The need for an end-to-end Knowledgeable enterprise for successful digital intelligence


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The need for an end-to-end Knowledgeable enterprise for successful digital intelligence
Sreejith M, Business Consultant, Netherlands

These days the term or concept end-to-end has become an inflated and over-used buzzword which seems to have lost it's true context in practice. The various information management tools each come with a promise to create visibility "end2end" only to re-create and multiply yet another complexity dimension that needs to be tackled before the decision makers could actually conceive true organizational end2end visibility of goals and gaps in performance. Thus it becomes imperative to develop a blueprint for laying the foundation of resilient 'digital-intelligence' so that the digital transformation programs achieve their two most important goals- sustainable value and competitive impact.
Hence, here I want to clarify in a better light the relevance of end-to-end knowledge management for a data-driven competitive organization.
An end-to-end knowledgeable enterprise (E2EKE) should entail the following core characteristics (minimum requirements)-
1.E2EKE should be guided by the information blueprint which fully integrates business information architecture with data intelligence. It should assimilate a dynamic knowledge base that cross-cuts functional information silos to sustain a single-version of truth. This version of reality allows for multiple levels of focus and granularity for a role-based access control.
2.E2EKE has a “deep information architecture”, which cultures prior knowledge (domain knowledge) with context awareness so that 'human in the loop ''active learning' could be enforced. Its deep because the analytic layers of the architecture are complex and non-linear. This creates the imperative that every recommendation made by the intelligence module of the E2EKE information management system is dynamically cognitive, so that it reflects runtime patterns in data and as-is scenarios, rather than static dashboards and historic trends.
3.E2EKE should characterize at all times a consistent mapping of top level organizational strategic goals to operational process, which can be referred to anytime by the relevant roles who could selectively access the knowledge available from the system and manipulate it by a governance protocol.
Further, these core principles of E2EKE system are guided by three main features:
1. Explainable and interpretable
2. User-defined
3. Actionable
All these principles are easier said than done! Why?
Let me explain this in three phases -challenges, core message and the action insight for the decision-makers
The Challenge: Most of the organizations have top-level strategic decision makers who just declare that they want results, mainly summarized as - revenue growth and profit for the given period, over the last period. At the same time, the mid-level workforce has the exponential peril to wrestle and diehard against opaque functional data, complex cumbersome processes and interpersonal conflict barriers to layout the path to achieve these targets. Unless they can show in an impactful way, the missing 'underlying thread' that ties together systemic intelligence, functional competence and overall business performance status-quo, they are battling up against a dead-end wall.
The Core Message: For ensuring BI effectiveness, business and IT should be in sync via the right business questions. The high-point of 'knowledgeable-enterprise' is when its decision-makers are empowered to ask the right questions or queries, guided by explainable insights.
Action insight: For achieving this end, the internal business processes and external market signals (policy, geospatial, trade etc.) should have a common interconnecting thread, that’s interpretable, no matter the role of the user.
Hope these ideas invite you to some new and unique frontiers of disruption in enterprise transformation. In case you share similar ideas or want to critique the tenets, I welcome you to reach out to me.


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