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Optimising financial processes

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5 Reasons that Data Initiatives Fail to Deliver


81% of GBS leaders surveyed stated that end-to-end process integration is a top priority for the coming year.

The same survey rated the highest priority objective for these same organizations as digitizing and exploiting data. This ranked above automation (2nd) and rethinking the operating model (3rd).

We need timely business insights from a trusted view of data to support the management of operational business processes, inform transformation and to provide the fuel for continuous improvement.

Driving these timely business insights is in the top 3 priorities of any business survey you care to read.

But successful business outcomes from these endeavours is as rare as hen’s teeth.

Why?

A recent article by Adrian Mitchell got me thinking. His article entitled “5 reasons why 80% of data and insight projects fail” is worth a read.

These failings are not just related to abject total failure alone, but to the much more pernicious result of failing to meet customer/stakeholder expectations.

We continue to invest heavily in the technical skills and capabilities for data and insight, but not enough in how to deliver the business outcomes.

Challenges include;

  • Getting agreement on the end-state business outcome required, or “what good looks like”
  • Collaboration between data analysts and business stakeholders is often focussed on the wrong thing
  • Identifying the single source of truth (which varies across the lifecycle)
  • Understanding what the data actually MEANS, in business terms

You can read the brief source article on this topic here . . .

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