re deploying systems today, you go through a lot of regulation to get that done. And so I think AI can fit in that framework to start with. The main areas I would think about it is what is a framework by which governments or regulators can validate the models that are being developed and make sure they are safe for public use.

And I think you can have a progression in terms of how onerous you make them, but I think initially it’s both building the capabilities amongst governments and so thinking through the right agencies, the right regulatory bodies who can have oversight. And over time both imposing requirements and you have to be careful because you can’t make the regulations onerous, that means the big companies can do it, but use stifle innovation from startups or from the open source community.

So it’s going to be difficult to get this right. So I would focus in more initially on building the capabilities in terms of developing the actual talent and abilities to interact, form the right public-private partnerships and over time codified into better laws. But I think it’s got to be a multi-stakeholder process to get there.

ADI IGNATIUS: We solicited some questions from our subscribers beforehand. So I want to ask one of them, this is from Afaf who’s in North Carolina in the U.S. and the question is how should companies think about training and adapting their non-technology workforce to support a generative AI journey, strategy?

SUNDAR PICHAI: I think it’s a great question. I think in every organization I think it’s important to unlock use cases and deploy it in the context of your workflows. I think one of the interesting things we have learned about these models is we call this fine-tuning. You can take these base models and in the context of your organization, fine tune it based on the data of the organization and they can really start working well for the context you have. So I would think about deploying it in the context of these organizations.

It could be as simple as we are building this into products, like into our productivity tools, be it Google Docs or Google Slides or Google Sheets and others are doing the same. And so you can imagine getting your workforce used to this notion of working collaboratively with AI assisting you. And I think that mindset change is going to be important for organizations to go through, for workforces to adapt.

And so I think that’s where I would start. But I think it’s important in any organization from the senior most levels, you’re thinking about what are areas which you can transform by deploying generative AI. To me, I was excited.

I mean, last week we announced this, but Wendy’s has used generative AI so that people can use voice as part of that drive-through order and the system works that way, but they’ve learned, people speak in thousands of different ways. And so to use the AI system to make that process more efficient, I think that’s an example of an organization applying generative AI in a way that delights their customers, their workforce is becoming more familiar with it. And so I think the sky is the limit in terms of how you can imagine to use these things, but I would get the journey started.

ADI IGNATIUS: Well, so a little bit more on that. So if somebody’s watching this and they’re like, okay, this sounds pretty cool, I don’t really know how to apply it in my company, I’m not sure if there is an application in my company, how do you get started? How do you get comfortable with the technology and figure out its potential?

SUNDAR PICHAI: Today many of these companies are using a cloud provider. Right. And so I think it’s a good conversation to start with your cloud provider, hopefully it’s Google, to talk about. We all have generative AI tools and solutions which we can apply in the context of your workspace. And so that’s where I would ask the question and I would get pilot programs started. I think people tend to overthink the initial approach. I think literally this is about seeding your organization with four to five pilot ideas, challenging your organization from the top down on saying where all can you apply generative AI seeking ideas and then getting a few pilot proposals underway. And I think that gets the organization thinking about it. It’s almost like a new muscle memory you need to develop. So there is a cultural transformation to go with it. And so to me it’s about challenging your teams, your leaders, and getting a few pilot ideas underway.

ADI IGNATIUS: So let’s shift gears a little bit. The tech sector and including Google has taken some hits in recent months. There have been layoffs, spending cuts, what happens in a cycle like this. What’s your expectation for the severity of this downturn and how are you trying to weather the storm and emerge from it stronger rather than weaker?

SUNDAR PICHAI: Yeah. We have taken so many macro shocks as an economy and as a global system from the pandemic to the war in Ukraine and to rising interest rates and so on. So there’s a lot of macro shocks and so at this point I think the right thing and I think what most organizations need to assume is that these tough conditions are here and you have to constantly work on making sure your organization is adapting.

From a Google standpoint, I’ve approached it with two main ways of thinking about it. First is it’s important to stay the course in terms of driving innovation for the longer term. And I think that’s what over time will separate the pack from the companies which will get this moment right. Particularly for us sensing this moment, the point of inflection with AI, we are focused on investing in R&D, driving that long-term innovation that is needed with AI. And if anything, doing more of it through a moment like this, I think this is extraordinarily important. So that’s an aspect of weathering this moment.

The second part of it is to do the first part well, you have to make trade-offs and so really going to first principles, having clarity about what are the things of all the things you’re doing that really make a difference for the long term. And hence sharpening your focus as a company, driving efficiencies and making the tough decisions needed and doing that on a sustained ongoing way is what will allow you to build for the long term well, and so it’s doing both, which is not always easy.

I think you’re always pulled towards doing more of the ladder, but I think it’s important to get both right and at least at a Google standpoint focused hard on making sure we are investing both for the long term and doing that well at the same time using this moment. It’s a moment of clarity and having all these constraints actually drives clarity. And so you dig deep and find what really matters and then you focus organization more on those efforts.

ADI IGNATIUS: So you’re the CEO of one of the most recognizable brands in the world and your CEO at a time where the rules have kind of changed, that the rise of social media and the expectations are that CEOs do more than run companies effectively, that they need to have a public presence and take stands on certain issues and address their own workforces sometimes publicly if they’re not happy with something and it’s very complicated. How do you think about this evolving role and what is the role of a CEO in 2023?

SUNDAR PICHAI: It’s a good question. It’s something I think in a Google context it’s meant a lot as well. I do think the world has evolved to a place where as a CEO today you have a lot of stakeholders and it’s not just your shareholders or your customers, it’s your employees. It’s the communities in which the company operates in. So it’s important to keep that in mind.

I think the way I’ve approached this is I think you have to be clear about the few issues that really matter to the company and it could matter to the company because it matters a lot to your employees or it matters to the company because you want to be a good citizen in the communities you work in, et cetera. But having clarity around the few issues, so the few values you stand for and being consistent about it, I think it’s more important.

And I think where you tend to drift is by spreading yourself too thin, if you will. So what I’ve tried to do is being clear about the values we care about as a company and be it sustainability or building a diverse workforce and making sure we stay committed to it, but committed to it in the context of the work we do, work we do. And the fact that it would drive a better company in that process.

So I think that’s where maybe you want to have a framework with which you’re working on, but I do think it’s important to keep all stakeholders in mind as you’re running a company and doing it with empathy I think is more important than ever.

ADI IGNATIUS: So when I think back to the days when Google was founded, I feel like its ambitions were relatively limited and relatively clear. Now the company is much bigger. There’s much more going on. How do you think about, what is your big ambition, I guess, for the company now?

SUNDAR PICHAI: I mean we set out our big ambition many years ago when we said we have felt fortunate that our mission feels timeless. Having a mission to organize the world’s information and making it universally accessible and useful and if anything, or with time passing, it just felt more relevant than before.

So we feel fortunate with that, but what’s excited us is that AI allows us to pursue the most ambitious version of that mission. And so we think about it as how do we make AI helpful for everyone and we are focused on four main areas. First is to improve knowledge and learning. Second is boosting creativity and productivity. Third, which has been important to us, it’s not just for us. We want to enable others, other organizations be it companies, be it nonprofits, be it governments to use AI to make their organizations better. And finally, and arguably the most important of it all is to do it safely and responsibly. So that’s our ambition and doing it in a way that it benefits everyone is what I’m really focused on with the company and we couldn’t be more excited about it.

ADI IGNATIUS: So building on that, I want to bring in one more question that we solicited from our subscribers. This is from Antonio in Portugal. Question is, we’ve seen Google experiment with various moonshot projects. So Sundar, if you had the chance to pursue an entirely outlandish or whimsical project, what would it be and why?

SUNDAR PICHAI: We are working on quite a few. We are trying to solve quantum computing, which is as moonshot-y as it gets, or we have other efforts underway. Maybe I would say two things. One, I think if we could do more, and we are doing it today by supporting other companies so we don’t need to necessarily do it ourselves, is to work hard to enable a technology like nuclear fusion to happen. I think providing abundant, clean, renewable energy at an affordable price point is as game changing as anything I can think about. And so that’s an example of a moonshot, would love to be able to do.

The other thing I would say is my life got transformed by getting access to computers and technology and gaining the power of products like Google in my hands. I think with AI we have the chance, a moonshot is, I think over time we can give every child in the world and every person in the world regardless of where they are and where they come from, and access to the most powerful AI tutor, which can teach them anything they want on any topic. And obviously it needs to work in conjunction with their teachers and parents and so on. But I think a promise of something like that is real and that’s an example of a moonshot I’d get super excited about.

ADI IGNATIUS: That’s a good moonshot. Well Sundar, I think we’re out of time, but I want to thank you for being with us and for sharing your views, particularly this moment where generative AI is suddenly what we’re all trying to figure out. And as I said before, you’re really on the front line. So thank you very much for being with us.

SUNDAR PICHAI: Thanks Adi, it’s been a real pleasure. Appreciate it.

ADI IGNATIUS: That’s Sundar Pichai, the CEO of Google, who was speaking with me at HBR Live: Leaders Who Make a Difference.

And we have more episodes and more podcasts to help you manage your team, your organization, and your career. Find them at HBR dot org slash podcasts or search HBR in Apple Podcasts, Spotify, or wherever you listen.

This episode was produced by Mary Dooe. We get technical help from Rob Eckhardt. Our audio product manager is Ian Fox, and Hannah Bates is our audio production assistant. Thanks for listening to the HBR IdeaCast . We’ll be back with a new episode on Tuesday. I’m Adi Ignatius.

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Chapter 21 - Organizational Change Management in SRE

• Table of Contents
• Foreword II
• 1. How SRE Relates to DevOps
• Part I - Foundations
• 2. Implementing SLOs
• 3. SLO Engineering Case Studies
• 4. Monitoring
• 5. Alerting on SLOs
• 6. Eliminating Toil
• 7. Simplicity
• Part II - Practices
• 9. Incident Response
• 10. Postmortem Culture: Learning from Failure
• 11. Managing Load
• 12. Introducing Non-Abstract Large System Design
• 13. Data Processing Pipelines
• 14. Configuration Design and Best Practices
• 15. Configuration Specifics
• 16. Canarying Releases
• Part III - Processes
• 17. Identifying and Recovering from Overload
• 18. SRE Engagement Model
• 19. SRE: Reaching Beyond Your Walls
• 20. SRE Team Lifecycles
• 21. Organizational Change Management in SRE
• Appendix A. Example SLO Document
• Appendix B. Example Error Budget Policy
• Appendix C. Results of Postmortem Analysis
• About the Editors

Organizational Change Management in SRE

By Alex Bramley, Ben Lutch, Michelle Duffy, and Nir Tarcic with Betsy Beyer

In the introduction to the first SRE Book , Ben Treynor Sloss describes SRE teams as “characterized by both rapid innovation and a large acceptance of change,” and specifies organizational change management as a core responsibility of an SRE team. This chapter examines how theory can apply in practice across SRE teams. After reviewing some key change management theories, we explore two case studies that demonstrate how different styles of change management have played out in concrete ways at Google.

Note that the term change management has two interpretations: organizational change management and change control. This chapter examines change management as a collective term for all approaches to preparing and supporting individuals, teams, and business units in making organizational change. We do not discuss this term within a project management context, where it may be used to refer to change control processes, such as change review or versioning.

SRE Embraces Change

More than 2,000 years ago, the Greek philosopher Heraclitus claimed change is the only constant. This axiom still holds true today—especially in regards to technology, and particularly in rapidly evolving internet and cloud sectors.

Product teams exist to build products, ship features, and delight customers. At Google, most change is fast-paced, following a “launch and iterate” approach. Executing on such change typically requires coordination across systems, products, and globally distributed teams. Site Reliability Engineers are frequently in the middle of this complicated and rapidly shifting landscape, responsible for balancing the risks inherent in change with product reliability and availability. Error budgets (see Implementing SLOs ) are a primary mechanism for achieving this balance.

Introduction to Change Management

Change management as an area of study and practice has grown since foundational work in the field by Kurt Lewin in the 1940s. Theories primarily focus on developing frameworks for managing organizational change. In-depth analysis of particular theories is beyond the scope of this book, but to contextualize them within the realm of SRE, we briefly describe some common theories and how each might be applicable in an SRE-type organization. While the formal processes implicit in these theoretical frameworks have not been applied by SRE at Google, considering SRE activities through the lens of these frameworks has helped us refine our approach to managing change. Following this discussion, we will introduce some case studies that demonstrate how elements of some of these theories apply to change management activities led by Google SRE.

Lewin’s Three-Stage Model

Kurt Lewin’s “unfreeze–change–freeze” model for managing change is the oldest of the relevant theories in this field. This simple three-stage model is a tool for managing process review and the resulting changes in group dynamics. Stage 1 entails persuading a group that change is necessary. Once they are amenable to the idea of change, Stage 2 executes that change. Finally, when the change is broadly complete, Stage 3 institutionalizes the new patterns of behavior and thought. The model’s core principle posits the group as the primary dynamic instrument, arguing that individual and group interactions should be examined as a system when the group is planning, executing, and completing any period of change. Accordingly, Lewin's work is most useful for planning organizational change at the macro level.

McKinsey’s 7-S Model

McKinsey’s seven S’s stand for structure, strategy, systems, skills, style, staff, and shared values. Similar to Lewin’s work, this framework is also a toolset for planned organizational change. While Lewin’s framework is generic, 7-S has an explicit goal of improving organizational effectiveness. Application of both theories begins with an analysis of current purpose and processes. However, 7-S also explicitly covers both business elements (structure, strategy, systems) and people-management elements (shared values, skills, style, staff). This model could be useful for a team considering change from a traditional systems administration focus to the more holistic Site Reliability Engineering approach.

Kotter’s Eight-Step Process for Leading Change

Time magazine named John P. Kotter’s 1996 book Leading Change (Harvard Business School Press) one of the Top 25 Most Influential Business Management Books of all time . Figure 21-1 depicts the eight steps in Kotter’s change management process.

Kotter’s process is particularly relevant to SRE teams and organizations, with one small exception: in many cases (e.g., the upcoming Waze case study), there’s no need to create a sense of urgency. SRE teams supporting products and systems with accelerating growth are frequently faced with urgent scaling, reliability, and operational challenges. The component systems are often owned by multiple development teams, which may span several organizational units; scaling issues may also require coordination with teams ranging from physical infrastructure to product management. Because SRE is often on the front line when problems occur, it is uniquely motivated to lead the change needed to ensure products are available 24/7/365. Much of SRE work (implicitly) embraces Kotter’s process to ensure the continued availability of supported products.

The Prosci ADKAR Model

The Prosci ADKAR model focuses on balancing both the business and people aspects of change management. ADKAR is an acronym for the goals individuals must achieve for successful organizational change: awareness, desire, knowledge, ability, and reinforcement.

In principle, ADKAR provides a useful, thoughtful, people-centric framework. However, its applicability to SRE is limited because operational responsibilities quite often impose considerable time constraints. Proceeding iteratively through ADKAR’s stages and providing the necessary training or coaching requires pacing and investment in communication, which are difficult to implement in the context of globally distributed, operationally focused teams. That said, Google has successfully used ADKAR-style processes for introducing and building support for high-level changes—for example, introducing global organizational change to the SRE management team while preserving local autonomy for implementation details.

Emotion-Based Models

The Bridges Transition Model describes people’s emotional reactions to change. While a useful management tool for people managers, it’s not a framework or process for change management. Similarly, the Kübler-Ross Change Curve describes ranges of emotions people may feel when faced with change. Developed from Elisabeth Kübler-Ross’s research on death and dying, 1 it has been applied to understanding and anticipating employee reactions to organizational change. Both models can be useful in maintaining high employee productivity throughout periods of change, since unhappy people are rarely productive.

The Deming Cycle

Also known as the Plan-Do-Check-Act (or PDCA) Cycle, this process from statistician Edward W. Deming is commonly used in DevOps environments for process improvements—for example, adoption of continuous integration/continuous delivery techniques. It is not suited to organizational change management because it does not cover the human side of change, including motivations and leadership styles. Deming’s focus is to take existing processes (mechanical, automated, or workflow) and cyclically apply continuous improvements. The case studies we refer to in this chapter deal with larger, organizational changes where iteration is counterproductive: frequent, wrenching org-chart changes can sap employee confidence and negatively impact company culture.

How These Theories Apply to SRE

No change management model is universally applicable to every situation, so it’s not surprising that Google SRE hasn’t exclusively standardized on one model. That said, here’s how we like to think about applying these models to common change management scenarios in SRE:

• Kotter’s Eight-Step Process is a change management model for SRE teams who necessarily embrace change as a core responsibility.
• The Prosci ADKAR model is a framework that SRE management may want to consider to coordinate change across globally distributed teams.
• All individual SRE managers will benefit from familiarity with both the Bridges Transition Model and the Kübler-Ross Change Curve , which provide tools to support employees in times of organizational change.

Now that we’ve introduced the theories, let’s look at two case studies that show how change management has played out at Google.

Case Study 1: Scaling Waze—From Ad Hoc to Planned Change

Waze is a community-based navigation app acquired by Google in 2013. After the acquisition, Waze entered a period of significant growth in active users, engineering staff, and computing infrastructure, but continued to operate relatively autonomously within Google. The growth introduced many challenges, both technical and organizational.

Waze’s autonomy and startup ethos led them to meet these challenges with a grassroots technical response from small groups of engineers, rather than management-led, structured organizational change as implied by the formal models discussed in the previous section. Nevertheless, their approach to propagating changes throughout the organization and infrastructure significantly resembles Kotter’s model of change management. This case study examines how Kotter’s process (which we apply retroactively) aptly describes a sequence of technical and organizational challenges Waze faced as they grew post-acquisition.

The Messaging Queue: Replacing a System While Maintaining Reliability

Kotter’s model begins the cycle of change with a sense of urgency . Waze’s SRE team needed to act quickly and decisively when the reliability of Waze’s message queueing system regressed badly, leading to increasingly frequent and severe outages. As shown in Figure 21-2 , the message queueing system was critical to operations because every component of Waze (real time, geocoding, routing, etc.) used it to communicate with other components internally.

As throughput on the message queue grew significantly, the system simply couldn’t cope with the ever-increasing demands. SREs needed to manually intervene to preserve system stability at shorter and shorter intervals. At its worst, the entire Waze SRE team spent most of a two-week period firefighting 24/7, eventually resorting to restarting some components of the message queue hourly to keep messages flowing and tens of millions of users happy.

Because SRE was also responsible for building and releasing all of Waze’s software, this operational load had a noticeable impact on feature velocity—when SREs spent all of their time fighting fires, they hardly had time to support new feature rollouts. By highlighting the severity of the situation, engineers convinced Waze’s leadership to reevaluate priorities and dedicate some engineering time to reliability work. A guiding coalition of two SREs and a senior engineer came together to form a strategic vision of a future where SRE toil was no longer necessary to keep messages flowing. This small team evaluated off-the-shelf message queue products, but quickly decided that they could only meet Waze’s scaling and reliability requirements with a custom-built solution.

Developing this message queue in-house would be impossible without some way to maintain operations in the meantime. The coalition removed this barrier to action by enlisting a volunteer army of developers from the teams who used the current messaging queue. Each team reviewed the codebase for their service to identify ways to cut the volume of messages they published. Trimming unnecessary messages and rolling out a compression layer on top of the old queue reduced some load on the system. The team also gained some more operational breathing room by building a dedicated messaging queue for one particular component that was responsible for over 30% of system traffic. These measures yielded enough of a temporary operational reprieve to allow for a two-month window to assemble and test a prototype of the new messaging system.

Migrating a message queue system that handles tens of thousands of messages per second is a daunting task even without the pressure of imminent service meltdown. But gradually reducing the load on the old system would relieve some of this pressure, affording the team a longer time window to complete the migration. To this end, Waze SRE rebuilt the client libraries for the message queue so they could publish and receive messages using either or both systems, using a centralized control surface to switch the traffic over.

Once the new system was proven to work, SRE began the first phase of the migration: they identified some low-traffic, high-importance message flows for which messaging outages were catastrophic. For these flows, writing to both messaging systems would provide a backup path. A couple of near misses, where the backup path kept core Waze services operating while the old system faltered, provided the short-term wins that justified the initial investment.

Mass migration to the new system required SRE to work closely with the teams who use it. The team needed to figure out both how to best support their use cases and how to coordinate the traffic switch. As the SRE team automated the process of migrating traffic and the new system supported more use cases by default, the rate of migrations accelerated significantly .

Kotter’s change management process ends with instituting change . Eventually, with enough momentum behind the adoption of the new system, the SRE team could declare the old system deprecated and no longer supported. They migrated the last stragglers a few quarters later. Today, the new system handles more than 1000 times the load of the previous one, and requires little manual intervention from SREs for ongoing support and maintenance.

The Next Cycle of Change: Improving the Deployment Process

The process of change as a cycle was one of Kotter’s key insights. The cyclical nature of meaningful change is particularly apparent when it comes to the types of technical changes that face SRE. Eliminating one bottleneck in a system often highlights another one. As each change cycle is completed, the resulting improvements, standardization, and automation free up engineering time. Engineering teams now have the space to more closely examine their systems and identify more pain points, triggering the next cycle of change.

When Waze SRE could finally take a step back from firefighting problems related to the messaging system, a new bottleneck emerged, bringing with it a renewed sense of urgency : SRE’s sole ownership of releases was noticeably and seriously hindering development velocity. The manual nature of releases required a significant amount of SRE time. To exacerbate an already suboptimal situation, system components were large, and because releases were costly, they were relatively infrequent. As a result, each release represented a large delta, significantly increasing the possibility that a major defect would necessitate a rollback.

Improvements toward a better release process happened incrementally, as Waze SRE didn’t have a master plan from square one. To slim down system components so the team could iterate each more rapidly, one of the senior Waze developers created a framework for building microservices. This provided a standard “batteries included” platform that made it easy for the engineering organization to start breaking their components apart. SRE worked with this developer to include some reliability-focused features—for example, a common control surface and a set of behaviors that were amenable to automation. As a result, SRE could develop a suite of tools to manage the previously costly parts of the release process. One of these tools incentivized adoption by bundling all of the steps needed to create a new microservice with the framework.

These tools were quick-and-dirty at first—the initial prototypes were built by one SRE over the course of several days. As the team cleaved more microservices from their parent components, the value of the SRE-developed tools quickly became apparent to the wider organization. SRE was spending less time shepherding the slimmed-down components into production, and the new microservices were much less costly to release individually.

While the release process was already much improved, the proliferation of new microservices meant that SRE’s overall burden was still concerning. Engineering leadership was unwilling to assume responsibility for the release process until releases were less burdensome.

In response, a small coalition of SREs and developers sketched out a strategic vision to shift to a continuous deployment strategy using Spinnaker , an open source, multicloud, continuous delivery platform for building and executing deployment workflows. With the time saved by our bootstrap tooling, the team now was able to engineer this new system to enable one-click builds and deployments of hundreds or thousands of microservices. The new system was technically superior to the previous system in every way, but SRE still couldn’t persuade development teams to make the switch. This reluctance was driven by two factors: the obvious disincentive of having to push their own releases to production, plus change aversion driven by poor visibility into the release process.

Waze SRE tore down these barriers to adoption by showing how the new process added value. The team built a centralized dashboard that displayed the release status of binaries and a number of standard metrics exported by the microservice framework. Development teams could easily link their releases to changes in those metrics, which gave them confidence that deployments were successful. SRE worked closely with a few volunteer systems-oriented development teams to move services to Spinnaker. These wins proved that the new system could not only fulfill its requirements, but also add value beyond the original release process. At this point, engineering leadership set a goal for all teams to perform releases using the new Spinnaker deployment pipelines.

To facilitate the migration, Waze SRE provided organization-wide Spinnaker training sessions and consulting sessions for teams with complex requirements. When early adopters became familiar with the new system, their positive experiences sparked a chain reaction of accelerating adoption . They found the new process faster and less painful than waiting for SRE to push their releases. Now, engineers began to put pressure on dependencies that had not moved, as they were the impediment to faster development velocity—not the SRE team!

Today, more than 95% of Waze’s services use Spinnaker for continuous deployment, and changes can be pushed to production with very little human involvement. While Spinnaker isn’t a one-size-fits-all solution, configuring a release pipeline is trivial if a new service is built using the microservices framework, so new services have a strong incentive to standardize on this solution.

Lessons Learned

Waze’s experience in removing bottlenecks to technical change contains a number of useful lessons for other teams attempting engineering-led technical or organizational change. To begin with, change management theory is not a waste of time! Viewing this development and migration process through the lens of Kotter’s process demonstrates the model’s applicability. A more formal application of Kotter’s model at the time could have helped streamline and guide the process of change.

Change instigated from the grass roots requires close collaboration between SRE and development, as well as support from executive leadership. Creating a small, focused group with members from all parts of the organization—SRE, developers, and management—was key to the team’s success. A similar collaboration was vital to instituting the change. Over time, these ad hoc groups can and should evolve into more formal and structured cooperation, where SREs are automatically involved in design discussions and can advise on best practices for building and deploying robust applications in a production environment throughout the entire product lifecycle.

Incremental change is much easier to manage. Jumping straight to the “perfect” solution is too large a step to take all at once (not to mention probably infeasible if your system is about to collapse), and the concept of “perfect” will likely evolve as new information comes to light during the change process. An iterative approach can demonstrate early wins that help an organization buy into the vision of change and justify further investment. On the other hand, if early iterations don’t demonstrate value, you’ll waste less time and fewer resources when you inevitably abandon the change. Because incremental change doesn’t happen all at once, having a master plan is invaluable. Describe the goals in broad terms, be flexible, and ensure that each iteration moves toward them.

Finally, sometimes your current solutions can’t support the requirements of your strategic vision. Building something new has a large engineering cost, but can be worthwhile if the project pushes you out of a local maxima and enables long-term growth. As a thought experiment, figure out where bottlenecks might arise in your systems and tooling as your business and organization grow over the next few years. If you suspect any elements don’t scale horizontally, or have superlinear (or worse, exponential) growth with respect to a core business metric such as daily active users, you may need to consider redesigning or replacing them.

Waze’s development of a new in-house message queue system shows that it is possible for small groups of determined engineers to institute change that moves the needle toward greater service reliability. Mapping Kotter’s model onto the change shows that some consideration of change management strategy can help provide a formula for success even in small, engineering-led organizations. And, as the next case study also demonstrates, when changes promote standardizing technology and processes, the organization as a whole can reap considerable efficiency gains.

Case Study 2: Common Tooling Adoption in SRE

SREs are opinionated about the software they can and should use to manage production. Years of experience, observing what goes well and what doesn’t, and examining the past through the lens of the postmortem, have given SREs a deep background coupled with strong instincts. Specifying, building, and implementing software to automate this year’s job away is a core value in SRE. In particular, Google SRE recently focused our efforts on horizontal software. Adoption of the same solution by a critical mass of users and developers creates a virtuous cycle and reduces reinvention of wheels. Teams who otherwise might not interact share practices and policies that are automated using the same software.

This case study is based on an organizational evolution, not a response to a systems scaling or reliability issue (as discussed in the Waze case study). Hence, the Prosci ADKAR model (shown in Figure 21-3 ) is a better fit than Kotter’s model, as it recognizes both explicit organizational/people management characteristics and technical considerations during the change.

Problem Statement

A few years ago, Google SRE found itself using multiple independent software solutions for approximately the same problem across multiple problem spaces: monitoring, releases and rollouts, incident response, capacity management, and so on.

This end state arose in part because the people building tools for SRE were dissociated from their users and their requirements. The tool developers didn’t always have a current view of the problem statement or the overall production landscape—the production environment changes very rapidly and in new ways as new software, hardware, and use cases are brought to life almost daily. Additionally, the consumers of tools were varied, sometimes with orthogonal needs (“this rollout has to be fast; approximate is fine” versus “this rollout has to be 100% correct; okay for it to go slowly”).

As a result, none of these long-term projects fully addressed anyone’s needs, and each was characterized by varying levels of development effort, feature completeness, and ongoing support. Those waiting for the big use case—a nonspecific, singing-and-dancing solution of the future—waited a long time, got frustrated, and used their own software engineering skills to create their own niche solution. Those who had smaller, specific needs were loath to adopt a broader solution that wasn’t as tailored to them. The long-term, technical, and organizational benefits of more universal solutions were clear, but customers, services, and teams were not staffed or rewarded for waiting. To compound this scenario, requirements of both large and small customer teams changed over time.

What We Decided to Do

To scope this scenario as one concrete problem space, we asked ourselves: What if all Google SREs could use a common monitoring engine and set of dashboards, which were easy to use and supported a wide variety of use cases without requiring customization?

Likewise, we could extend this model of thinking to releases and rollouts, incident response, capacity management, and beyond. If the initial configuration of a product captured a wide representation of approaches to address the majority of our functional needs, our general and well-informed solutions would become inevitable over time. At some point, the critical mass of engineers who interact with production would outgrow whatever solution they were using and self-select to migrate to a common, well-supported set of tools and automation, abandoning their custom-built tools and their associated maintenance costs.

SRE at Google is fortunate that many of its engineers have software engineering backgrounds and experience. It seemed like a natural first step to encourage engineers who were experts and opinionated about specific problems—from load balancing to rollout tooling to incident management and response—to work as a virtual team, self-selected by a common long-term vision. These engineers would translate their vision into working, real software that would eventually be adopted across all of SRE, and then all of Google, as the basic functions of production.

To return to the ADKAR model for change management, the steps discussed so far—identifying a problem and acknowledging an opportunity—are textbook examples of ADKAR’s initiating awareness step. The Google SRE leadership team agreed on the need ( desire ) and had sufficient knowledge and ability to move to designing solutions fairly quickly.

Our first task was to converge upon a number of topics that we agreed were central, and that would benefit greatly from a consistent vision: to deliver solutions and adoption plans that fit most use cases. Starting from a list of 65+ proposed projects, we spent multiple months collecting customer requirements, verifying roadmaps, and performing market analysis, ultimately scoping our efforts toward a handful of vetted topics.

Our initial design created a virtual team of SRE experts around these topics. This virtual team would contribute a significant percentage of their time, around 80%, to these horizontal projects. The idea behind 80% time and a virtual team was to ensure we did not design or build solutions without constant contact with production. However, we (maybe predictably) discovered a few pain points with this approach:

• Coordinating a virtual team—whose focus was broken by being on-call regularly, across multiple time zones—was very difficult. There was a lot of state to be swapped between running a service and building a serious piece of software.
• Everything from gathering consensus to code reviews was affected by the lack of a central location and common time.
• Headcount for horizontal projects initially had to come from existing teams, who now had fewer engineering resources to tackle their own projects. Even at Google, there’s tension between delegating headcount to support the system as is versus delegating headcount to build future-looking infrastructure.

With enough data in hand, we realized we needed to redesign our approach, and settled on the more familiar centralized model. Most significantly, we removed the requirement that team members split their time 80/20 between project work and on-call duties. Most SRE software development is now done by small groups of senior engineers with plenty of on-call experience, but who are heads-down focused on building software based on those experiences. We also physically centralized many of these teams by recruiting or moving engineers. Small group (6–10 people) development is simply more efficient within one room (however, this argument doesn’t apply to all groups—for example, remote SRE teams). We can still meet our goal of collecting requirements and perspectives across the entire Google engineering organization via videoconference, email, and good old-fashioned travel.

So our evolution of design actually ended up in a familiar place—small, agile, mostly local, fast-moving teams—but with the added emphasis on selecting and building automation and tools for adoption by 60% of Google engineers (the figure we decided was a reasonable interpretation of the goal of “ almost everyone at Google”). Success means most of Google is using what SRE has built to manage their production environment.

The ADKAR model maps the implementation phase of the change project between the people-centric stages of knowledge and ability . This case study bears out that mapping. We had many engaged, talented, and knowledgeable engineers, but we were asking people who had been focused on SRE concerns to act like product software development engineers by focusing on customer requirements, product roadmaps, and delivery commitments. We needed to revisit the implementation of this change to enable engineers to demonstrate their abilities with respect to these new attributes.

Implementation: Monitoring

To return to the monitoring space mentioned in the previous section, Chapter 31 in the first SRE book described how Viceroy—Google SRE’s effort to create a single monitoring dashboard solution suitable for everyone—addressed the problem of disparate custom solutions. Several SRE teams worked together to create and run the initial iteration, and as Viceroy grew to become the de facto monitoring and dashboarding solution at Google, a dedicated centralized SRE development team assumed ownership of the project.

But even when the Viceroy framework united SRE under a common framework, there was a lot of duplicated effort as teams built complex custom dashboards specific to their services. While Viceroy provided a standard hosted method to design and build visual displays of data, it still required each team to decide what data to display and how to organize it.

The now-centralized software development team began a second parallel effort to provide common dashboards, building an opinionated zero-config system on top of the lower-level “custom” system. This zero-config system provided a standard set of comprehensive monitoring displays based on the assumption that a given service was organized in one of a handful of popular styles. Over time, most services migrated to using these standard dashboards instead of investing in custom layouts. Very large, unique, or otherwise special services can still deploy custom views in the hosted system if they need to.

Returning to the ADKAR model, the consolidation of monitoring tools at Google began as a grassroots effort, and the resulting improvements in operational efficiencies provided a quantifiable basis ( awareness and desire ) to initiate a broader effort: SRE self-funded a software development team to build production management tooling for all of Google.

Designing a migration of interdependent pieces is often more complicated than a blank-sheet design. But in real life, the hardest engineering work ends up being the evolution of many small/constrained systems into fewer, more general systems—without disturbing already running services that many customers depend on. In the meantime, alongside the existing systems, new small systems are added—some of which eventually surprise us by growing into large systems. There is an intellectual attraction to starting anew with the big design, only backing into constraints that are really necessary, but the migration of systems and teams turns out to be the most difficult work by far .

Designing horizontal software requires a lot of listening to prospective end users, and, in many ways, the tasks of building and adoption look much like the role of a product manager. In order for this effort to achieve success, we had to make sure that we absorbed and prioritized priorities. Meeting customer needs—of both SREs and other production users—was also a critical element of success. It is important to acknowledge that the move toward common tooling is still a work in progress. We iterated on the structure and staffing of the teams building our shared technologies to better enable meeting customer needs, and we added product management and user experience talent (addressing missing knowledge ).

In the past year or two, we have seen uptake of these SRE-designed and -built products across a broad swath of teams at Google. We have learned that to achieve success, the cost of migration (from older, fragmented but specialized solutions) needs to be small relative to the net benefits of the new common solution. Otherwise, the migration itself becomes a barrier to adoption. We continue to work with the individual teams building these products to reinforce the behaviors needed to delight customers with the common solutions the teams are delivering.

One common theme we discovered across horizontal software development projects was that no matter how good new software and products were, the cost of migration—away from something that was already working to something new—was always perceived as very high. Despite the allure of easier management and less specific deep knowledge, the costs of migrating away from the familiar (with all its warts and toil) were generally a barrier. In addition, individual engineers often had a similar internal monologue: “I’m not improving or changing the system; I’m swapping out one working piece for another working piece.” ADKAR describes this resistance as the “knowledge-to-ability gap.” On the human side, in order to recognize and embrace change, people need time, coaching, and training in new tools and skills. On the technical side, implementing change requires understanding adoption costs and including work to minimize these costs as part of the launch process.

As a result, migration costs need to be nearly zero (“just recompile and you pick up new $thing”) and the benefits need to be clear (“now you’re protected from $foo vulnerability”) to the team, to individuals, and to the company.

SRE commonly used to build products that we committed to in a “best effort” way, meaning that the amount of time we gave the product fit into the cracks between everything else we were doing (managing primary services, capacity planning, dealing with outages, etc.). As a result, our execution was not very reliable; it was impossible to predict when a feature or service would be available. By extension, consumers of our products had less trust in the end result since it felt perpetually delayed and was staffed by a rotating cast of product managers and individual engineers. When individual SREs or SRE teams built tools for their own use, the focus was on solving individual problems to reduce the cost of maintaining SLOs for supported systems. In endeavoring to build common tooling for most use cases at Google, we needed to shift the focus to measuring the success of this effort in terms of product adoption.

Owing to both our organizational culture and our wealth of resources, we approached this project in a bottom-up, rather than top-down, fashion. Instead of mandating that users migrated to our new monitoring system, we sought to win over users by demonstrating that our new offering was better than existing solutions.

Over time, we learned that how we conducted our development process would inform how potential internal users perceived the end result. These projects gained real traction only when staffed by production-experienced engineers 100% dedicated to building software, with schedules and support identical to the rest of Google’s software development. Building common software transparently, like clockwork, with great communication (“We’ll have X done by Y date”), greatly improved the speed of migration to the new system. People already trusted the new system because they could observe how it was developed from an early stage. Perceptions of how the sausage is made turned out to be more important than we anticipated from the get-go . Our initial thought that “if you build something great, people will naturally flock to it” didn’t hold true. Rather, these projects had to be clearly defined, well advertised in advance, evaluated against a multitude of user cases (targeted to the grumpiest adopters first), leaps and bounds better than existing options, and adoptable with little to no effort.

The more consumers you have for common tooling and adoption, the more time you actually have to spend doing things other than writing code. This may sound obvious in retrospect, but clear end goals, believable dates, regular updates, and constant contact with consumers is paramount. Often skeptical consumers will ask, “If my current one-off shell script works okay, do I really need this?” Adoption of common software or processes is analogous to reliability as a feature—you may build the best thing in the world, but if people don’t adopt it (or can’t use it if it’s not reliable), it’s not useful to anyone. Having a plan for adoption—from champions to beta testers to executive sponsors to dedicated engineers who understand the importance of minimizing barriers to adoption—is both the end goal and the starting point when it comes to building and adopting common tools and practices.

This is because adoption drives a network effect: as the scale and reach of common software tools increases, incremental improvements to those tools are more valuable to the organization. As the value of the tools increases, development effort dedicated to them also tends to increase. Some of this development effort naturally goes toward further reducing migration costs, incentivizing greater adoption. Broad adoption encourages building organization-wide improvements in a consistent, product-like fashion, and justifies staffing full teams to support the tools for the long term. These tools should be characterized by rapid development, feature stability, common control surfaces, and automatable APIs.

When it comes to measuring the impact of such efforts, we can ask questions similar to the following:

• How quickly can a new product developer build and manage a world-scale service?
• Enabled by common tools and practices, how easily can an SRE in one domain move to another domain?
• How many services can be managed with the same primitives, as end-to-end user experiences versus separate services?

These are all possible and highly valuable ways to measure impact, but our first measurement must be adoption.

As demonstrated by the Waze and horizontal software case studies, even within a single company, SRE change management may need to tackle a variety of problem spaces and organizational context. As a result, there’s likely no single formal model of change management that will neatly apply to the spectrum of changes any given organization may tackle. However, these frameworks, particularly Kotter’s eight-step process and the Prosci ADKAR model, can provide useful insights for approaching change. One commonality across any change necessary in an environment as dynamic as SRE is constant reevaluation and iteration. While many changes may start organically in a grassroots fashion, most can benefit from structured coordination and planning as the changes mature.

1 Elisabeth Kübler-Ross, On Death and Dying: What the Dying Have to Teach Doctors, Nurses, Clergy and Their Own Families (New York: Scribner, 1969).

Chapter 20 - SRE Team Lifecycles

Copyright © 2018 Google, Inc. Published by O'Reilly Media, Inc. Licensed under CC BY-NC-ND 4.0

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FEBRUARY 17, 2020

This in turn shifts demand towards soft skills such as leadership and creative problem-solving (a key takeaway from LinkedIn’s 2020 Workplace Learning Report). via Google Analytics, Salesforce) had more than a few delegates nodding knowingly. The Fidelity team wanted to engage employees’ sense of curiosity about learning.

LT 2020 & the Trends Shaping Workplace Learning

From Learning to Marketing, One Leader’s Worthwhile Switch

JANUARY 9, 2017

As CLO, Grodnitzky took on a customer-facing role, writing thought leadership pieces and representing Richardson to existing and prospective clients. They have strong buy-in from leadership , in words and actions. Thus, the transition to CMO came naturally. Our customers are both sales professionals and learning leaders,” she explained.

July bonanza at Working Smarter Daily

JULY 30, 2011

Google + – fundamental misunderstanding of networks? - George Siemens , July 10, 2011. What is Google + for? - David Weinberger , July 8, 2011. 21st Century Leadership - Jay Cross , July 12, 2011. The fabulous case study of Queensland Police on Facebook - Ross Dawson , July 18, 2011.

Event Marketing: Your complete Guide for 2023

JANUARY 3, 2023

Expand thought leadership & authority. Thought Leadership and Networking Events. Thought Leadership events are a great way to build your brand and make a positive appearance in the middle of the crowd you really want to impress. An example of this event type is Rethink Leadership for Senior Pastors. Product Launches.

How L&D Can Deliver When the CEO Delivers a Capability-Led Business Strategy

FEBRUARY 16, 2023

So I did a bit of a job crafting, I think, so whenever there was a new development opportunity, I put my hand up, ended up facilitating some leadership workshops and things like that. And so we've identified innovation, digital customer experience, leadership , safety and wellbeing as really strategic capabilities. Where are we at now?

Free L&D webinars for July 2019

Limestone Learning

JUNE 28, 2019

Top organizations are embracing coaching as an integral part of leadership performance, and in response, the Goleman EI team has launched new training strategies with executive coaches from around the world. You’ll learn how to: Establish your leadership team's baseline. Some case studies of the SDGs in practice.

Designing eLearning Experiences that Match Learner Preferences

JULY 27, 2015

Since then, his work has been transformed into DISC-based self-assessments that have been widely used to build self-awareness, teams, leadership skills, management skills, skills in conflict management and negotiation, and for a multitude of communication-related purposes. Follow her on Twitter , LinkedIn or Google +.

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Competition Law Enforcement: Key Case Studies

Competition law enforcement has been instrumental in promoting fair market practices, with landmark cases serving as pivotal precedents for shaping the legal and regulatory landscape. Notable examples include Microsoft's antitrust saga, in which the company was accused of abusing its monopoly power by bundling its Internet Explorer web browser with its Windows operating system. The Google Shopping case is another prominent example, where the European Commission fined Google €2.42 billion for breaching EU antitrust rules by favoring its own shopping service over rivals. These cases, along with cartel conduct, abuse of dominance, and merger reviews in various regions, have contributed substantially to the development of competition law enforcement. Further examination of these cases and others reveals the complexities and nuances of competition law enforcement in action.

Table of Contents

Microsoft's Antitrust Saga

As the digital landscape was rapidly evolving in the 1990s, Microsoft's dominance in the software industry began to raise eyebrows among regulators and competitors alike. The company's market share and aggressive business practices sparked concerns about potential abuse of its monopoly leverage. Regulatory oversight bodies, such as the United States Department of Justice (DOJ), initiated investigations into Microsoft's conduct, focusing on its bundling of software products and alleged exclusionary behavior.

The DOJ filed an antitrust lawsuit against Microsoft in 1998, accusing the company of violating Section 2 of the Sherman Act. The case centered on Microsoft's practice of bundling its Internet Explorer web browser with its Windows operating system, thereby stifling competition from rival browser providers. The court ultimately ruled that Microsoft had engaged in anticompetitive behavior, ordering the company to split into two separate entities. While the breakup was later overturned on appeal, the case marked a significant milestone in the enforcement of competition law, highlighting the need for robust regulatory oversight to prevent the misuse of monopoly leverage.

The Google Shopping Case

The Google Shopping Case is a landmark competition law enforcement action that highlights the European Commission's scrutiny of digital platforms. In 2017, the Commission levied a record-breaking fine of €2.42 billion against Google for breaching EU antitrust rules, specifically for illegally promoting its own shopping service over those of competitors. This case centers on allegations of self-preferencing practices that distorted the online shopping market, ultimately hindering consumer choice and innovation.

Antitrust Allegations Raised

Regulatory scrutiny has been a recurring theme in Google's operational landscape, and the Google Shopping case is a seminal example of this phenomenon. The European Commission's antitrust allegations against Google underscore the importance of regulatory oversight in ensuring a level playing field in the digital marketplace. The Commission's investigation, launched in 2010, centered on allegations that Google had abused its dominant position in the search engine market by favoring its own comparison shopping service, Google Shopping, over rival services.

Industry scrutiny has been intense, with competitors and consumer groups arguing that Google's practices stifled innovation and hindered competition. The Commission's probe revealed that Google had systematically demoted rival comparison shopping services in its search results, while promoting its own service. This alleged conduct, the Commission argued, had a significant impact on the market, reducing traffic to rival services and depriving them of the opportunity to compete on equal terms. The Google Shopping case highlights the need for effective regulatory oversight to prevent dominant firms from abusing their market power and undermining competition.

Illegal Self-Promotion Practices

Google's self-promotion practices in the Google Shopping case have been a focal point of the European Commission's antitrust allegations. The Commission accused Google of favoring its own comparison shopping service, Google Shopping, over those of its competitors. This self-preferencing led to the demotion of rival services in search results, ultimately stifling competition. In addition, Google's practices were found to be misleading, as they included fake reviews and ratings that artificially boosted its own shopping service. Additionally, Google's advertising practices were deemed misleading, as they failed to clearly distinguish between organic search results and paid advertisements. These practices not only harmed competitors but also misled consumers, who were unable to make informed purchasing decisions. The Commission's investigation revealed that Google's self-promotion tactics had a significant impact on the market, leading to a substantial reduction in traffic to rival services. This case highlights the importance of ensuring that dominant companies do not abuse their market position through illegal self-promotion practices.

Record-Breaking Fine Imposed

In a landmark decision, the European Commission imposed a record-breaking fine of €2.42 billion on Google for breaching EU antitrust rules, marking one of the largest penalties ever levied on a single company. This decision followed a lengthy investigation into Google's alleged abuse of dominance in the online shopping market, where it was found to have unfairly promoted its own comparison shopping service, Google Shopping, over rival services.

The fine calculation was based on the gravity and duration of the infringement, as well as Google's revenue from its comparison shopping service. The European Commission considered the fine necessary to deter future anti-competitive behavior and restore fair competition in the online shopping market. This decision demonstrates the European Commission's commitment to regulatory scrutiny, ensuring that dominant companies do not abuse their market position to stifle competition. The Google Shopping case serves as a precedent for future antitrust enforcement, emphasizing the importance of fair competition in the digital economy.

Cartel Conduct in Europe

In the European competition law enforcement landscape, cartel conduct remains a significant concern, with the European Commission imposing substantial fines on companies found to have engaged in anti-competitive behavior. Notable price fixing cases have led to hefty penalties, highlighting the importance of effective leniency programs in detecting and deterring such conduct. The European Commission's approach to cartel enforcement has been shaped by its experience with high-profile cases, informing its strategies for identifying and punishing cartel activities.

European Cartel Fines

How effectively have European antitrust authorities been fining cartel participants, and what trends can be discerned from the sanctions imposed? The European Commission has been instrumental in cracking down on cartel conduct, imposing significant fines on companies found to be engaging in anti-competitive behavior. In recent years, the Commission has levied record-breaking fines, with some exceeding €1 billion.

In terms of fine calculation methods, the Commission typically considers factors such as the gravity and duration of the infringement, as well as the company's turnover. Additionally, the Commission may also take into account any mitigating or aggravating circumstances, such as cooperation with the investigation or obstruction of justice. Cartel investigations have revealed that companies often engage in sophisticated schemes to conceal their anti-competitive activities, underscoring the need for robust enforcement measures.

The Commission's approach to fining cartel participants has been shaped by its desire to deter similar conduct in the future. By imposing significant financial penalties, the Commission aims to create a strong incentive for companies to comply with competition law. In this respect, the trend towards increasingly severe fines is likely to continue, serving as a powerful deterrent to would-be cartel participants.

Price Fixing Cases

The European Commission's vigorous enforcement of competition law has led to the uncovering of numerous price fixing cases, underscoring the prevalence of cartel conduct in various industries across Europe. These cases involve anti-competitive agreements among competitors to fix prices, rig bids, or allocate markets, ultimately harming consumers and distorting competition.

These cases demonstrate the Commission's commitment to detecting and prosecuting cartel conduct, including bid rigging and market allocation schemes. By cracking down on such anti-competitive practices, the Commission aims to promote fair competition and protect consumers' interests. The Commission's enforcement actions serve as a deterrent to companies considering engaging in cartel conduct, promoting a level playing field across European markets.

Leniency Programs

A cornerstone of the European Commission's efforts to combat cartel conduct is its leniency program, which offers incentives to companies that self-report and cooperate with investigations. This program has been instrumental in detecting and prosecuting cartel cases, as it encourages companies to come forward and disclose their involvement in anti-competitive activities.

The leniency program provides significant benefits to companies that cooperate, including full immunity from fines for the first company to report a cartel and reduced fines for subsequent cooperators. The program's amnesty effectiveness is evident in the high number of cartel cases uncovered through self-reporting. In fact, the majority of cartel cases pursued by the European Commission have been initiated through leniency applications.

The leniency benefits are conditional upon the company's continuous cooperation throughout the investigation. Companies must provide detailed information about the cartel, including its scope, duration, and participants, as well as any evidence in their possession. The program's success can be attributed to its ability to create a strong incentive for companies to self-report and cooperate, thereby facilitating the detection and prosecution of cartel conduct.

Abuse of Dominance in Asia

Across Asia, competition authorities have been grappling with the complex issue of abuse of dominance, wherein a single entity or a group of entities exploit their market power to stifle competition and harm consumers. This phenomenon is particularly prevalent in markets with high concentration levels, where a single firm or a few firms wield significant market power.

In recent years, regulatory frameworks in Asia have evolved to address this issue. For instance, the Competition Commission of Singapore (CCS) has been actively enforcing Section 47 of the Competition Act, which prohibits abuse of dominance. Similarly, the Japanese Fair Trade Commission (JFTC) has been cracking down on abuse of superior bargaining position, which is a variant of abuse of dominance. In China, the State Administration for Market Regulation (SAMR) has been enforcing the Anti-Monopoly Law, which prohibits abuse of dominance. These regulatory frameworks have been instrumental in curbing abuses of market power and promoting competition in Asian markets.

Anti-Competitive Mergers Blocked

Scores of proposed mergers and acquisitions in Asia have been thwarted by competition authorities in recent years, citing concerns that these deals would substantially lessen competition in the relevant markets. These deal vetoes demonstrate the importance of merger reviews in maintaining a competitive landscape.

In several instances, the mergers were blocked due to concerns about the creation of dominant players, which would have led to reduced competition and innovation. For example, in the telecommunications sector, a proposed merger between two major players was vetoed due to fears that it would result in a dominant entity controlling a significant market share. Similarly, in the e-commerce space, a deal was rejected as it would have led to the creation of a dominant player with significant market power.

These decisions highlight the role of competition authorities in ensuring that mergers and acquisitions do not harm competition. By conducting thorough merger reviews, these authorities can identify potential competitive concerns and take steps to address them, ultimately promoting a competitive and innovative business environment.

Landmark Cases in Emerging Markets

In the domain of competition law enforcement, emerging markets have witnessed several landmark cases that have shaped the regulatory landscape and sent a strong message to businesses operating in these jurisdictions. These cases have addressed complex issues, such as market dynamics and regulatory hurdles, and have had a significant impact on the business environment.

One notable example is the case of Brazil's Administrative Council for Economic Defense (CADE) vs. Petrobras, which addressed allegations of anticompetitive practices in the fuel market. The case led to significant changes in the market dynamics of the Brazilian fuel sector, with CADE imposing substantial fines and requiring Petrobras to divest assets.

Another example is the case of India's Competition Commission of India (CCI) vs. Google, which involved allegations of abuse of dominance in the search engine market. The CCI's decision sent a strong message to digital platforms operating in India, emphasizing the significance of compliance with competition regulations.

These landmark cases demonstrate the commitment of emerging market regulators to enforcing competition laws and promoting fair market practices. They also serve as crucial precedents, shaping the regulatory landscape and influencing market dynamics in these jurisdictions.

Frequently Asked Questions

What are the consequences of non-compliance with competition law.

Non-compliance with competition law can result in severe consequences, including substantial fines imposed by regulatory authorities, as well as reputation damage that can lead to long-term financial losses and erosion of stakeholder trust.

How Do Authorities Detect Cartel Conduct in Various Industries?

Authorities detect cartel conduct through a combination of cartel markers, such as unusual pricing patterns, and industry profiling, which involves analyzing market structures and firm behaviors to identify potential collusive activities.

Can Individuals Be Held Liable for Antitrust Violations?

In antitrust law, individuals can be held liable for violations, emphasizing personal accountability. Criminal prosecutions are employed to deter and punish culpable individuals, as seen in cases where executives are fined or imprisoned for cartel participation or other anticompetitive conduct.

What Role Do Economics Play in Competition Law Enforcement?

In competition law enforcement, economics plays a crucial role through economic analysis, which informs merger reviews and antitrust investigations, providing a framework to assess market dynamics, competitive effects, and potential harm to consumers.

Are Competition Authorities Effective in Promoting Consumer Welfare?

Competition authorities' effectiveness in promoting consumer welfare is contingent upon their ability to mitigate market power abuse and resist regulatory capture, ensuring that enforcement decisions prioritize consumer interests over corporate influence.

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Case study: Kingfisher Group takes DIY approach to AI roll-out across e-commerce sites

International home improvement retailer kingfisher group opens up about the evolution of its ai strategy, and the rewards it is reaping.

• Caroline Donnelly, Senior Editor, UK

Several months into the start of the global Covid-19 coronavirus pandemic, international home improvement retail group Kingfisher debuted a revamped company strategy focused on repositioning the organisation as a digital and service-oriented entity.

Kingfisher, which owns the B&Q, Screwfix and DIY.com brands in the UK, had seen several of its brands suffer sales declines as a result of what it termed in its 2020 financial results  as “the company’s operating model becoming overly complex”.

“While some of our banners [brands] have delivered growth over the past four years … our performance has been disappointing. Group sales and retail profit need to improve,” its financial report, published in June 2020, stated.

In the wake of this realisation, the Powered by Kingfisher strategy was created, with an emphasis on ensuring each of the company’s brands was meeting the diverse and distinct needs of their respective customer bases, while also drawing on the businesses “core strengths and commercial assets”.    

“To serve customers effectively today, we also need to be digital and service-orientated, while leveraging our strong store assets,” the report added.

A month after going public with its plans for a strategic shift in how the company operates, Kingfisher announced the creation of a new role within its customer team with the appointment of Tom Betts as group data director.

Fast forward several years, and these two events have led to Kingfisher having its own in-house data and artificial intelligence (AI) team whose efforts have seen it centrally develop and roll out various digital tools that have boosted sales across its brands.

On this point, the company’s 2024 financial report stated: “Our [brands] are leveraging data and artificial intelligence to build customer-centric tools and solutions, support better commercial decision-making and higher productivity, thereby unlocking significant new sources of revenue, profit and cash.”

Speaking to Computer Weekly, Mohsen Ghasempour, group AI director at Kingfisher, said the appointment of Betts led to the creation of a team that has steadily grown in size and whose work has led to a notable uptick in sale across the group.

“We started with almost zero people on AI, and today we have around 28 – a mixture of machine learning engineers, data scientists, and engineers – so we [have the internal capabilities] to develop our own AI solutions,” he said,

“If you look at our portfolio of AI offerings today, we have 30-plus different initiatives on the go … and it might surprise people to know how much AI technology is impacting the way the DIY industry is operating.”

The company is using AI in its supply chain management and logistics function to deliver a demand forecasting model that can predict how demand for certain products will change over a 12-month period, as well as to pick up on patterns within the reviews customers leave about its products.

“We have services that sit on top of our customer reviews to extract actionable insights. Our AI algorithm can detect that 200 reviews are about product quality, and what specifically they are complaining about,” said Ghasempour.  

The company is also working on some “very cool technology” that will help the group’s in-store customers find the products they are looking for more efficiently, he added. “There is a lot happening with AI here at the moment.”

AI at the beginning

However, when Ghasempour first joined the company three years ago, Kingfisher knew it wanted to use AI to help achieve its strategic goals, but was still figuring out what role the technology would play in its business.

“When we started, there was no plan in terms of ‘This is how we’re going to use AI’,” he said. “So, the question became ‘How are we going to use it?’”

The answer to that came through trying to address what Ghasempour describes as one of the businesses’ biggest problems: a customer wanting to buy a product online that is no longer in stock.

“It wasn’t an AI problem, it was a product availability issue [that needed solving] that was affecting customer experience,” he said. “At that time, the challenge was ‘How are we going to solve it?’, but we did not necessarily think the answer was in using AI.”

While addressing this challenge, the idea of creating an “alternative product” recommendation algorithm emerged, which Ghasempour said gave way to an exploration of what role AI could play in the process.

“We started investigating how we can use AI when customers are at the point of buying a product that is not available, and how you can recommend a product which is very similar to the product that they’re looking for as an alternative,” he said. “That was the first recommendation service we developed, it went live in early 2023 on [B&Q’s online site] diy.com.”

This service has now been rolled out, in one form or another, across all of Kingfisher’s brands, and since B&Q became the early adopter of the technology, the brand has seen more than 10% of its e-commerce sales originate from product recommendations, according to the company’s own stats.

“From the basic algorithm to solve one problem, today we have 10 different recommendation algorithms that try to help the customer journey in different ways by offering [serving customers information about] frequently bought together products and personalised recommendations,” said Ghasempour.

And the early success achieved from its first forays into building AI-powered recommendation engines allowed the company to take the concept of Powered by Kingfisher even further by providing it with the proof points needed to ditch some of its legacy tech providers, he added.

“We had some legacy recommendation providers on [our]  e-commerce platform, and we started running tests A-B tests against those providers to demonstrate that we can achieve better performance, which justified building [out] this in-house [data and AI] capability even more,” he said.

“We completely replaced all the third-party providers we used for recommendation engines, so all of that, across all of our e-commerce platforms, is now powered by internal capabilities.”

These capabilities have also been created using Google Cloud’s portfolio of AI tools , with Ghasempour revealing that Kingfisher has partnerships in place with Microsoft and Amazon Web Services (AWS) too.

“Anybody wanting to build any kind of AI capability needs some infrastructure and at Kingfisher we have a partnership with all three cloud providers, but when it comes to AI and data science capability, Google has a bit more of a mature platform, from our point of view,” he said. “It was more intuitive and easier to use, so we started building that capability in Google’s infrastructure.”

Attuned to AI with Athena

Google Cloud’s fully managed development platform, Vertex AI, is playing a foundational role in the delivery of Kingfisher’s AI and data strategy, as it forms the basis of the company’s AI orchestration framework Athena.

Before the introduction of Athena, Kingfisher was effectively setting about addressing individual customer pain points, such as lack of product availability, by creating the AI microservices needed to address these problems from scratch each time.

In Kingfisher’s own words , this way of working resulted in lengthy development times for each microservice, which in turn slowed down the release time for them and caused scalability issues.

What Athena does is allow the Kingfisher team to automatically select the correct, ready-made Microsoft needed to answer a specific user issue or query, which it claims has cut the development time for new AI services from months to weeks.

“This is a fairly new technology for us, and is probably about a year old,” said Ghasempour. “And the idea behind Athena was, ‘How can we actually build a framework that means we can start to utilise the services in a in a safe and secure way, but also move fast because whoever is using this technology fastest is going to get the competitive advantage?’”

Athena acts as a “wrapper” around existing large language models, such as Google Gemini and Chat GPT, that allows Kingfisher to tap into the respective capabilities of these competing tools at once.   

“Athena can wrap around all of those large language models, and provide a stronger and more powerful service because it can utilise all of those language models at the same time, plus build the security model around them. So, we can we can track all the conversation and we can make sure there is nothing inappropriate happening,” said Ghasempour.

This means Kingfisher can essentially take a “build once, apply everywhere” approach to rolling out AI services across its retail brands.

“You can just do the development once but you can scale it up to more banners [brands] while you’re still secure in the safe environment,” said Ghasempour.

Presently, Kingfisher is using Athena to create services that will make it even easier for the company’s customers to find products using AI-based conversational, image and text searches.

For instance, if a customer does not know the name of the piece of equipment they need to replace on a household item or what the name of a certain tool is, Athena makes it possible for the customer to search the product catalogue for what they need using an image and get a result in seconds.

“All they have to do is upload a photo of the part and we’ll show them exactly what they need,” said Ghasempour.

It is also experimenting with using Athena to moderate the content of the listings published on the marketplace section of diy.com, which allows third-party sellers to sell their home improvement wares online through its website.

“Athena assesses the description of the product to check for any racism or sexism, for example, and offers visual moderation of all the product images,” said Ghasempour.  

Furthermore, the technology is being put to use internally at Kingfisher, to assist its 82,000-strong workforce with finding information about the group’s employment policies and guidelines that are contained within hundreds of internal staff documents.

“In any organisation you have a lot of documentation, from the legal team or HR, that tell staff what the rules of working there are, but people don’t go read the documents. So, at the moment, we’re putting [Athena] on top of those documents, so staff can ask an [internal chatbot] about the maternity leave policy, for example, and get the information they need,” said Ghasempour.

“Over the next couple of months, we’ve got a few more services going live internally to empower our colleagues using this technology to do their day-to-day jobs more efficiently.”

Read more about cloud AI use in retail

• Retail-related studies into AI’s influence suggest its capabilities are welcome by the sector and shoppers alike – but tech leaders advise treading cautiously.
• The French retailer has some catching up to do on its data strategy and digital transformation – and its new data chief has an ambitious roadmap to deliver on data science, business intelligence and artificial intelligence.

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Australian Diabetes Educators Association

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Excellence in diabetes care: Celebrating the winners and finalists of the 2024 Abbott Case Study Competition

29 August 2024 —Join us in congratulating the winners and finalists of the 2024 Abbott Case Study Competition , which recognises excellence in the care, education, and self-management of diabetes through the use of flash glucose monitoring, LibreView, and the ambulatory glucose profile report.

This year’s competition featured a range of outstanding submissions from dedicated professionals.

Congratulations to Sabrina Sharp for receiving the top honour, the Judge’s Choice Award , for her case study titled Supporting our patient by enhanced technology to achieve safe glucose levels and autonomy in palliative self-care during chemotherapy .

Sabrina Sharp (far left) receiving her award. Pictured with ADEA President Amanda Bartlett, Bryan Ladell from Abbott, and ADEA Vice President Ann Bush at the Australasian Diabetes Congress on 23 August.

Ms Sharp expressed her gratitude, saying she was honoured to receive the award and that it was a privilege to support her client during his diabetes and cancer journey.

She said the FreeStyle Libre 2 helped her client “maintain optimal glucose levels, offering him safety and control”.

“Although he lost his battle in July 2024, his family found comfort knowing he received the best care possible, while avoiding painful finger pricks during end-of-life care,” Ms Sharp said.

“The FreeStyle Libre 2 also gave them the confidence to enact treatment changes without undue risk of hyperglycaemia or hypoglycaemia.

Ms Sharp said working with her incredible clients, their families, her colleagues, and the team at Abbott Diabetes Care had been “an incredibly rewarding experience”.

“This recognition not only honours our collective efforts but also highlights the unique needs of a very special patient group,” she said.

We also congratulate the other finalists in the Judge’s Choice Award:

• Fran Brown : Diabetes discovery — Libre 2 brings newfound self-determination
• Yi (Angela) Jin : Overcoming therapeutic stagnation: A culturally responsive approach to improved glycaemic control and psychological well-being in type 1 diabetes
• Beck Newton : Leveraging continuous glucose monitoring to improve type 2 diabetes management

The Early Career Award was presented to Amy Zheng for her case study, Revealing the unexpected: technology’s role in discovering secondary causes of hyperglycaemia .

Amy Zheng (second from right) receiving her award. Pictured with ADEA President Amanda Bartlett, Bryan Ladell from Abbott, and ADEA Vice President Ann Bush at the Australasian Diabetes Congress on 23 August .

These professionals have made significant contributions to diabetes care, highlighting the positive impact of personalised approaches with these technologies.

They each received scholarships for professional development and full registration to the Australasian Diabetes Congress 2024.

Their case studies are featured in the top 10 of the Abbott FreeStyle Case Study booklet , with the Judge’s Choice and Early Career Award case studies also published in the Australian Diabetes Educator publication , offering wider recognition of their work.

We once again congratulate all participants and extend our gratitude to Abbott for this initiative, which underscores the vital role of technology in diabetes management.

• Read the Abbott FreeStyle Case Study booklet .