The Concept and Importance of Knowledge Supply Chains

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The late 20th century was a period of major social, economic, and political changes. It was also a time of explosive growth in information technology – in how people store, access, and process information. This period is now widely known as the beginning of the Information Age, a term made to distinguish it from the Industrial Age. Experts agree that the onset of the industrial revolution was the most important event in the history of humanity since the domestication of animals and farming. Similarly, the information revolution has had a tremendous impact on every aspect of our life and it has already earned its own place in human history.

A distinguishing characteristic of the information age is the increasing importance of knowledge. Knowledge is increasingly the main source of economic growth, more important than land, labor, capital, or other physical resources. Peter Drucker introduced the term “knowledge worker” in 1969 (The Age of Discontinuity: Guidelines to Our Changing Society. William Heinemann Ltd.), and later suggested that “the most valuable asset of a 21st-century institution, whether business or non-business, will be its knowledge workers and their productivity.” (Management Challenges for the 21st Century. Harper Collins. 1999)

According to Savage, in the agricultural age, wealth was determined by the ownership and cultivation of land. In the industrial age, wealth was based on ownership of capital. In the information age, wealth is based upon the ownership and successful application of knowledge – Fifth Generation Management: Co-creating through Virtual Enterprising, Dynamic Teaming and Knowledge Networking. Boston: Butterworth-Heinemann.

The term “knowledge” can be defined in many ways. Here, I will define knowledge as “actionable information”, that is, information with clear meaning, beneficial purpose, and preferably a high ROI.

Arguably, the information age can be divided into two major eras. The first is what we can call the digitization era. During this time, major advances were made related to our ability to store, access, and process information in digital (versus analog) form. This era begun with the invention of the transistor and progress continued unabated till the advent of the Internet and the development of online social networks. Up to that point, the electronic devices were helping us express, capture, store, share, access, and process information in raw form.

We are now entering the second era of the information age that we can call the knowledge era. For many enterprises today, the creation, maintenance, and use of knowledge representations are essential elements to success. For example, the knowledge graphs used by Microsoft’s Bing and Google’s Search services define descriptions and connections of people, locations, and organizations. They capture general knowledge about the world because these services cater to the information needs of every person with access to the Internet. Similarly, Facebook has the world’s largest social graph, which apart from connecting you to your friends it also connects artists to songs, actors to movies, people to locations, and everything else that could be beneficial to Facebook’s users or its advertisers.

It should be noted that the most valuable knowledge may not be directly encoded in the data that we collect or acquire but it is to be sought in the connections that can be made between different pieces of information, or “facts” (which are encoded directly in the data), and the inferences that can be made based on these data.

It is also important to point out that the classification scheme that I propose is primarily motivated by economic considerations rather than any technological considerations. During the industrial age, the ability to produce tangible goods in larger amounts, with minimum manual intervention, and at a higher speed was the impetus of adopting the new advances in technology and creating competitive advantage. Similarly, during the digitization era, the ability to capture, store, access, and process information at higher volumes than ever before and at lower costs than ever before has been creating competitive advantage over the past few decades. However, today, nearly everyone has embraced the digitization era. The ability to accomplish digitization is readily available to anyone whether through robust cloud infrastructures and services or other means. In other words, the tools of digitization have been commoditized, while effective and robust practices for digitization have been developed to cover nearly every business need.

Embracing digitization today does not create a competitive advantage. The competition has moved into the identification and maximum utilization of knowledge. An advantage in the market can be obtained if you know something that others do not or if you know it faster than they do – the financial markets is the ultimate arena of that competition, of course. Everyone has data, everyone can access data, and everyone can process data. The market value of all these data is directly related to the extent that they can be used to alter business outcomes, not our ability to store them, access them, or process them. Which begs the question: how can an organization make the best use of available data and thereby maximize the utilization of knowledge for its benefit?

I believe that the answer can be found by drawing an analogy between the processes and means of production for physical (tangible) goods, on one hand, and the processes and means of production for knowledge, on the other hand. In the past thirty years or so, nearly every large corporation has benefited tremendously by advances in the field of supply chain management. Supply chains are large networks that encompass all development stages of a product; theoretically, this covers everything involved in the transformation from raw materials to a completed customer deliverable unit, including the transitions between stages and all information flows across the network. Examples of successfully managing the supply chain, and the impact that it can have to the company’s bottom line, abound. From Siemens CT (maker of computed tomography X-ray machines) to Gillette, and from Apple’s recovery in 1997 to Amazon’s seemingly endless commercial triumphs. There is nothing analogous to these successes for the production of knowledge. There isn’t even a conceptual framework to provide guidance.

I firmly believe that introducing the concept of knowledge supply chains (KSC) and thinking about the production of knowledge in those terms can lead to significant advantages for many knowledge intensive organizations. Besides the obvious benefits of streamlining and optimizing the collection and the procurement of data, there are lessons learned in the domain of the manufacturing supply chains that seem to be applicable in the production of knowledge.

Many manufacturing companies realized early on that there were problems in their supply chains, but they couldn’t really understand the problems, let alone figuring out the best way to fix them. Although there are many reasons for failing to meet operational goals, it turns out that quite often the root cause seemed to be the lack of ownership. None in the company was responsible for running the supply chain. Now, if you work in a knowledge intensive organization, ask yourself the following question: Who in your organization is responsible for the production of knowledge across the company?

There are people with roles responsible for the sourcing of information and knowledge management but, in most cases, these individuals do not have the authority to coordinate key activities that take place in different groups with different agendas and possibly conflicting goals. If the analogy is of any guidance, the worse case scenario is having multiple independent groups going all the way up to the CEO, who is not the right person to run your knowledge supply chain – much like any manufacturing CEO would not be the right person to plan and operate the manufacturing supply chain. Another lesson would be that teamwork is required to obtain best results. Cross-functional teams are a recurring theme in companies that run good supply chains.

Here are a few more reasons that one should bother thinking in those terms:

  • If you feel that, in your organization, information management (and implicitly knowledge management) is treated as a cost center rather than a profit center then the concept of KSC may help you position information management as a source of strategic advantage rather than a necessary nuisance.
  • Sometimes managers, whether in IT or any other department, place an excessive amount of emphasis on technology itself (e.g. this deep learning technology or that blockchain technology, or whatever the hype du jour happens to be) and that shifts the focus from the careful thinking and design of a solution to a business problem to the technology itself.
  • Data are very important, and the quality of data is paramount for being successful in the knowledge era, but cultural shifts, business processes, and adjustments in operations must also be well thought and accounted for in the overall ROI evaluation.
  • R&D heavy organizations rely increasingly on a broad and diverse network of external relationships to foster innovation. Organizing entire business processes throughout a value chain of multiple companies is a key benefit of thinking about these networks in terms of a supply chain.

I can think of many other reasons that would make the concept of KSC important to any organization in the knowledge era. In subsequent blogs, I will describe the essential elements of a KSC, meanwhile, I welcome your feedback on these initial thoughts.

 

 

RightFind® Navigate makes it possible to unify data sources within an open integration ecosystem and equip researchers with contextualized discovery so they can find the right information at the right time. That means different types of content – such as scientific literature, patents, internal documents and presentations, and market reports – are all available to search and access in one place.

If you’d like to learn more, check out:

Babis Marmanis

Author: Babis Marmanis

Babis Marmanis, Ph.D., is responsible for defining the technology vision of all software systems at CCC. He leads a global team of professionals with a passion for continuous technological innovation and the delivery of high-quality software systems. Babis has written the books Spend Analysis and Algorithms of the Intelligent Web, and contributes to journals, conferences and technical magazines.

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