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Extracting value

Do accountants and managers charged with controlling costs get more time to make good on their debts?

In the United States, the most interesting cost challenge I encountered is the Thomson’s love affair with Next. In terms of knowledge management, Next was an initiative to create a “digital news hub.” (See niemanlab.org/2013/09/reuters-nixes-next-failed-redesigns-and-the-challenge-of-expanding-a-digital-audience.)

According to the Nieman Lab analysis: “Reuters Next was conceived as a complete overhaul of Reuters.com as well as the backend systems that deliver news and updates from journalists and editors around the globe. In May, the company unveiled a preview version of the new site, a unified design that merged article pages and topic pages, where every story could act as a jumping off point in a constantly updating river of news.”

The cost of Next almost a year after the shutdown is not public knowledge. The Nieman Lab research highlights barriers that have tripped up other information-centric companies. Thomson Reuters wrestled with disparate content types and retired without a victory. Staff and management churn added friction to the effort. In short, one of the largest and most capable information companies had to reverse course. Instead of pumping up Thomson Reuters’ revenues and profit with a next-generation system, the highly regarded company stumbled.

What are the steps an organization can take to reduce the costs and risks of extracting value from digital information? I ran a series of queries on Bing and Google and scanned some of the considerable output those systems generated. I tallied the reasons scholars, journalists and analysts identified. The results were surprising only in their consistency and repetitiveness. Based on my research, the top three reasons knowledge management projects experience cost overruns are:

  • management,
  • changes to specifications, and
  • technical problems.

“Circular knowledge”

The generality of those points is itself important. The fuzziness associated with the concepts “content,” “digital information,” “big data,” etc., make it difficult to nail down what a system will do, can do or should do. Bucharest Academy of Economic Studies’ analysts Daniela Hincu and Luban Florica offered a fresh view of the challenge. In “On Some Issues about Knowledge Management System Implementation,” they wrote, “The ultimate goal of knowledge management is to facilitate circular knowledge of instrumental knowledge to codified knowledge.” (See http://gandalf.fcee.urv.es/sigef/english/congressos/congres15/036_Hincu%20-%20Luban.pdf.)

The phrase “circular knowledge” is pregnant with implications. On the surface, the concept suggests that institutional knowledge is recursive. The company and its staff encounter a situation, find that existing information does not provide an answer. The organization charts a course and that information expands the tacit and implicit knowledge. In short, the phrase nicely hooks a human’s learning process to an organization’s.

Digging a bit deeper, the phrase circular knowledge implies a process that influences the decision-making within an organization. The phrase “telephone tag” once suggested a process that was a result of “keeping in touch” with colleagues. The process of circular knowledge may be a similar emergent behavior. Making a decision without engaging in both a dialog and fact gathering may be a catalyst in the actions an organization takes. Good or better decisions, one assumes, emerge from the process.

Also, the phrase triggers for me an association with the inefficiency of bureaucracies. The behaviors that accompany business activities may contribute to inefficiency, higher costs and unacceptable risks. Circular knowledge can shift attention from the “rightness” of a decision to a process akin to a cat’s chasing its tail. In a less favorable light, the pursuit of “knowledge” becomes a job in itself. Instead of widening a horizon, knowledge, information and facts are distilled to a rationalization. My hunch is that GM and the managers involved in the digital projects with massive cost overruns removed themselves from the broader context of a decision, project or objective. What is surprising is that organizations want better information systems and then demonstrate behaviors that are neither well conceived or informed.

When Mary Barra, the CEO of General Motors, said, “Today’s GM will do the right thing” and “I am deeply sorry,” she seemed to mean it. (See money.cnn.com/2014/04/01/news/companies/barra-congress-testimony.)

The problem, however, is not likely to go away because a person makes a statement under oath. My history professor Dr. Philip Crane, a former member of Congress, was fond of telling his students: “Important principles may, and must, be inflexible.”

Knowledge management systems can provide access to information and a wealth of organizational data. However, if those who tap that information make cost reductions and expediency subservient to what common sense dictates is right and proper action, the most sophisticated retrieval system will be largely without value.


 

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