Data Tips #21 - Putting effort where it matters

Today I want to address something that is very important: putting effort where it is effectful and really matters to the organisation.

There are three main areas I think are important to prioritise within:

• Use cases
• Data quality
• Change management

It is easy to say "we need to improve data quality" or "we need to become datadriven". In practice it is a lot harder than it sounds, especially if you try to fix everything everywhere at the same time. That is why prioritisation matters. The factors differ a bit from area to area.

Use cases

• Use case value - what ROI is expected from the different use cases?
• Strategic value - does the use case make a strategic shift possible?
• Organisational fairness - to drive a company-wide transformation you need to spread use cases between business units, even when the expected ROI is higher in one area.

Data quality

Use case value applies here too. Because data quality affects the business through the use cases, that is a good starting point for prioritisation. If poor data quality leads to decisions nobody trusts, the fix has a business case attached.

Change management

Effort here is what turns a delivered platform into a changed way of working. Prioritise the parts of the organisation where new behaviour will be visible to others - success spreads faster than mandates.