Pattern recognition

March 22, 2013

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Social sciences are concerned with understanding and representation of what is going on and what has happened. Earlier, social scientists took great leaders and their personal characteristics as the topics to be explained. Context and time did not matter. More recent approaches to the study of social phenomena can be summarized as trying to understand temporality; the processes of becoming, live movement in time, which, in the world of business, either gives rise to viability or makes us slowly, or rapidly, obsolete.

The life stream of individuals is the new focus area. Life streams are also called social activity streams. The term “lifestream” was coined by Eric Freeman and David Gelernter in the mid-1990s to describe a time-ordered stream of documents that functions as a diary; every document created and every document received is stored in the lifestream.

In management studies, the questions of becoming, remembering and forgetting are not only new concerns. They are the essence of modern knowledge management, especially in the time of Big Data, when “it is cheaper to keep than to throw away”.

There is a fear of memory loss in business, but there is also the opposite fear, that memory produces practices in the present that should best be forgotten.

Anthropologists claim that reproduction of the past is easier than change. This often leads us into situations where the past is no longer an adequate guide to the present, leading to a situation where an information asset turns into a liability.

Knowledge-intensive work takes place in communication. The process of knowing is the process of communication. The most important knowledge management challenge is to understand what takes place in that interaction: what is being discussed? What is not discussed, what is silenced? Who is included in the conversation, who is excluded? The most important measure, however, is how the common narrative develops, how fast, and where to.

This is why an organization should be seen as a pattern in time, a lifestream, a continuing story without beginnings. Everything we do is built on what has happened before. New people join this narrative and people leave. The patterns that emerge do so because of what everybody is doing. It is what many, many local interactions produce. Work is dynamic participation and influencing how the story develops.

Without understanding and visualizing where we come from and where we are heading, it is impossible to know whether we move at all, whether the flurry of daily activities is actually keeping us trapped in repetitive patterns without any progress. The same people having the same conversation again and again, as often seems to be the case.

Our past, together with our intentions for the future is present in the daily, mundane actions and interactions that often pass without notice. A lifestream is the ongoing reference point and visualization of progress in place (a map) and time (a calender). It is the means for pattern recognition to help create the future we truly desire.

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More on the subject: Euan Semple on Patterns. Doc Searls Weblog. Big Data and pattern recognition.

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