Dark Patterns: Recognizing Them in Real Time

We all know that events are firing off in many directions at once and the amount of events to sort through is mind boggling. In fact for every event you see; there are, at least, an order of magnitude number of events occurring for every one you see and this does not take into consideration the events you don't see (aka Dark Events).  It's a bit of an iceberg phenomena. What can help sort out the importance is to look for patterns of multiple events occurring over time and leveraging those patterns for next best action based on opportunity or threat analysis? Until big data, in memory, this was a difficult, if not impossible approach to take. Ahhh, the advantage of emerging digital technologies for business.

Seeking Patterns of Interest:

There are many noise events and patterns occurring at the same time there are emerging patterns that may mean something to an organization. Just like scanning headlines in the news, you ignore many individual articles. However when certain trends start to emerge, new events and patterns of connected events now mean something. This is true of organizations as well. Identifying emerging patterns of interest or targeting the size and shape of patterns that will require an organizations attention will be a growing field over time as we get into a predictive mode of business instead of our reactive habits.  Mining patterns will be a new set of skills organizations will need to have over time.


Connecting Patterns to Context:

Collecting interesting patterns can be fun, but organizations need to have a purpose that directly or indirectly affect them. This means that patterns of events need to matched against known opportunities and threats at a maximum or analyzed for next best actions. Matching against known patterns is the easy job, which may require multiple patterns to present or emerging. The real challenge is to recognize the value or non-value of an emerging set of events or patterns fast enough to make a difference. Of course there will be the normal analysis after the fact, but the premium is on near real time. Matching patterns to opportunities and threats will also be a new set of skills organizations will have to cultivate over time. There will be noise patterns just like noise events.


Connecting Patterns to Smart Actions:

So a pattern not only looks interesting, but it will require action, specifically associating the right actions that correspond to patterns. In the case of expected patterns, actions can be inventoried and put into action quickly. Many savvy organizations do this today. It takes some scenario planners that can identify patterns that represent conditional action(s). While this is not easy, it has been done. It's the emerging patterns and their ability to affect the getting to the goals set by applications, processes and work forces.  Goals driven approaches with next best action features will lead to the kind of organizational learning necessary to make smart actions a reliable habit.


Net; Net: 

Dark events alone have significant impact on organizations. However,  when events are considered in concert with processes and data, the impact magnifies. The same can be said of patterns of events and the coordinated actions that can and should be made in a timely manner. This is where complexity science can contribute, but that is a topic for another day. Stay tuned for our last blog about dark events on the ROI of Illuminating Darkness.

Additional Reading on Dark Events:

http://jimsinur.blogspot.com/2015/05/announcing-new-series-on-dark-events.html
http://jimsinur.blogspot.com/2015/05/dark-events-introduction-to-unexplored.html
http://jimsinur.blogspot.com/2015/06/dark-event-discovery-and-analysis.html
http://jimsinur.blogspot.com/2015/06/the-trifecta-of-digital-darkness.html