We’re pleased to announce the publication of the latest Version (4.0) of our Knowledge Value Chain Handbook. Here’s an excerpt (with added emphasis) from the Introduction.
Knowledge is a fundamental resource of our economic lives. If you were going to enter the business of, say, manufacturing airplanes, you would want to hire people with substantial applied expertise in the sciences of metallurgy, electronics, and even polymers—all the basic building blocks of your product.
Most of us work and compete in what is widely acknowledged to be a knowledge-based economy. But we do not have a science of knowledge—because there isn’t one yet. Philosophy has a branch called epistemology that discusses the origins and characteristics of human knowledge—but that doesn’t qualify as a science in the sense that technologies and management practices can be consistently derived from its principles.
Even the basic economics of knowledge are open to study and debate. Classical economists like Adam Smith generally did not regard knowledge as a key economic component. The fundamental “factors of production” were land, labor, and capital—with knowledge and information barely mentioned as being essential to production.
Modern economists have begun to recognize knowledge as the fourth factor of production, and have gathered some insights into how it behaves. Fritz Machlup of Princeton University was one of the first to measure the knowledge macro-economy in 1962. By 1968, Peter Drucker described the knowledge worker’s central role in creating productivity and competitiveness. Kenneth Arrow (and subsequent financial economists) worked on knowledge-related issues such as asymmetries of information in financial markets.
But these findings, however interesting, have limited applicability in a typical business setting. This is partly because the measurement of knowledge as an economic asset is at best inexact. Current financial accounting addresses knowledge only indirectly—as intellectual property assets and/or good will.
Organizational leaders sense that knowledge is important as a strategic resource, yet we don’t know how to measure or manage it—or how to discuss it at more than a basic level.
As Big Data becomes more common practice in many industries, people are concerned about data overload and about making sure the right information gets analyzed. These problems—common to nearly all organizations, large and small—are only getting worse, and soon will be of urgent concern at the highest levels of leadership.
We believe that Big Data, as promising as it is, can fail to the extent it neglects the key first step in the cycle Plan-Produce-Present. By collecting data without prior regard to the need for hypothesis testing or any other value-down structure, it can create a data-up mentality that challenges the limits of the analytic and sense-making resources of the enterprise.
Big Data tempts us to look through the wrong end of the telescope. By looking up from the data end, things can seem unnecessarily confusing—even overwhelming. Viewing things value-down helps avoid most data overload problems.
The KVC framework is easy to understand and apply because it builds on a simple insight: in a complex organization, the people who produce information (producers) are fundamentally different from the people who use it to create results and value (users). This creates a knowledge-value gap between producers and users that is often vast—some call it a “gulf”—and includes many professional and cultural barriers.
In short, information people don’t typically understand the language of business, and business people don’t typically understand the language of information. The connection between the two halves—the knowledge value chain—is broken.
The net result is that information resources and the people who manage them fail to have the impact they could have, and fail to optimize their return on investment. Instead of being part of the organizational solution, information becomes part of the problem as people scurry to absorb and try to make sense of it all.
Understanding the knowledge value chain from both producer and user perspectives is a first step toward bridging this fundamental barrier.
The rest of the book goes on to tell you how to do this. If you found this excerpt useful, order a full electronic copy of the Handbook here. Your order will help us produce more research and training materials.
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