A while ago I wrote a blog about the Data Quadrant Model I developed. I use this model in my consultancy and speaking engagements. Increasingly I receive great feedback from organisations that are applying it, which is great.
A week ago I wrote about the un-order of quadrant IV, this post will be about it's (diagonal) mirror image, quadrant I. The quadrant of Facts.
It is in all its aspects a mirror image of quadrant IV. It is the quadrant with the lowest entropy. There is order, governance, rules, standards and automation. Quadrant I is constantly searching for efficiency or optimisation gains. The 'systems' (I use the term loosely here) in this quadrant are characterised by (mostly linear) cause and effect relations that are repeatable, perceivable and predictable. Checks and balances are strict in terms of the adherence to standard operating procedures.
Quadrant I is the domain of methodology (seeks to identify cause-effect relationships through the study of properties which appear to be associated with qualities). Methodology can be translated to architecture as in (information) system development. Put it In other words; if you have no architecture for quadrant I.....
There is a tremendous effort necessary to keep the 'systems' in quadrant I low in terms of entropy, it needs to be controlled and it needs to be governed fiercely. Organisational-wise, quadrant I benefits hugely of organisational centralisation (as opposed to quadrant IV that benefits a lot from decentralisation).
What it all boils down to is that in quadrant I there is no fooling around with data. People working in quadrant I have a data-mindset combined with an engineering heart. Data Architecture, Data & Information modeling, Databases (using the terms loosely), Data processing (sets & transactions), etc.. They are infused with the will to improve the consistency, availability, reliability and traceability of data. If there is a science of data, these people are living it and doing it. If anyone wants to know the pedigree of a certain data element....
And no - they are not 'IT' - they are the glue that binds business with IT1 and they are scarce. You either got to buy them or train them - there is no middle ground, especially since universities are dropping the ball here big time. They seem to be pre-occupied by offering 'Data Science' masters now, riding the waves of opportunity and short-termism.
I want 'Science of Data' masters.....
Ah well, at least there is job security for quadrant I peeps. ;-)
1 In terms of Business- and IT alignment I am loosely referring to the generic framework for Information Management - the middle column of the Information management model. Warning: Organisations are using this framework as a blueprint for organizational structure. I can not begin to explain how utterly wrong that is. It is a framework that assists in thinking and designing, nothing more.