Lucidea’s Lens: Knowledge Management Thought Leaders
Part 110 – Tom Stewart

Tom Stewart is a strategist, senior executive, and one of the thinkers who discovered and developed the concepts of knowledge-based businesses, and the role of intellectual capital and thought leadership in strategy. He is an experienced research center leader, book author, business journalist, publishing executive, and C-suite marketing and knowledge management leader. 

Tom held positions as the Editor-in-Chief of the Harvard Business Review, Chief Marketing & Knowledge Officer of Booz & Company, and Executive Director of the National Center for the Middle Market. Previously, he had senior roles at Fortune and in book publishing. 

Here are definitions for five of Tom’s specialties: 

• Content Management: Creating, managing, distributing, publishing, and retrieving structured information–the complete lifecycle of content as it moves through an organization. 
• Digital Transformation: The cultural, organizational, and operational change of an organization, industry, or ecosystem through a smart integration of digital technologies, processes, and competencies across all levels and functions in a staged and strategic way. 
• Innovation: The process by which an idea is translated into a good or service for which people will pay. 
• Intellectual Capital: The sum of everything everybody in a company knows that gives it a competitive edge. A metric for the value of intellectual capital is the amount by which the enterprise value of a firm exceeds the value of its tangible (physical and financial) assets. It includes human, structural, and relational capital. 
• Strategy: A set of guiding principles that, when communicated and adopted in the organization, generates a desired pattern of decision making. The way that people throughout the organization should make decisions and allocate resources to accomplish key objectives. A strategy provides a clear roadmap that defines the actions people should take (and not take) and the things they should prioritize (and not prioritize) to achieve desired goals. 

Tom created the following content. I have curated it to represent his contributions to the field. 

Books by Tom Stewart 

Excerpt from Intellectual Capital, Preface to the Paperback Edition 

Too much of what passes for knowledge management is just glorified data processing.  On page 71 of this book, I briefly distinguish between intellectual capital and intellectual working capital.  This distinction was a new idea to me–it came to me while I was working on the proofs of the book.  In the past eighteen months, I’ve come to think it’s a valuable distinction, and especially important to keep in mind as knowledge management becomes the rage.  Intellectual working capital is workaday information–the flow or torrent of data, facts, meter readings, and so forth.  Of this stuff, I wrote, “A worker might need precise, up-to-date information at any given moment, but not necessarily at this moment.  What he does need, at every moment, is a way to get the data he might need at any moment.”  

Implicit in those somewhat knotty sentences is a truth that might be lost in some corporations’ full-throttle rush to “do” knowledge management.  Intellectual working capital should not be managed the same way as intellectual capital.  It wants different aims, different measurements, and possibly different means.  These pieces of information are to the New Economy what inventory and receivables are to the Old Economy.  Working capital is a Bad Thing.  It is a cost to be minimized, not an asset whose value should be increased.  It is not to be stored but to be kept moving.  Intellectual working capital is a through-put, cycle-time, inventory-management problem. 

Knowledge management advocates correctly decry the wastefulness of constantly “reinventing the wheel”; one way to do that is to create a digital warehouse in which is stored every wheel anyone has ever invented.  But that dream–the dream of a corporate master file, an encyclopedia where every needed fact, every policy, every conceivably valuable piece of knowledge can be found with just a few clicks of the mouse–is both impractical and wrong.  Impractical because technology and markets are changing so quickly that it would be impossible to possibly create such an omnium-gatherum of corporate brainpower, unless one is willing to spend such enormous amounts of money setting up and maintaining the encyclopedia that it will not be worth the effort.  Wrong because that’s not the right way to do warehousing–unless your company’s value proposition is to be a storehouse for knowledge, as a silo is for grain.  One wants the smallest possible warehouse, which stocks only what’s otherwise hard to get in a timely way.  Knowledge management and knowledge databases should really be about linking people to people to serve customers, people needing expertise with people who have expertise.  They should be about connection, not collection. 

I see a second mistake being made by advocates of knowledge management.  Too often they focus inside companies.  Much of knowledge management has been an inside job, automating and animating the files.  It’s hyperlinked, hypersonic librarianship.  Too little is about serving customers.  Consultant Stan Davis points out that business people frequently confuse an organization with a business. Organizations are defined from the inside out: They are described by who reports to whom, by departments and processes and matrices and perks.  A business, on the other hand, is defined from the outside in, by markets, suppliers, customers, and competitors. 

There is money to be saved by improving knowledge management in the organization.  But there is money to be made by managing the knowledge of the business.  What is the knowledge customers are paying for? Real customers–not phony “internal customers” but people with money in their hands? It’s their money that is important, not the money the budget committee has allocated to knowledge management.  

Excerpt from The Wealth of Knowledge, Chapter 1: The Pillars of the Knowledge Economy 

The knowledge economy stands on three pillars. The first: Knowledge has become what we buy, sell, and do. It is the most important factor of production. The second pillar is a mate, a corollary to the first: Knowledge assets–that is, intellectual capital–have become more important to companies than financial and physical assets. The third pillar is this: To prosper in this new economy and exploit these newly vital assets, we need new vocabularies, new management techniques, new technologies, and new strategies. On these three pillars rest all the new economy’s laws and its profits.  

Knowledge is what we buy, sell, and do.  

It has become traditional in books about knowledge and knowledge management to spend several pages defining knowledge and distinguishing it from data, information, and sometimes wisdom. I feel no need to inflict any such rumination on you, dear reader; dictionaries and common usage are good enough. But it is–I have always maintained–important to make a distinction between data and information, on the one hand, and knowledge, on the other.  

Data and information are smaller than knowledge and, if it exists, wisdom. They are also different in kind. In computerese, eight bits equal one byte. But eight–or zubleteen zillion–bits of information do not equal a byte of knowledge. Knowledge is not a sum but a summation, a relation. Data and information plug into knowledge: They are tiles in a mosaic, but they are not its design. Bits of data and information–facts, factoids–can be startling or telling or important, but they’re not like knowledge. 

Knowledge involves expertise. Achieving it involves time. It endures longer than information–sometimes forever. To be knowledgeable, to know a subject, is something different from and greater than knowing a fact or possessing a lot of information about something.  

It is impossible, however, to make a clear distinction between information and knowledge that works for a very large group. This is because one man’s data can be another man’s knowledge, and vice versa, depending on context. Your deep expertise in accounting, metallurgy, or literature may be an interesting tidbit to the person you sit next to at dinner tonight. Therefore what’s information and what’s knowledge depends on context. 

If this were a study of epistemology or information theory, we might want more precise definitions, but it’s not and we don’t.

The Intellectual Capital Model