When the repertoire of enterprise data fails to generate any meaningful information to answer business questions, returning to the drawing board is the wise decision.
Observed carefully, more than often, the root cause points to methodology flaws rather than a direct breakdown in IT systems or integrations.
Problem is, we still treat data as departmental assets and take a territorial approach to fixing problems. While this is necessary for quick turn around, a holistic approach needs to be in place for addressing data issues impacting across the organisation (involving both IT and business teams), or we’ll end up storing a huge amount of data unusable nor used by the workforce.
Some key areas that should be coehersed to ensure continuous value generation;
Observed carefully, more than often, the root cause points to methodology flaws rather than a direct breakdown in IT systems or integrations.
Problem is, we still treat data as departmental assets and take a territorial approach to fixing problems. While this is necessary for quick turn around, a holistic approach needs to be in place for addressing data issues impacting across the organisation (involving both IT and business teams), or we’ll end up storing a huge amount of data unusable nor used by the workforce.
Some key areas that should be coehersed to ensure continuous value generation;
- A focus group with representatives from every unit of the business.
- Specifying organisational goals that are aligned with data capturing, collecting, analysis and representation accross the organisation (outlining the big picture for your data projects).
- A common mechanism/process to capture data challenges faced by every unit.
- A clearly outlined Data policy for internal users ( sharing, redundancies, security...etc)
- Periodic measuring/ reporting of data assets and its returns ( e.g Data ROI, YoY return, ratio of active and unused data, amount of Intel lead to new growth engine, productivity increase and etc.)
- Strategic mining of the unused or less used data for new insights on business questions
- An active initiative to resolve the top three to five data issues affecting the business (e.g. Incomplete customer data, redundancy, bias data, sluggish data delivery to users and etc)
Achieving data utopia might still be a far fetched dream, especially when data is collected through almost every imaginable device/equipment possible. As such, there is no shame in starting with huge amount of wrong data rather than no data. Understand the big picture and take a phased approach, solve one issue at a time. Measure outcome as you move along and the value your data generates will only increase.

