Is Knowledge Dead?

As you know by now, I am keenly interested in — some might say, obsessed with — the fact that value, far from being a static variable, is dynamic — it changes constantly. We must always be testing our value model against the possibility that it is no longer optimal for current market needs.

My Nietszhe-inspired title refers to conversations I had during the past week, independently of each other, with two senior knowledge professionals, each of whom I respect highly. They both offered me their unsolicited opinions that, in effect, “knowledge is dead” insofar as a commercially viable service or product is concerned. They recommended that I pivot my practice away from the construct.

As the originator of “the knowledge agency” as a business model that I have used for over two decades, my attention was piqued. Our tenure covers two recessions (2000-01 and 2008-09) during which Knowledge was declared dead, at least outside the academic world.

So in the short term, the dire predictions were true. In both recessions, knowledge projects were delayed, then cancelled, then people let go, then whole KM departments and initiatives shut down.

However, I am not ready for — nor did I ever seriously consider — abandoning knowledge as an essential tool of business management and strategy. Part of the reason for this is that I realize that value dynamics are complex — and there may be long-term vectors in play that move more “slowly but surely” than immediate commercial concerns.

In researching the latest edition of my much-requested lecture “Metrics: The Language of Value,” I became aware of two significant long-term signals that KM is alive as a value-adding management practice.

The Baldrige Framework

The Baldrige Excellence Framework is used by representatives of the US Commerce Department to judge applicant firms’ “excellence,” as defined in the framework’s criteria. Of the seven major scoring criteria, Information and Knowledge Management (IKM) is one of them. IKM alone is said to be valued at 4.5% of the total excellence score.

Metrics_-_The_Language_of_Value_180201d

I interpret this to mean that 4.5% of the management excellence of an enterprise can be attributed to its management of knowledge. I would extend this to mean that KM budgets, to be on parity, should be 4.5% of total enterprise budgets — a figure that widely exceeds the actual budgets for most of these initiatives.

Even so, this seems curiously low, given that intangible assets (many of which we would characterize as knowledge) are now said to be worth, on average, over 44% of the total enterprise balance sheet — and much more than that, in some industries.

Regardless of which figure you prefer — 4.5%, 44%, or somewhere in between — the conclusion is the same: Knowledge is strategically essential, yet perpetually underfunded as an enterprise resource, relative to the benefits it produces.

ISO 9000

Another major quality scoring system comes from the International Standards Organization (ISO). This system is used by more than 1 million organizations worldwide. The latest ISO standards release includes, for the first time, a section on knowledge management — though it is not assigned a quantitative score.

The ISO 9001:2015 standard (Clause 7.1.6 – Organizational Knowledge) states that KM has three essential roles:

  1. “Determine the knowledge necessary for the operation of [the Organization’s] processes and to achieve conformity of products and services”
  2. Maintain and make available this knowledge “to the extent necessary”
  3. “When addressing changing needs and trends,…consider [the Organization’s] current knowledge and determine or access any necessary additional knowledge and required updates.”

As I read the ISO standard, the essential roles of knowledge strategy are captured in Role 1, the initial determination of knowledge needs, and Role 3, the fulfillment of those needs dynamically as your competitive ecosystem, and your place within it, evolve.   Role 2 represents the tactical ham in the sandwich — maintenance and availability of knowledge.  This is, in my experience, the role that most knowledge managers focus on — often to the exclusion of the other roles — and execute pretty well.

That said, in both Roles 1 and 3 we as a discipline have significant work to do.  Role 1 (knowledge determination) is too often discharged episodically and reactively, rather than systematically and  pre-emptively as it should be.  Likewise, Role 3 (knowledge dynamics) is rarely addressed effectively. Throughout my work I have noted a stickiness and resistance to change within the epistemic resource architecture of many of my larger clients. This posture, while both short-sighted and ultimately self-defeating, is often just a natural byproduct of garden-variety bureaucratic inertia.

Management practice moves slowly. Many of us, for example, are using strategy models that were developed in the last century, long before the internet was a force.

One way to read the relatively recent adoption of KM standards by the Baldrige framework and ISO 9000 is as a positive sign of continued gradual movement in the direction of taking knowledge seriously as a strategic resource.

Knowledge by Numbers

Once again I was called on recently to speak to Columbia graduate students on knowledge metrics, a topic that combines two of my favorite interests — and seems to be a favorite among my audiences.

Metrics form the key to ROI and the production of value — and therefore essential in all aspects of management. Metrics of our own performance, comparable against ourselves and against others, empower us to improve that performance.

Metrics are the language of value

“Financial people” (MBAs and those with equivalent experience) are trained in the understanding and application of metrics to their performance and goals, and are typically as comfortable with talking numbers as they are with speaking words. They think in numbers — and some would say that they even dream in numbers!

Not so “knowledge people.” They may be uncomfortable with, or even resistant to, using numbers rigorously to describe their performance. This can lead to a situation where there is little shared understanding — or even basis for informed discussion — with the financial types who drive most significant enterprise decisions. I call this the knowledge-value gap.

In most organizations, if it comes to a battle between numbers-friendlies and numbers-phobics, the friendlies almost always win. Metrics are literally the language of value and ROI — and therefore the language of most senior management, boards, and external stakeholders.

Knowledge people must learn to “talk numbers” or risk being left out of the most significant strategic conversations in the enterprise — including those involving resource allocations (e.g., budgets, staffing, etc.)

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What is Knowledge Strategy?

As you know if you are a regular visitor here, I teach in a graduate program called Information and Knowledge Strategy at Columbia University. It’s exciting, with many great faculty and talented students — with the added energy that we feel that together we are creating a new field of study.

But what, exactly, is Knowledge Strategy?

A few posts ago I shared my views on the essential distinctions between Information and Knowledge. But what is Knowledge Strategy (KS), as opposed Knowledge Tactics? The skill sets and techniques of knowledge strategists usually include tactical components — building online Communities of Practice, building SharePoint sites, designing and building and curating best practices and lessons learned databases, and so on.

But those are components, not the essence of KS. I’ll offer a working definition: Knowledge Strategy is the practice of developing and deploying enterprise knowledge and its component assets as essential and integral resources in competitive business strategy. KS means, simply, actively recognizing and using knowledge as a strategic resource and a bridge to competitive advantage.

Knowledge strategy and business strategy

Deep_Industry_Strategy_2015-08-29_TWPowell_150902bIn other words, knowledge strategy should not be developed separately from a competitive business strategy.  The two should be developed and implemented in close coordination, as shown in the Strategic Knowledge Architecture diagram at left — and should both respond to the value model defined by the overall purpose and mission of the enterprise.

Professor Michael Zack, in his thoughtful paper “Developing a Knowledge Strategy,” agrees in saying, “the most important context for guiding knowledge management is the firm’s strategy.” (Though this may seem obvious to some, Zack goes on to note the irony that “the link between knowledge management and business strategy, while often talked about, has been widely ignored in practice.”)

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Seed and Soil

Siddhartha Mukerjee, the brilliant Columbia oncologist and Pulitzer-winning writer, has struck again. In a recent New Yorker magazine (September 11), his article “The Invasion Equation” describes a striking leap of insight that could transform cancer research. This insight, called “seed and soil,” brings ecological or systems thinking to studies of cancer research — and could equally be applied to management interventions.

Mukerjee is, as always, dazzling in the depth of his historical knowledge that brings us to any given point. A key issue in cancer treatment is whether any given cancer will stay in place — and be treatable there by surgery and/or chemotherapy — or whether it will metastasize into cancers in other parts of the body. It turns out that this has less to do with the nature of the cancer itself, and more with the nature of the host tissue. The fundamental research question Mukerjee addresses is, “Why do cancers spread more often to certain parts of the body than to others?”

What determines cancer’s journey?

Mukerjee traces his work back to that of a 19th-century doctor Stephen Paget, who noticed that cancers spread more often, for example, to the liver than to the spleen, in spite of the many similarities of these two organs. The characteristics of the cancer cells, in other words, play only part of the role. It is also something about the tissue that plays “host” to the tumor that makes metastasis more or less likely.Seed and Soil

Paget termed this “seed and soil,” a concept that will be resonant with those who have studied ecology or systems thinking. Mukerjee claims that this is coming back as an avenue of inquiry after lying largely dormant for the past century.

Mukerjee displays leaps of insight that would delight any creative artist.  He goes on to show how the seed and soil metaphor applies to other areas of biology — the overbreeding of mollusk populations in the Great Lakes, for example.

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Columbia IKNS Residency – August 2017

As a faculty member of Columbia University’s Information and Knowledge Strategy (IKNS) program, I have a variety of duties and responsibilities. One of these is to actively participate in the “residencies,” a twice-yearly physical coming together of the students — many of whom live and work outside New York City, and some of whom are outside the United States.  (See the great 2017 cohort below.)IKNS 2017 Cohort

It’s always exhausting, due to the string of 16-hour days and the need, as a faculty member, to always be “on” for advising students. My job consists primarily of counseling student teams who are working on live consulting projects within sponsoring organizations, many of which are large and complex — NASA and the United Nations, for example.

“Year of the KVC”

This cycle was especially challenging — and rewarding — as the students had clearly embraced the Knowledge Value Chain model to an extent that had not happened in previous cohorts of the program. This was not only hugely gratifying to me, it was a substantive assist to my work. As students engaged the model on behalf of their clients, many of them also engaged my help in determining how the model could benefit their clients.

While the students were respectful of my time, and even apologetic in some cases, I pointed out that this is how the KVC model grew in the first place — with input from clients and interested friends. And that is how it will continue to grow in the future — so I regard no question or application as off-topic or non-fruitful. It’s all good!

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What is the Difference Between Information and Knowledge?

In my KVC Handbook v. 4, I draw a clear distinction between knowledge and information — essentially that knowledge is a more “processed” version of information. In speaking with people I find that this difference is still not totally understood — so will amplify here.

The short version

Simply put, the distinction is this: information is essentially inanimate — organized data that has been captured in databases, papers, books, news articles. Information is essentially mediated — by definition it exists only as embedded in a medium like those mentioned.

Info_vs_knowledgeKnowledge, on the other hand, is essentially organic, and more specifically, human. What we mean when we talk about knowledge is invariably embedded in an animate being. (I’ll allow that this definition could recognize that animals have knowledge — but until such time as they can write or talk understandably to us about it, I’m willing to let that line of speculation go.)

A book on the shelf is information — until a person reads it, understands it, and absorbs it. Then (and only then) it has been converted into that person’s knowledge. (When the person subsequently socializes that knowledge and applies it to make decisions and/or take actions, then it has become intelligence. But that’s a discussion for another time.)

But what about “explicit knowledge”?

There are those who speak of tacit knowledge — implying that there are also varieties of knowledge that are non-tacit, i.e., explicit knowledge. The scientist-philosopher Michael Polanyi is said to have first coined this distinction in the late 1950s, which has become widely-accepted, even canonical, in the Knowledge Management establishment. In 1995, Nonaka and Takeushi developed a model (“SECI”) for how individual tacit knowledge is converted into explicit knowledge, then socialized within the enterprise.

We think a wrong turn was taken. The KVC framework finds “explicit knowledge” a contradiction in terms; we define all knowledge as quintessentially tacit. Knowledge that has been mediated — by speaking it, writing it, entering it into a database, etc. — is what we identify as, by definition, information.

We fully agree with most experts — and this was Polanyi’s original driving insight — that “we know more than we can speak.” Indeed, we find this a titanic understatement. It is a mere fraction of what we know that we can capture in its mediated form  as information. Read the rest of this entry »

Building Knowledge Value in Practice

My basic work and message have been steadfast for a couple of decades: helping companies use information and knowledge more effectively in the service of functioning and competing more effectively.

However, I find that the way I express this core message varies based on the level of sophistication of my audience and on the level of the opportunity it represents.

In speaking recently with students at Columbia University’s innovative Information and Knowledge Strategy program, I used a technique recommended by many successful speakers — distilling a complex message down to core “principles of practice” that can be readily applied.  I’ll briefly describe below what those are.

The inspiration for my talk started one year prior, when Larry Prusak had spoken to a previous group of students, and observed that, “We have to figure out how to SELL this knowledge stuff.” Larry is a pioneer in the knowledge field and has a knack for knowing — and saying — what is really happening. So his words resonated deeply with me, and I vowed to use my training in business strategy to help these students “sell” their work.

To me, selling anything is primarily about getting the potential buyer to recognize the value of what you are selling — after that, the stuff sells itself. I believe this insight applies not only to knowledge but to all B2B sales — and B2C too.

Knowledge producers and practitioners, though often acting as internal staff resources rather than outside agencies, still must “sell” their work and its value. When they do not understand this, or know how it applies to their work, their contribution is undervalued, their careers can suffer, and so on. It’s not a happy situation.Key_Principles

I believe that the key to escaping this low-value loop is to understand and practice these six principles: Read the rest of this entry »

Positioning Knowledge for Value

The early-winter holiday break is an opportunity to recharge our batteries and refocus our strategies. Amidst visiting with family and friends, I took time to reflect on the recent past and what the future holds.

Among other things, I realized that over time my clients have been paying more attention to the top half of the Knowledge Value Chain (how knowledge is used) and less about the bottom half (how knowledge is produced.)

What drives knowledge strategy?

Ideally, knowledge strategies spring from, and are tightly linked to, top-level enterprise strategies. In practice, however, many of the problems in knowledge production spring from misunderstandings of, or lack of clear linkages to, enterprise value.  Some of my research on this is cited in the KVC Handbook.  This knowledge-value gap raises several existential questions about knowledge-centric activities, among them:

  • How does knowledge support our enterprise mission and strategies?
  • What tangible benefits does knowledge provide us?
  • Is our knowledge strategy optimized in an economic sense?

Any lack of clarity at the top of the pyramid tends to get driven down through the chain, where it causes tactical and executional confusion and ineffectiveness.  Those of you in the trenches will know what I mean…

Benefits-driven positioning

If you are a knowledge producer, do not wait for those problems at the top to get sorted out — seize the initiative yourself!

We’ve been advising our clients: Always position your product (and I use this term to include services) from the point of view of the needs of, and benefits to, your user/customer/client/patron. Not — as so many of us do instinctively — from how your product works, why it is wonderful, or even why it’s better than your rivals’.  The diagram below summarizes TKA’s discovery process for working with clients on this. Read the rest of this entry »

Busy Season

I hope each of you is enjoying this new year — whenever it is that you celebrate its beginning.

For me, 2017 is already full of new beginnings and revelations.  To recap:

Launch of KVC Clinic v.2.0

In the fall of 2016, we launched an expanded version of our KVC Clinic. KVC Clinic elementsThis includes three days of on-site work with each intelligence or knowledge services group, as well as depth interviews with internal clients. It’s a hybrid event incorporating experiential team learning, organizational diagnosis, and customer research.

We received enthusiastic engagement from our initial host team, and were able to quickly develop a solid set of recommendations going forward. We are delighted that this client has added the KVC as a major 2017 initiative in their knowledge services program. Read the rest of this entry »

Bad Night for Big Data

I have a nightmarish pet scenario that as we as a society gain non-stop access to ever-increasing data, there is a risk that we actually get progressively dumber — as we lose the ability to process and analysis that data sufficiently.

My idea got a workout this week during election night when the polling industry, most of whom had predicted a single or even double percentage point Clinton victory, got it monumentally wrong.

When we hear on TV every ten minutes about how Watson is curing cancer, among other breathless hype about Big Data, an error of this stunning magnitude seems at first paradoxical.

But the more you think about it, the more it makes a perverse kind of sense.

“Dewey Defeats Truman”

Embarrassing election errors are nothing new — witness the iconic photo of President-elect Truman gleefully displaying the newspaper headline “Dewey Defeats Truman” the day after the 1948 election.dewey-defeats-truman

People claimed then that the error was due to a combination of slow reporting and the print-era need to prepare headlines hours in advance of publication.

What IS new is that polls are now easier and cheaper to field, and as a natural consequence there is a proliferation of them. And, as they are invariably deemed newsworthy, they feed the hungry news-cycle monster. They generate eyeballs and click-bait — and they’re fun, especially when your own pick is ahead.

Especially toward the close of this 18-month campaign, it seemed like a new poll was appearing every other day. We became so collectively absorbed in the twitching poll dashboards that we neglected the fleeting opportunity to discuss in any depth the serious challenges facing our country and our society.

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