In recent years have seen information systems intelligence increase to the point that somehow we are led to think what systems choose and act on the work we do.
We know that today we live in knowledge management era and the needs and expectations of the human being point in the way that systems help us how to think, show us the information we need to work quickly so that we can use it to make a decision.
A month ago my car suffered a serious breakdown. It broke the diesel pump (we Europeans like to drive diesel cars) and fuel entered into the engine. At the time the breakdown occurred I was driving at 220 km / h (in Portugal we do it very fast) the pace at which fuel entered inside the engine “cleaned” it at the speed of light. The engine was so clean and shinny (no more oil to lubricate it and consequently it broke plus the turbo, intercooler, etc). I was lucky because the repair cost become free of charge and in return and got the same car but with a completely new engine (0 km).
Yesterday appeared on the car’s control panel (like a BPMS’s dashboard) an exhaust sign with some circles inside. I was glad to have a system that tells me so quickly that such malfunction exists.
I took the car to the garage and it was told the particulate filter it had to be changed and I was a lucky guy because there is a high risk of fire.
When I made a reflection about this filter issue I remembered the fuel pump failure episode.
When stopped the car because the control panel showed an alarm signal to inform that the engine had run out of oil, I noticed that the trunk was sprayed with diesel because most of the fuel went directly out to the exhaust (where is mounted the filter – voilà!).
Why when the engine was being changed the mechanics and did not thought to check the filter? Simple: because the diagnostics are made using “intelligent” systems that read inform stored in the car’s control unit. Once at the time the repair was done the filter’s status had not reached its critical point, the mechanic (our knowledge worker) did not bothered to think it was necessary to carry out additional mechanical parts inspections that could have been affected.
The mechanic did not want to think because this type of particular system is turning people into lazy.
This issue does not even apply to the brand of my car because it seems that it became a best practice. The other day someone told me it took the car to repair in order to solve an issue. Two days after the engine had reached the minimum oil level. Previously whenever a car went into repair regardless the kind of service requested mechanic carried out a basic inspection (a good maintenance practice to avoid future failures).
If indeed it is very important to have systems that tell us where failures are occurring and thereby contribute to reduce the diagnosis time and action taken, on the other hand it seems like we humans are giving too much importance only to information that the systems provide, limiting our ability to reason and perform the work.
Are we being carried by this trend?
Martin Böhringer dedicated to study activity streams and has published a presentation called Using Activity Streams to Provide Enterprise Case Management solution at www.bpm2010.org and questioned on the other day on Facebook’s group called Activity Streams in Europe if users trust machines choosing information for them.
This question is clearly linked to the case presented here. My answer had two variants: regarding a personal standpoint I think we appreciate that systems present information we are interested in subscribing (news, photos, trends) on a professional basis users tend to take control of the meaningful streams to perform tasks. Otherwise users will get lost and become unproductive by information overload. It is essential that we manage the information that we intend to analyze and carry out our reasoning ability to link information and perform our work in the business context.
A lot could also be told about moments of truth regarding customer perspective, because this is also business process management, but I think the case is self explanatory and you can did your own conclusions.