As promised I did try and get all of this into a process map last night while getting through the last three episodes of The English (worth watching and the linked review is a good summary). One of the reasons for that is that the type of system I am describing pretty much exemplifies what I call messy coherence and I picked the banner illustration to make that point, Converging footsteps in the snow contrast with yesterday’s single footprint in the sand. If you design a knowledge management (KM) system correctly then its a lot of objects and a lot of interactions so that any application can emerge. Too many KM approaches, whatever the stated intent, end up creating a system based on how the designers think people should work. Better to create opportunities for contextual interaction within a fairly basic design and then put in more effort if stable patterns emerge. In that respect, quite a few Agile people need to think less about clearing backlogs and more about architecture, less about their being agile in development and more about creating systems in which agility is enabled.
So given that principle, it’s going to be a lot easier to define the objects and interactions and make some suggestions about patterns that could emerge, interestingly I could hand-draw those last night in conversations with myself while (Spoiler alert) contemplating the potential horror of Emily Blunt’s face erupting with syphilitic ulcers. The essence of designing decision support systems, and I’ve been doing that for forty years now, is to keep things simple in execution but allow complexity to emerge. Hence actors and artefacts with defined interactions lead it to that.
One thing up front, everything I am talking about here could be done with technologies other than our SenseMaker®. I happen to think that the high abstraction of our metadata lends itself to abduction and serendipitous discovery which means a better capacity for innovation, as well as discovery but what I am going to outline here, is not dependent on its use. That said SenseMaker® Genba, which is currently in beta has been designed with this type of application in mind and with the parallel development of open APIs that will allow integration with existing operational systems.
I’m using objects as a catch-all term, with a nod to object orientation; yes I could get into inheritance and polymorphism, and I suspect both will be a crucial aspect of long-term use, but for the moment I’m keeping things simple. So they fall into two categories as follows:
My intent should now be becoming clearer and I should add that this type of approach will also require some basic reporting and statistical tools – we have used Tableau as well as R and Excel in our own work. You will also need technical support to monitor use, provide assistance with reporting and access and keep a note of repeating patterns that might justify additional automation.
So let’s take a couple of uses cases to illustrate how this works:
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