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 are 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, 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 so many 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.)

Seven steps to improving Knowledge ROI

How do you bridge this knowledge-value gap that lurks, eroding value in so many organizations? What is the roadmap?  I ended the session by sharing with the audience these steps that will speed them on their journey toward metrics-literacy and knowledge ROI:

1. Understand the enterprise value system.  What does your client organization measure and reward? Each organization has its own purpose and mission, enterprise metrics, KPIs, and so on. Start by understanding how the organization thinks and communicates about value, both internally and externally.
2. Link knowledge metrics directly to these existing enterprise metrics. This linkage is the primary source of strength and ROI for a knowledge initiative.  Knowledge goals and metrics become less relevant the farther they are from organizational goals and metrics.
3. Identify behaviors you are trying to produce, optimize, or change. Metrics work — because they drive behavior within the organization. Which behaviors are working in achieving desired enterprise outcomes, and which need to improve?
4. Measure what matters.  Develop metrics for those behaviors in a way that is most effective for the benefits (i.e., Results, Outcomes, and Impact) you are trying to achieve. This requires a deep understanding of cause and effect.
5. Bend the value curve. Engage available value levers to drive benefits up, and costs down. This point gets a little involved, I’ll explain this in a separate post.
6. Monitor and anticipate. With each metric comes the risk that people will “work to the metric” — and not to what really produces value. Once operational, metrics should be assessed periodically to insure they are producing the desired outcomes.
7. Add value continually. Adding value is not a one-time event — it’s an ongoing process driven by a deep underlying commitment to thought leadership.

We wish you, all our readers and supporters, the happiest of holidays — with our best wishes for success and fulfillment in the coming year.

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 deploying enterprise knowledge and its assets as essential resources in competitive business strategy. KS means, simply, actively recognizing and using knowledge as a strategic resource.

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.”)

Read the rest of this entry »

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.

Read the rest of this entry »

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.

Read the rest of this entry »

Value Gets Lost

“I’m stuck at the bottom of the pyramid.” “My value is unclear to people who matter.” “I’m invisible.”

In conducting “Points of Pain” exercises during TKA’s workshops and on-site clinics, too often we hear things like this from competent and hard-working knowledge producers. In study after study, roughly half of the challenges expressed by PRODUCERS of organizational knowledge or intelligence involve questions or concerns about the value they generate.

More often than not, the questions are not about producing value per se — usually producers are pretty clear and confident about that. The major gap is that their client USERS do not understand this value — and that therefore they have trouble attributing the value of knowledge back to those who originally produced it.

Our output is their input

In economic terms, any knowledge or intelligence work product, while typically the OUTPUT or end product of a knowledge or intelligence process, is subsequently the INPUT or raw material for a client’s work stream. Knowledge users take over where knowledge producers leave off — that’s one of the fundamental lessons of the KVC framework. During the handoff — the Communication step — the knowledge work product is transformed into intelligence — the basis for decisions, actions, and the production of “enterprise value” (for example, a product that brings revenues into a business).

A KVC Clinic client recently pointed out to us that the KVC triangle graphic makes it appear as if value is only produced by people and processes at the top. This was a fundamental misunderstanding of the model — for which (of course) I take full responsibility.  And hereby try to correct, please read on…

Triangle and trapezoid

The Enterprise Value (EV) Triangle

The Enterprise Value (EV) Triangle

What we mean by the word Value in the “little triangle” at the top of the KVC triangle is more properly specified as “Enterprise Value” (EV). Value is produced at each one of the seven steps in the KVC process (see the KVC Handbook p. 54). But value is only realized — i.e., made manifest and measurable in terms of revenues or other organizational outcomes or results — at the top.

Using one of my favorite analogies, the people who pick the grapes ultimately get paid by the people who buy the wine — but there is a value chain of activities that separate these two economic events in time and space.

The Knowledge Value (KV) Trapezoid

The Knowledge Value (KV) Trapezoid

With knowledge services, the problem is that the production of “Knowledge Value” (KV) — what another client called “the trapezoid” below Communication — is often separated from the production of EV, in two respects: (1) separated in time, and (2) separated in organizational location.

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