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A new business information system, or decision support tool, is a big investment, but if you are considering buying a new system which promises to improve organisational effectiveness and efficiency, how confident are you that it will achieve these objectives if your underlying business data is still the same old data you’ve always had?

The benefits generated will be heavily dependent on the quality of your data. Any demonstration of a new system will likely use highly tailored example data in order to show off its full potential, but what happens when you plug in your organisation’s current data? Same results as the demo? Possibly not. The new system might highlight some underlying data quality issues you may not have even been aware of, or perhaps you were aware of them but they hadn’t been a problem up to now. Or maybe it isn’t even possible to plug in your business data without a great deal of manipulation first to fit the new system’s requirements.

The fundamental questions for the organisation are:

  • Is your current data of sufficient quality to achieve the expected benefits?
  • If not, what is the likely time/cost/effort to improve data quality to required levels?
  • Does the business case still stand if these costs are included?

If your organisation’s data cannot be easily (or cheaply) improved, or made available to your new system, is it still worth pushing ahead with the new software? Will you just get the same (possibly) dubious results you always did, but in a prettier presentation?

From a Data Manager’s perspective, the headache could be having to having to undertake a complex data migration project.

Do you actually need the new information system or just better data quality/availability? Or do you need both?

In the next part of this series of blog posts, we will look at why data migration can be such a challenge.

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