This article originally appeared on the BeyeNETWORK.
Knowing who talks to whom has always seemed to be interesting if you are tracking gossip or want to know how a rumor got started. But these days social network analysis – as this burgeoning discipline is called – is very much center stage in a number of extremely important applications, especially in the government as it seeks to improve its intelligence capabilities.
Let's start with the fact that business intelligence must be applied if it is to be useful, and it needs to be actionable. In most cases, this implies that the intelligence has to be transmitted, communicated and shared. Whenever the terms transmission or communication are present, we are sure to find that some network must exist to enable the transportation of the bit structure underlying the information that makes up that business intelligence.
Yet social network analysis is primarily about the paths that information exchanges take between individuals and not about the physical infrastructure of the communication networks themselves. The latter enable the interactions between individuals or among people, but the former is concerned with the fact that certain individuals act as key nodes in these networks and become critical factors in the successful transmission or sharing of business intelligence.
Some years ago, researchers in the management of technology field discovered that the amount of communication between coworkers was in inverse proportion to the distance they sat from each other at work. My former professor, Tom Allen, at the MIT Sloan School of Management, showed that there was a 30% chance you would talk to someone whose office was 10 meters away; 15% chance you would talk to someone whose office was 20 meters away; and only a 2% chance you would talk to someone whose office was 30 meters away. Out of this work emerged Allen's well-known "thirty-meter rule" – that two scientists or engineers whose desks are more than thirty meters apart have a communication frequency of almost zero.
These stark findings pointed the way to some of the early studies about how individuals congregated and interacted around the water cooler or the coffee machine and that the socialization that occurred there was invaluable in terms of knowledge sharing. This is a phenomenon closely related to the common belief that the main value in attending many professional conferences lies in "networking," or the ability to communicate and share intelligence with other participants that have similar interests. This is a very human characteristic.
Professors Nonaka and Takeuchi in The Knowledge Creating Company, their pioneering work on knowledge sharing in Japanese enterprises, developed their model for knowledge transfer through a four-phase cycle: socialization, externalization, combination and internalization. They well established how important these cycles are for knowledge sharing to take place – that is, how important it is for the right hand to know what the left hand is doing within an organization.
A Powerful Tool
Enter social network analysis. Today it is getting a very significant amount of attention because it is a powerful tool in improving the nation’s intelligence capabilities, especially our fight against terrorism. If we can find who talks to whom, through the study of communication links and patterns, we might be able to connect the dots and find the bad guys before they do harm. This leads us to carry out business intelligence not only on the content of the communications, but very much on the structure of the network, its topology and in the identification of the key nodes.
However, beyond its role in national security, this specific application of social network analysis allows us to identify the pathways that business intelligence must travel if it is to be used, integrated, enriched and applied by individuals within enterprises. We learn that there are critical nodes, star nodes, usually representing key points in the routing at which important intelligence can either be effectively funneled or tragically choked. For this reason, these star nodes were early on called "gatekeepers." They were essential actors in the process because they received information and then decided whether or not to channel it to other members of the network that shared the same interests or were working on the same type of problems. Hence, the receiving node and the transmitting node (the gatekeeper) collaborate to share information that is useful to other members of the network. Gatekeepers have been identified in almost any work environment grouping of knowledge workers.
Much of the early research in this field took place before the widespread use of the Internet and/or even corporate e-mail, and now we need to understand the implications of these technologies in the process of collaboration, the sharing of business intelligence. Stay tuned, social network analysis and business intelligence travel in lockstep these days.
Dr. Barquin is the President of Barquin International, a consulting firm, since 1994. He specializes in developing information systems strategies, particularly data warehousing, customer relationship management, business intelligence and knowledge management, for public and private sector enterprises. He has consulted for the U.S. Military, many government agencies and international governments and corporations.
Dr. Barquin is a member of the E-Gov (Electronic Government) Advisory Board, and chair of its knowledge management conference series; member of the Digital Government Institute Advisory Board; and has been the Program Chair for E-Government and Knowledge Management programs at the Brookings Institution. He was also the co-founder and first president of The Data Warehousing Institute, and president of the Computer Ethics Institute. His PhD is from MIT. Dr. Barquin can be reached at firstname.lastname@example.org.
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