The mole is in the system : Why your new enterprise digitization program failed?
Problem Scenario : It’s day one at the office for Mike, as the new digitization consultant of the global multinational software company ‘Alpha’. He has been entrusted and assigned by the CEO with the task of revamping as well as well as figuring out the cracks and loopholes in the DigitalX enterprise transformation project 2020.
His predecessor was not able to take the project beyond the launch phase as the inconsistencies and complexities started popping up very rapidly post deployment.
The following signposts should be a good checklist for Mike to begin his evaluation-
- What were the measurable gaps between the strategic objectives and the operational performance of DigitalX?
- Were the strategic objectives and operational performance metrics clearly laid out in the mission, and were they coherent and aligned?(refer to figure above).
- How should the asset (digital information assets) definitions be improved with respect to business requirements? Was the case for enterprise information integration and interoperability properly evaluated for these asset definitions?
- What would be a better option to achieve an integrated enterprise model, a top-down or a bottom-up approach? In either case, how could it affect the outcomes?
- How much oriented towards end-user value (user-centric) was the employed enterprise information model?
One of the ways to look at (tasks 1 and 2) is to ensure that enterprise business processes are properly mapped to information systems. Therefore, an information system deliverable is an integration of enterprise information, enterprise business rules, and Enterprise processes.(Prakash et.al, 2008).
As far as task 3 goes the organization has to scope out its transition from data quality to information quality. Experienced CIOs would certainly acknowledge Information quality could be tagged as the nexus of actionable intelligence. You need to define what's threshold quality parameters that needs to be ascertained before they are transformed and reshaped through the information flow pathway.
As far as task 4 is concerned the leadership should have clarity to the level of granularity they wish to attain for actionable intelligence for transforming the enterprise information to valuable enterprise digital assets. The ontology and business semantics of any information architecture and the orchestration business rules out of it for decision making can adhere to different models pertaining to different styles of modelling.
The data integration mechanism which is the backbone of any EIA, has to be carefully devised to allow for synchronicity and transparency. In the present global scenario, we mostly deal with distributed and decentralized information systems, hence the extended enterprise ( your company and its collaborating partners) context is a complex cyber-physical entity, that needs a highly provisioned knowledge management roadmap for each of these cases.
I go through in detail about the various state-of art systems and frameworks to approach each of the above tasks and the challenges associated with their implementation, in the upcoming posts.
If these scenarios sounds familiar, and provoke a reflection, you could reach out to me and dont forget to follow and support.
Stay tuned!