Managing Your Mission-Critical Knowledge 01-21

Managing Your Mission-Critical Knowledge

When executives talk about “knowledge management” today, the conversation usually turns very
quickly to the challenge of big data and analytics. That’s hardly surprising: Extraordinary amounts of rich, complicated data about customers, operations, and employees are now available to most managers, but that data is proving difficult to translate into useful knowledge. Surely, the thinking goes, if the right experts and the right tools are set loose on those megabytes, brilliant strategic insights will emerge

Tantalizing as the promise of big data is, an undue focus on it may cause companies to neglect something even more important—the proper management of all their strategic knowledge assets: core competencies, areas of expertise, intellectual property, and deep pools of talent. We contend that in the absence of a clear understanding of the knowledge drivers of an organization’s success, the real value of big data will never materialize.

Yet few companies think explicitly about what knowledge they possess, which parts of it are key to future success, how critical knowledge assets should be managed, and which spheres of knowledge can usefully be combined. In this article we’ll describe in detail how to manage this process.

Map Your Knowledge Assets

The first step is to put boundaries around what you’re trying to do. Even if you tried to collect and inventory all the knowledge floating around your company—the classic knowledge-management approach—you wouldn’t get anything useful from the exercise (and you’d suffer badly from cognitive overload). Our goal is to help you understand which knowledge assets—alone or in new combinations—are key to your future growth. We would bet heavily that if your company has a knowledge-management system, it doesn’t adequately parse out your mission-critical knowledge.

This step alone can be quite challenging the first time around. When we worked with a group of decision makers at ATLAS, the major particle physics experiment at the European Organization for Nuclear Research (CERN), we interviewed many stakeholders to get a holistic view of the knowledge underpinning its success and then surveyed nearly 200 other members of the organization. Ultimately we mapped only a portion of the ATLAS knowledge base, but in the process we whittled down a list of 26 knowledge domains to the eight that were deemed most important to organizational outcomes.

Absent a clear understanding of your knowledge assets, big data’s value won’t materialize.

Your list of key assets should ultimately include some that are “hard,” such as technical proficiency, and some that are “soft,” such as a culture that supports intelligent risk taking. You may also have identified knowledge that you should possess but don’t or that you suspect needs shoring up. This, too, should be captured.

The next step is to map your assets on a simple grid along two dimensions: tacit versus explicit (unstructured versus structured) and proprietary versus widespread (undiffused versus diffused). The exhibit “What Kind of Knowledge Is This?” which includes a mapping grid, will help you figure out where to place your knowledge assets on your own map. (We owe a debt to Sidney G. Winter, Ikujiro Nonaka, and the late Max Boisot for their work on these dimensions. Had he lived, Boisot would have been a coauthor on this article.)

Use these categories to help place your assets along the y axis from bottom to top:

• An expert can use the knowledge to perform tasks but cannot articulate it in a way that allows others to perform them.

• Experts can perform tasks and discuss the knowledge involved with one another.

• People can perform tasks by trial and error.

• People can perform tasks using rules of thumb, but causal relationships aren’t clear.

• It’s possible to identify and describe the relationship between variables involved in doing a task so that general principles become clear.

• The relations among variables are so well known that the outcome of actions can be calculated and reliably delivered with precision. (Knowledge assets covered under patents or other forms of copyright protection generally fit here.)

Use these categories to help place your assets along the x axis from left to right:

• Only one person in the organization has this knowledge.

• A few people in the organization have this knowledge.

• Many people in one part of the organization have this knowledge.

• People throughout the organization have this knowledge.

• Many people in the industry have this knowledge.

• Many people both inside and outside the industry have this knowledge

Unstructured versus structured.

Unstructured (tacit) knowledge involves deep, almost intuitive understanding that is hard to articulate; it’s generally rooted in great expertise. World-class, highly experienced engineers may intuit how to solve technical problems that nobody else can (and may be unable to explain their intuition). Rainmakers in a strategy consulting firm know in their bones how to steer a conversation or a discussion, develop a relationship, and close a deal, but they would have trouble telling colleagues why they made a particular move at a particular moment. 

Structured (explicit or codified) knowledge is easier to communicate: A company that’s expert in the use of discovery-driven planning, for example, can bring people up to speed on that methodology quickly because it has given them recourse to a common language, rules of thumb, and conceptual frameworks. Some knowledge is so fully structured that it can be captured in patents, software, or other intellectual property.

Undiffused versus diffused.

To what extent is the knowledge spread through—or outside—the company? One division may have expertise in negotiating with officials of the Chinese government, for example, which another division totally lacks. That knowledge is obviously undiffused. But most companies have certain broadly shared competencies: Those in the consumer packaged goods industry tend to have companywide strength in developing and marketing new brands; and many employees in the defense industry know a lot about bidding on government contracts. Some knowledge, of course, is diffused far beyond the boundaries of the organization.

Interpret the Map

Simply mapping your knowledge assets and then discussing the map with your senior team can uncover important insights and ideas for value creation, as our experience with decision makers at Boeing and ATLAS demonstrate.

Global sourcing at Boeing.

Sourcing managers at Boeing were aware that their relationships with internationally dispersed customers, suppliers, and partners were changing. The whole ecosystem was sharing in the creation of new aircraft technologies and services and in the associated risks. Future success would depend on learning to manage this interdependence.

With that insight in mind, the managers mapped the critical knowledge assets in their global sourcing activities, which ultimately resulted in a research paper that one of us (Martin Ihrig) coauthored with Sherry Kennedy-Reid of Boeing. They saw that cost-related knowledge—performance metrics, IP strategy, and supply-base management—was well structured and widely diffused. However, knowledge about supplier capabilities, although codified, had not spread throughout the Boeing sourcing community. And other knowledge that was important to future value creation—how to leverage Boeing’s potent and technically sophisticated culture for effective communication and negotiation, determine Boeing’s business needs and global sourcing strategy, and, most important, assess the geopolitical influences on global sourcing decisions—was neither codified nor widely shared.

Taken together, these observations suggested that Boeing was placing greater emphasis on technical efficiencies, such as improving processes and productivity, than on strategic growth, such as creating research initiatives with suppliers or building a shared innovation platform. As Boeing’s business became progressively more intertwined with that of its ecosystem partners, the development of knowledge assets would need to change.

Insights from this mapping exercise enabled the team to recommend several initiatives aimed at developing and disseminating tacit knowledge, such as a program to help employees who had a deeper understanding of geopolitical influences to put some structure around their knowledge and pass it on to others in the company, and a program to identify the capabilities of key suppliers and determine how Boeing could work more strategically with them.

Advanced physics at CERN.

The experimental work done at ATLAS is carried out by thousands of visiting scientists from 177 organizations in 38 countries, working without a traditional top-down hierarchy. This extraordinary operation has had spectacular results, including the discovery of the Higgs boson, for which Peter Higgs and François Englert were awarded a Nobel Prize in 2013. Our mapping of ATLAS’s knowledge base was done in a research partnership with Agustí Canals, Markus Nordberg, and Max Boisot.

Our team had a surprising insight when a study of that map revealed that “overview of the ATLAS experiment” was one of the top eight knowledge domains. We hadn’t given much thought to that domain, but we quickly realized how central it was to a knowledge-development program like ATLAS. Changes in the overall direction of a project can’t easily be codified when the project is so complex. The direction is continually evolving, and not necessarily in a linear fashion, as the technical and scientific work advances; but individual researchers can’t adapt their work accordingly when they don’t know what that direction is. ATLAS requires that huge numbers of people, from many countries and cultures, understand what others are learning and how it affects the overall technical direction.

Without the knowledge map, the leadership team at ATLAS would have predicted that scientific and technical knowledge were regarded as mission critical—indeed, most existing resources went to helping those domains make progress. But we found it extraordinary that the soft domains of project management and communication skills also emerged as central to ATLAS’s performance. Retrospectively, that made sense: A consensus on overall direction depends on the successful sharing of knowledge among specializations and between scientists as they cycle back to their home organizations and new people take their place. These important soft domains were much less developed and not well diffused; clearly, they needed more resources and attention.

Identify New Opportunities

Mapping knowledge assets and discussing their implications often leads directly to strategic insights, as it did at Boeing and ATLAS. But we also find it helpful to systematically explore what would happen if knowledge were moved around on the map or different spheres of it were combined. Here are some examples:

Selectively structure tacit knowledge (move it up on your map’s Y axis).

The proprietary knowledge assets in the lower left corner of your map are often the most important knowledge your company has—the deep-seated source of future strategic advantage. You need to think about which of them can and should become more structured so that (for example) your basic research will lead to the creation of bona fide intellectual property that can be developed into new products, licensed, or otherwise monetized. Structuring tacit knowledge often involves capturing expert employees’ insights with the ultimate goal of disseminating them to many more people in the company. In general, speeding up codification will increase the value of knowledge. But making the tacit explicit can also be dangerous. The more codified the knowledge is, the more easily it may be diffused and copied externally.

When you’re trying to decide what to structure further and what to keep tacit, it can be useful to distinguish between product and process. Suppose you’ve decided that your expertise in some technical domain can be codified into intellectual property. You may want to capture some of your process knowledge—whether it’s an engineer’s know-how or the conversational routines your marketing people use to tease out emerging customer needs—only informally. That way, even if a patent expires or codified knowledge is leaked, essential experience stays within the company.

Disseminate knowledge within the company (move it to the right on your map’s X axis).

Purposefully deciding which knowledge to diffuse internally can pay huge dividends. Very often one division is wrestling with a problem that another division has solved, and close study of the map will reveal the potential for productive sharing—as it would with the exemplary business unit’s expertise in negotiating with the Chinese. Productive sharing can also be done between functions: Korean chaebols (conglomerates) expend considerable money and effort to ensure that knowledge is transferred from company to company as well as from headquarters to subsidiaries.

The ease of knowledge sharing is directly proportional to the degree of knowledge codification, of course: A written document or spreadsheet is easier to share than tacit experience accumulated over many years. Some tacit knowledge can’t be codified but can be shared. One powerful way to do so internally is to run workshops that bring together people who have subject matter expertise with people facing a particular problem for which that expertise is relevant. Apprenticeship programs, too, have long been an effective way to transfer difficult-to-codify tacit knowledge.

Diffuse knowledge outside the company (move it farther right on your map’s X axis).

The most straightforward way to create value through knowledge dissemination is to sell or license your intellectual property. DuPont, for example, commercializes only a small fraction of the hundreds of patents it owns; the rest can be licensed, sold, or shared with other companies. Even companies without patents can often identify new markets for existing IP. This magazine is an example: Reprints of HBR articles have been sold to MBA and corporate learning programs for decades. A few years ago someone had the idea of collecting the best of those articles in “Must Read” collections for individual buyers, and a profitable business was born.

Some companies give away knowledge and still make a big profit.

Many companies are experimenting with less familiar ways of sharing knowledge across organizational boundaries. If suppliers, customers, and even competitors that work together on projects are creating value within your ecosystem, as at Boeing, this is worth considering. But you should keep in mind what knowledge must be protected; your map of assets will help you make those judgment calls.

Some companies even give away knowledge, ultimately making more money than they would if they kept it proprietary. In the early 1990s Adobe Systems saw an opportunity to develop a file-sharing format that would retain the text, fonts, images, and other graphics in a document no matter what operating system, hardware, or software was used to send and view it. Adobe was among the first to develop the idea behind the PDF. It then structured that knowledge in the form of the Adobe Acrobat PDF Writer and Adobe Reader. It shared the Reader on the internet, thereby creating demand for the Writer (at $300 and up), which was free from competition for years and remains one of Adobe’s leading products. Similarly, McKinsey shares selected insights through McKinsey Quarterly, generating demand for its proprietary problem-solving skills.

The recent decision of the business magnate and inventor Elon Musk to share Tesla Motors patents with anyone who wants to use them was also very astute. Clearly, Musk believes that Tesla (like Adobe) will make more money if more people build on the platform he has provided. His decision also recognizes that in order to thrive, Tesla (like Boeing) needs to create a strong ecosystem. It’s a vote of confidence in the company’s capacity to protect enough tacit knowledge to stay ahead of the competition. (Musk told a reporter for Bloomberg Businessweek, “You want to be innovating so fast that you invalidate your prior patents, in terms of what really matters. It’s the velocity of innovation that matters.”) This is one of the most interesting examples of open innovation that we’ve seen: Musk is betting not just that he can pull more partners into the world of electric cars but that he can pull the mainstream automobile industry into a more responsible position with respect to climate change.

Contextualize knowledge (move it down on your map’s Y axis).

Codified knowledge can be applied in less structured spaces in a variety of ways. Sometimes it’s a matter of taking well-established routines and applying them to new businesses. This approach is central to the growth strategies of many companies. Procter & Gamble, for instance, uses world-class brand-building competencies when it moves into new markets and develops new products. Similarly, Goldman Sachs rapidly generates new investment banking offerings by applying its analytics capabilities to changes in financial market conditions.

Contextualization can also come from combining structured and unstructured knowledge. The people who originally tried to build knowledge-management systems for consulting firms quickly discovered that most consultants used codified information as a networking tool: They would notice who wrote an article on sourcing from Indonesia (for example) and then talk with that person directly, picking her brain for more-tacit insights. Indeed, many companies build competitive advantage on just such combinations.

To be applied in a new setting, codified knowledge must generally be contextualized. If Boeing USA comes up with a new production process and then ships the related knowledge to China in the form of supporting documents, Chinese engineers have to assimilate the knowledge and adapt it to their context.

Discover new knowledge (move it to the left on your map’s X axis).

The most challenging—and highest-potential—opportunities often come from spotting connections between disparate areas of expertise (sometimes inside the company, sometimes outside it). The analytic techniques that can turn big data into big knowledge are used partly in hopes of finding such unexpected connections.


In the pursuit of innovation, flashes of insight can come from many sources. Sometimes a new technology embedded in an existing product makes it possible to change your value proposition. That happened when Rolls-Royce’s jet engine sensors provided the company with new performance data, which in turn made it more profitable to sell power by the hour than to sell engines outright. Thinking about someone else’s business model can lead to strategic insights as well. After managers at CEMEX studied how FedEx, Domino’s, and ambulance squads operate, they decided to charge for delivering truckloads of ready-mix concrete within a specified time window rather than for cubic meters of the product. Changes in the external environment can create new opportunities. Subway went from an also-ran to a high-growth fast-food business when it capitalized on consumers’ growing interest in tasty, more-nutritious, low-calorie food. Your company may have developed valuable process expertise that you could sell through consulting to other companies even outside your industry. IBM has done that many times over. 

It’s not easy to systematize this part of the knowledge-development process, which arises to some extent from intuition, tacit knowledge, and time spent studying the map. The ATLAS team’s insight about the importance of soft skills is an example. So is Boeing’s insight that becoming part of an interdependent ecosystem had major implications for what kinds of knowledge would have to be developed. A small publishing industry that is devoted to helping companies make innovative connections of this kind includes the book MarketBusters: 40 Strategic Moves That Drive Exceptional Business Growth, which one of us (Ian MacMillan) wrote with Rita McGrath; William Duggan’s Strategic Intuition: The Creative Spark in Human Achievement; and Frans Johansson’s The Medici Effect: What Elephants and Epidemics Can Teach Us About Innovation

One thing we can assure you: Your competitors will have access to the same kinds of data and general industry knowledge that you do. So your future success depends on developing a new kind of expertise: the ability to leverage your proprietary knowledge strategically and to make useful connections between seemingly unrelated knowledge assets or tap fallow, undeveloped knowledge.
Companies invest tens of millions of dollars to develop knowledge but pay scant attention to whether it contributes to future competitive advantage. The process we’ve outlined here is meant to prevent that lapse. Once you’ve mapped your mission-critical knowledge assets, the challenge is to be disciplined about which of them to develop and exploit, keeping future growth front and center. (Remember, strategy always includes deciding what not to do.) If your company thoughtfully manages its knowledge portfolio, it will achieve a distinct competitive advantage.





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Staying in the Know 06-10

Staying in the Know

In an era of information overload, getting the right information remains a challenge for time-pressed executives. Is it time to overhaul your personal knowledge infrastructure?

A common thread runs through many recent corporate setbacks and scandals. In crises ranging from BP’s Deepwater Horizon oil spill debacle to the Libor rate-fixing scandal in the City of London, the troubles simmered below the CEO’s radar. By the time the problems were revealed, most of the damage had arguably already been done. Despite indications that large companies are becoming increasingly complicated to manage,1 executives are still responsible for staying abreast of what’s going in their organization. But how do you keep tabs on what your competitors and employees are doing? How do you spot the next big idea and make the best judgments? How do you distinguish usable information from distracting noise? And how do you maintain focus on what’s critical?

Many management experts have assumed that better information systems and more data would solve the problem. Some have pushed for faster and more powerful information technologies. Others have put their faith in better dashboards, big data and social networking. But is better technology or more tools really the most promising way forward? We think not. In this article, we maintain that the capacity of senior executives to remain appropriately and effectively knowledgeable in order to perform their jobs is based on a personal and organizational capability to continually “stay in the know” by assembling and maintaining what we call a “personal knowledge infrastructure.” And while information technologies may be part of this personal knowledge infrastructure, they are really just one of the components.

We are not the first researchers to make this claim. More than 40 years ago, organizational theorist Henry Mintzberg suggested that information was central to managerial work and that the most important managerial roles revolved around information (monitoring, disseminating and acting as a spokesperson). Mintzberg described managers as the nerve centers of organizations and said informational activities “tie all managerial work together.”2 Other researchers suggested that management itself could be considered a form of information gathering and that we are quickly moving from an information society to an attention economy, where competitive advantage comes not from acquiring more information but from knowing what to pay attention to.3 Later research confirmed that dealing with information is critical and found that managers’ communication abilities are directly related to their performance.4

While the importance of informational roles and activities is well established, we take the idea a step further, arguing that managers — and especially senior executives — are only as good at acquiring and interpreting critical information as their personal knowledge infrastructures are. Managers rely on specific learned modes to manage and allocate their attention.5 However, how we pay attention is not simply a matter of internal mental processes that we can do little about. Rather, attentiveness (in other words, the capacity to stay on top, and the ability to distinguish between what matters and what doesn’t) mostly stems from what managers do or don’t do, whom they talk to and when, and what tools and tricks of the trade they use. In short, attentiveness relies on and is facilitated by things we can observe — and things we can do something about.

Technologies and new tools are not and cannot be “silver bullet” solutions. At times, simpler things such as talking to customers or networking with board members may be more important, provided they are done methodically and with some purpose. Selecting when particular elements are appropriate depends on the circumstances. As a result, understanding and, when needed, overhauling one’s personal knowledge infrastructure should be routine. In this article, we explain how this can be done, drawing on insights obtained by shadowing individual CEOs as they went about their daily jobs.6

About the Research

To uncover how top executives deal with information and knowledge, we conducted an observation-based exploratory study using a rigorous ethnographic protocol successfully employed in the past. We followed seven chief executives through their working days for several weeks. We went where they went, watched what they did, listened to what they and others said and asked what was going on when we did not understand. We also discussed our findings with them and with invited colleagues as part of structured feedback sessions.

Our sample comprised seven CEOs of acute and mental health organizations that are part of the National Health Service in England. In England, health care is provided by public sector bodies called trusts. Our sample included organizations that run multiple hospitals, have an annual budget of more than 500 million pounds and have up to 10,000 employees. The CEOs have both legal and financial responsibility. The sample included both men and women (3:4). The CEOs had diverse professional backgrounds (NHS management, private sector, nursing and medical) and were at different points in their careers, both in terms of tenure in their present post and overall experience at the CEO level. The sample also included organizations with different performance levels according to indicators by which their performance was monitored by national regulators (for example, financially sound vs. struggling).

CEOs were observed for five or more weeks, apart from one subject, where observations lasted 3½ weeks. The researchers had good access to the CEOs and were able to document nearly all aspects of their work, with exceptions such as one-to-one supervisory meetings with junior colleagues, HR-related meetings concerning individuals and private meetings with patients. When CEOs worked from home, data was collected in interviews afterwards. We conducted semi-structured interviews with five of the CEOs and a number of informal interviews with the other two CEOs. In addition, we conducted two formal interviews with two different personal assistants, which were recorded and lasted approximately half an hour each. Additional data came from meeting papers, articles referenced by the CEOs and copies of publications consulted, and they were supplemented by externally available information such as annual trust reports and regulatory documents. Following the study, our results were shared with two groups of CEOs at dedicated sector events. Those CEOs helped us to refine our findings and elaborate on the notion of the personal knowledge infrastructure.

Our research is based on a two-year study of the day-to-day work of seven CEOs of some of the largest and most challenging hospital- and mental health-based organizations in England. (See “About the Research.”) We chose to study health-care executives because they sit at the crossroads between the private and public sectors and therefore are expected to meet multiple, often competing, demands. To say that the informational landscapes in these organizations are complex is an understatement. Yet the organizations are increasingly subject to pressures to become more transparent, even as they compete with each other. Therefore they seemed to be a good choice as settings for studying the challenges of using information and knowledge to stay on top and ahead of the curve. Throughout our research we sought to answer a simple question: How did the CEOs know what they needed to know in order to be effective at their jobs?

“Nothing but Talking”

One of the first things that struck us was that, in contrast to the popular image of CEOs as lonely, heroic decision makers, the individuals we studied did not seek information or utilize discrete pieces of evidence for the purpose of making decisions. Rather, they often sought something much more ordinary: to make themselves knowledgeable in order to be ready for any eventuality, so that they could understand what to do next. Indeed, one of their main preoccupations appeared to be staying on top of what was happening within and around their organizations. As one put it: “The worst thing for a CEO is to find yourself asking after the fact: How could this happen without me knowing?”

Notably, staying on top was not a separate activity in addition to what the CEOs already did, but rather something they mostly did without thinking and without noticing — or something that they achieved while doing something else. Calling a former colleague who was in the news for the wrong reasons (an accident, a bad report from inspectors, protests about the closure of a loss-making hospital) can produce multiple outcomes: reinforcing a relationship and demonstrating solidarity, but also finding out what is going on. Indeed, many of the CEOs had difficulty acknowledging that checking in with people was an integral part of their job — hence the often-heard comment, “I do not know what has happened to my workday … It seems I have done nothing but talking.”

The Personal Knowledge Infrastructure

The CEOs we studied didn’t leave the process of staying informed to chance. Rather, they relied on a habitual and recurrent set of practices, relationships and tools of the trade, which constituted a personal knowledge infrastructure that supported them in their daily tasks of understanding, foreseeing and managing. This tacit and rarely discussed infrastructure, which was very different from their IT system, helped them to know what needed to be done and to get a sense of the right way forward. What made some CEOs more effective than others was not merely the characteristics of the individual components of their personal knowledge infrastructure but also the quality of the whole and its fit with the specific needs of the job. This personal knowledge infrastructure comprised three main elements: routine practices, relationships, and tools and technologies.

First, every CEO had a set of routine practices she or he relied on — things such as checking the morning news, running periodic review meetings, dropping by immediate collaborators’ offices to ask what was often “just a quick question,” walking around and occasionally even going to the cafeteria “to check how things are going.” These practices were not just internal. The CEOs also met with board members and managers of other organizations, attended conferences and staff events and participated in ceremonial functions such as charity events. Some of the gatherings were framed as leisure opportunities (having a drink, playing golf), but they weren’t entirely social. CEOs returned from such events with information and news they shared with various associates. Similarly, sitting on boards of other organizations was often seen as a necessary evil that helped the CEOs get a broader overview of what was going on beyond their organization.

Second, the personal knowledge infrastructure contained a number of social relationships. Like prior researchers, we found that most CEOs’ work was conducted verbally and was accomplished with and through others. Our CEOs used their relationships both to gather information and to make sense of it.7 For example, every CEO we studied carefully cultivated strategic relationships within and outside the organization. These relationships were usually engineered to produce a combination of breadth and depth of intelligence. Their network of contacts constituted a form of social capital that had been accumulated over time. On many occasions, we observed CEOs interacting with long-term colleagues, previous members of their staff and people with whom they had done business. They used their contacts to gather weak signals (on the principle that today’s gossip can become tomorrow’s news), triangulate information and confirm or contradict their evolving insights. Some of the CEOs were extremely strategic and nurtured relationships with various stakeholders (for example, management consultants, politicians or local leaders), whom they saw regularly for dinner or a drink. Some CEOs also relied on small groups of peers, whom they met with on a regular basis. These groups of peers, who were often also “comrades in adversity” facing similar challenges, operated both as a support group and as a precious setting where sensitive information was exchanged on the basis of reciprocity.

However, not all of the contacts were treated the same way.8 The CEOs appeared to have an informal hierarchy: those who were more distant, who could be used as a source of signals and needed to be taken with a grain of salt; those who were trusted and tended to provide reliable intelligence (for example, board members or colleagues, as well as their assistants); and finally, those with whom the various streams of information could be discussed and processed — the inner circle. All of the CEOs in our sample relied heavily on such an inner circle, usually composed of selected executive team members with whom they had the most intense interactions. The CEOs used these individuals not only to obtain information, often informally (given the open-door policy that was in operation for most CEOs), but also as sounding boards to test emerging understandings and reconcile possibly competing insights. These interactions allowed the CEOs not only to connect the dots but, more importantly, to figure out which information qualified as a dot that had to be connected further.

Finally, the CEOs’ personal knowledge infrastructures included a variety of tools of the trade. These included traditional tools such as phone, email, reports and journal articles from industry magazines, as well as less traditional sources such as Twitter, blogs and other social media. Most CEOs utilized some form of electronic reporting system or audit-based dashboard that helped them track critical performance indicators, and most consulted these tools regularly, but the sophistication of the tools varied substantially. (See “Components of a Personal Knowledge Infrastructure.”)

Components of a Personal Knowledge Infrastructure

To stay on top of things, CEOs need a combination of three elements: people who feed them information and act as sounding boards; routine activities; and technologies that allow them to track performance and pick up signals. These elements constitute a CEO’s personal knowledge infrastructure. What comes to the CEO’s attention and what stays under the radar depends on the makeup of this infrastructure.

Although most CEOs had a small pile of “will read” books in their office, they rarely had time for books or magazines during the course of a working day. Personal preferences played an important role here, more so than in the two previous categories. For example, while some CEOs relied heavily on mobile phones for calls and texts, others used email almost exclusively. Contrary to our expectations, most of the CEOs dealt personally with a range of emails — this was how their work was done. Some CEOs made very little use of written documents and required short summaries. Others wanted to have complete documentation “just in case.” Some CEOs still found comfort in printed paper; few were happy to go paperless.

One critical aspect of personal knowledge infrastructures was the extent to which individual elements were often intended to support each other. For example, CEOs who liked to run large formal meetings also invested significant time in social relationships, consulting collaborators on a one-to-one basis. The CEO of an organization that was struggling with issues of trust and hidden or misplaced information was working to triangulate soft data with hard knowledge. This often required him to follow up with people individually (for example, phoning staff members directly to corroborate information or requesting documentation from outside sources) while also working to set up formal structures currently lacking.

How the Personal Knowledge Infrastructure Evolves

Although all of the CEOs relied on a personal knowledge infrastructure, how these were composed varied greatly. We saw differences across all seven CEOs in terms of whether personal knowledge infrastructures had particular elements and also the amount of emphasis each element received. Two examples illustrate how different personal knowledge infrastructures contrasted with specific leadership styles in different situations.

CEO 1: Knowing the Details in a Struggling Organization

A newly appointed CEO was running a struggling hospital-based organization that was receiving increased regulatory attention for financial reasons. His personal knowledge infrastructure was designed to help him closely monitor his organization. He ran large, often long, weekly management meetings that provided an opportunity for all team members to examine operations and share and obtain a wealth of information. After the formal meetings, conversations continued in the executive offices. The CEO spent the bulk of his time in regular meetings with local managers of health-care organizations and funding agencies, picking up signals and providing insight into the work and progress of his organization. He also spent time working on wards and visiting and talking to staff. Moreover, he cultivated a wide network of colleagues whom he often consulted in rather informal ways and maintained external links to support his key strategic tasks. He had an open-door policy, both as a symbol of change and as a permanent invitation. He felt comfortable digging through reports and documents, and he set aside time on trains to go through what he called “the train pile of documents.” Though the CEO used the phone and the Internet, he liked to attend conferences and networking events to develop a broad view of the business environment.

CEO 2: Managing Via a Mix of the Formal and Informal

The second CEO, who had been in his position for more than five years, used a very different set of practices and tools. He worked with an established team to run an organization that prided itself on its ability to achieve operational excellence and strategic growth. Throughout the day, this CEO had a series of chats with executives, which often expanded into conversations between him and several people. Indeed, much of his working day was spent in what appeared as free-form interaction: sharing information informally, only sporadically framed by discussion about an immediate problem concerning a patient or a medical concern. 

This CEO rarely attended local meetings, so the other executives were an information gateway to local strategic issues for him. However, the headquarters-based, executive-team orientation was reinforced by several other structures, relationships and tools, purposefully arranged by the CEO so he could remain in the know. First, there was an executive who the CEO felt had a very different approach from the others, which gave him another voice and view to consider. The CEO also had an IT performance system, which he consulted every morning and which allowed him to identify any serious performance issues in the organization without needing to rely on reports from executives. 

The CEO supplemented such insights with visits to wards and other areas of the hospitals late in the evening and on weekends, which allowed him to gain informal insights from veteran staff. The internal systems were supported by national-level policy work and involvement via leadership positions in sector organizations and initiatives and networking. These allowed the CEO to both formally and informally stay in the know regarding strategic issues of potential relevance, and also to influence their direction to the benefit of his organization.

What Makes It Personal

As we have seen, different CEOs use different knowledge infrastructures that reflect both what they personally need and where their organizations are at a particular point in time. In each case, the context was particularly relevant. We saw different types of knowledge infrastructures (in other words, combinations of tools, practices and relationships) in relation to seven factors:

The CEO’s Experience

More experienced CEOs often had a more defined personal style that they carried with them when they changed jobs. Some had specific practices that they tried to reactivate in the new workplace and a network of contacts that constituted the social capital they had accrued over the years; we saw this in the case of a CEO facing an operational challenge in his new organization, when he called a former colleague for advice.

Job Tenure

The more time CEOs spent in the same organization, the more they learned, often the hard way, about sources they could trust and how they could make these sources work, given their existing infrastructures and approaches to work.

Makeup of the Executive Team and Board

The composition of the top management team, how competent its members are perceived to be and how well they work as a team affected the makeup of the inner circle. CEOs often included in their inner conversational circles directors who were easy to talk to or were particularly good at collecting and relaying intelligence. However, many CEOs, like the second CEO discussed above, also saw value in having friendly “devil’s advocates” on staff who were able to present different views and act as meaningful counterweights.

Organizational Conditions and Pressures

Organizations with different financial, efficiency, quality and safety environments posed different issues for the CEOs. When the conditions changed, they had to retune their antennae accordingly. A particular challenge involved the tools and technologies available. Systems can be powerful but are costly and difficult to change. Most CEOs worked to modify and develop existing systems but often they didn’t have a lot of room to make immediate changes. They worked with what they had while instigating long-term interventions so that the system would suit them rather than the other way around.

Strategic Vision

Entering new markets or introducing new products or services required CEOs to adapt their personal knowledge infrastructure accordingly. For instance, a CEO facing a possible merger began adding M&A events to his calendar.

Economic, Competitive and Regulatory Environment

The macro environment determined whether a CEO’s personal knowledge infrastructure was appropriate. Changes in the environment forced CEOs to adapt their existing personal knowledge infrastructure and reactivate old relationships.

The Kind of Manager the CEO Wants to Be

Ultimately, the above factors were filtered through the prism of “what kind of manager I would like to be.” For instance, a CEO who valued transparency and closeness to his organization’s users established a strong presence on social media and utilized this channel to garner insights into the experience of patients and their families. This sometimes allowed him to identify problems (such as low quality of service in a particular location or low staff morale) before his managers reported them.

Taken together, the factors above suggest that effective personal knowledge infrastructures tend to be unique and personal and conform to the preferences of the manager. They need to be continually adapted, tweaked and refined in keeping with the shifting nature of the CEO’s job, the environment and new opportunities.

Although most of our CEOs were reasonably successful, everyone saw room for improvement. Indeed, a CEO’s effectiveness was a reflection of his or her situation and person-specific alignment. For example, one CEO had spent years building a sophisticated IT performance monitoring system. Another CEO didn’t see having such a system as a priority; in his view, being an effective manager entailed moving away from operational considerations and focusing more on strategic and systemwide issues. 

The challenge of changing as the organization changes was highlighted by several CEOs: The personal knowledge infrastructure that serves you well during a period of crisis and turmoil may get in the way in calmer waters. The lesson is that there is no single best personal knowledge infrastructure. Through personal reflection, managers and CEOs need to learn how to ask themselves difficult questions regarding the quality and fit of the practices, tools and relationships that they rely on to become knowledgeable. They also need to develop structured ways of asking such questions consistently and over time — rather than waiting for something to go terribly wrong.

Four Traps

The quality and fit of the CEO’s personal knowledge infrastructure is critical because it determines how he or she sees the world and defines himself or herself as a manager and CEO. It is the prism through which managers understand what is going on, and it provides the horizon of information sources through which this understanding will be probed and evaluated. However, a poorly designed personal knowledge infrastructure can lock the manager inside an information bubble and create information biases and blind spots.9 Managers may only realize this when something happens that was not on their radar or when an incident exposes the misalignment between the current demands and needs of their job and their own role. By closely examining the work practices of our CEOs over time, we identified four potential traps:

1. Not Obtaining the Information You Need

Although conventional wisdom suggests that the main problem for today’s executives is too much information, the real problem is not enough relevant information. Due to insufficient monitoring, an inappropriate mix of monitoring practices, inadequate or insufficient social relationships, and information overload, managers can find themselves without the information they need.

EVALUATING YOUR PERSONAL KNOWLEDGE INFRASTRUCTURE

2. Developing a Personal Knowledge Infrastructure That Points You in the Wrong Direction

A typical problem with personal knowledge infrastructures is that they can be poorly aligned with the demands of the job. For example, if a CEO wants to foster innovation but the infrastructure informs her about operational issues only, the CEO is likely to focus on things that aren’t of primary importance. A personal knowledge infrastructure not only reflects the rules of attention but also shapes those rules. Researchers have highlighted lessons from major spectacular failures from the past, from the Challenger space shuttle disaster to the global financial crisis.10 Many of the managers in question were completely current on the wrong information — or information about the wrong things.

3. Setting Up a Personal Knowledge Infrastructure That Is Not “You”

A manager’s personal knowledge infrastructure can clash with his management style, both in terms of what he does, the tools he uses and the type of manager he would like to be. In our study, we observed a CEO who wanted to be a manager who delegated. However, his personal knowledge infrastructure systematically drove him to focus on details, which led him to take a hands-on approach — against his best intentions. The most effective managers we observed were those who reshaped their personal knowledge infrastructure to fit their work, their management style and what they considered important.

4. Starting With Technology Rather Than Personal Need

Last, some managers make the mistake of addressing the issue from the wrong end — considering technology first rather than later. Rather than being technology-centered, personal knowledge infrastructures need to be geared toward personal development, not toward buying new technologies. Rather than asking, “Is this technology good?,” CEOs should ask, “Will it do any good for me?”

Improving Your Personal Knowledge Infrastructure

So how do managers improve their personal knowledge infrastructures? We found that although CEOs easily recognize the importance of their personal knowledge infrastructure, they very rarely pause to reflect on its effectiveness and fit. More often than not, they discover its inadequacies through comparison with others’ practices or, more commonly, following breakdowns and failures. Developing, refining and testing the effectiveness or present fit of your personal knowledge infrastructure should be routine. (See “How to Improve Your Personal Knowledge Infrastructure.”)

How to Improve Your Personal Knowledge Infrastructure

For CEOs or other executives concerned about improving their personal knowledge infrastructure, we have developed six steps designed to initiate learning and reflection. Examine the following:


There is a great deal that individuals can do for themselves. The starting point is being aware of the composition and functioning of your personal knowledge infrastructure and also being candid about its internal contradictions, potential misfits and misalignments. In our study, we found that this was best done through discussions with others: a mentor, a coach, colleagues or a trusted counselor. After all, your personal knowledge infrastructure is very much a part of you. Having a personal knowledge infrastructure in place is one thing; being honest about how well-suited it is to your particular circumstances is very different.

To this end, in addition to studying CEOs in action, we developed the outlines of a reflection and developmental process one can apply to one’s own circumstances. This is a framework to guide individual and peer reflection, built around a set of questions. (See “Evaluating Your Personal Knowledge Infrastructure”)

Being a manager in today’s complex world requires becoming information-savvy in ways that are manageable and work for you in your specific context. What we learned from the CEOs we studied also applies more broadly to executives in general. Becoming and remaining practically knowledgeable is a critical task. It is a capability that managers need to learn, develop and continually refine, and it becomes increasingly important as the manager moves through his or her career and up the corporate ladder, when the risk of information overload significantly increases.

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