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.)

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.  Note that aspects of this will be verticalized, i.e., specific to the client’s industry.
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 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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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 »

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 »

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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The Knowledge Payout

Knowledge Management would be better off as a discipline if it leaned into the management side more, and relied a little less exclusively on the knowledge side. It’s possible to read articles or even whole books on KM and find little discussion specifying the knowledge that people use, specifically how they use it in producing value, and/or what it costs.

Productive knowledge is transitive and transactional; it is necessarily “about” something.  That something is the work that knowledge users do in producing value in the process of doing their jobs.

This reminds me of my college physics classes, where they would start discussions by positing, “Assume there is no gravity and no friction.”  This is because many basic models in mechanics work best under these idealized conditions.  But in the real world, where (regrettably) we all have to deal with both gravity and friction — the models need substantial modification before they adequately describe how things actually work.

I kept my previous post, The Research Matrix, blissfully free of such real-world considerations.  Intentionally so, since the principles of “knowledge science” — like those of physics — admittedly work best without them.

The value context

In reality, knowledge exists only in a value context — it provides benefits, but also incurs costs.  “Value” is simply the ratio of benefits to costs.  My intention here is to add that context to my previous post, and to offer you a systematic framework with which to assess knowledge benefits and costs.Value =

As our B2 list (“Nice to Know” items) grows, we still want to move things from Column B (What We Don’t Know) to Column A (What We Know) — but, in considering costs, we will surely need to make tradeoffs.  Life could be a dream if time and budgets were in infinite supply, but they are not.  So we need a “value of knowledge” payout table that considers the benefit (to solving our problem) and the cost of each “unit” of knowledge. This will enable us to create knowledge priorities driving a research agenda — essential in our world of all-too-finite resources.

“Cost versus value” is a theme I develop in the KVC Handbook (p. 40). At its most basic, it says that while the marginal COST of a given unit of knowledge is (more or less) fixed, its marginal BENEFIT is contextual based on the knowledge already possessed by the user.  Marginal benefit typically decreases over time spent in a research process, because you are adding progressively less to what you already know.

We can relate benefit and cost to each other by means of a KNOWLEDGE BENEFIT/COST RATIO (KBCR) — the “bang for your knowledge buck,” and functionally equivalent to our knowledge value or ROI.  KBCR is the function that we are seeking to maximize.

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The Research Matrix

The other day I received an email from “Susan”, an alumna of the Columbia IKNS program whom I had the good fortune to work with as one of my students there. Susan’s question to me was on research, which that program touches upon but doesn’t cover in great depth, and in which I have lots of experience.

Susan’s client is exploring the feasibility of entering a new industrial services market related to energy.  Susan was looking to me for guidance about how to structure and price her research proposal to them.  For my purposes here, it doesn’t matter what the industry is — though I can say it’s B2B, and not one of those industries (like technology or health care) that is often in the news.

The value question

I prefer to demystify things wherever possible, so I proposed that Susan start by determining the client’s value question: What do they want to find out, and why (i.e., what do they plan to do with the answer)?  Susan had studied the KVC model at Columbia, so she knows how value is created from knowledge by making decisions and taking actions based on that knowledge — and that Planning (“Step 0”) starts at the top.

Columns A and B

Then I went into TV detective mode. Working down the chain:  what do we know, and what do we want to know?  We essentially have two columns, A for what we know, B for what we don’t know.  A is essentially our “value-relevant knowledge inventory”, and B is our “open to buy” knowledge purchase order.

Our mission

Simply put, our mission is to move things systematically from Column B to Column A.  That’s the essence of the research agenda, represented in the diagram by the orange arrow.

Except that it’s not often that simple.  (Bet you could see that coming.)  Knowledge users/clients are people, and people are essentially and eternally curious.  So Column B starts life as a set of Minimally Required Knowledge (MRK) to solve our business problem — our “need to know” items.  (Philosophers call this paring-down approach Occam’s Razor.)

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Meetings Will Make You — or Break You

Most of us work in virtual meetings often, some of us almost exclusively.  People call in using Google Hangouts, Skype, GoToMeeting, WebEx, JoinMe, Free Conference, and so on.  (I’m speaking here of “virtual meetings for the rest of us,” not the high-end meeting rooms costing hundreds of thousands.)

The hybrid meeting

I’ve been part of and/or hosted lots of physical meetings, and lots of online meetings.  In a meeting I hosted the other day, I encountered a variation — the digital-analog hybrid, where some of the people are remote and some are in the room.  (I’m in New York City, where everybody passes through at one time or another.)

It’s amazing what happens around the table that people on the phone do not have access to.  Off-mic side comments, glances, smiles, tones of voice — a panoply of meta-meaning that provides richness and context, and that only those physically in the room benefit from.

This led to a misunderstanding with one of my three co-presenting colleagues who was not present in the room.  I should mention that presence or absence had nothing to do with how important each person was to the meeting, nor how important the meeting was to each of them.  It was based simply on their availability to come to NYC at that time.  (Some were connected from as far away as Europe.)

The problem

For my purpose here, it’s not so important what exactly transpired.  Let’s just say it was a miscue deriving from an agenda item that was modified at show-time by consensus of those physically around the table — but not made clear — and here’s where as meeting leader I fell short — to those calling in. In other words, it was a problem enabled by the hybrid nature of the meeting.

What I’d like to share with you — because many of you may experience this too, with regard to meetings, or other conflicts with peers — is how we resolved it.

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