Data & AI Strategy metrics

By April 25, 2019Data & AI

Why are Data & AI strategy metrics important? The beauty of “strategies” for some is that a strategy – unlike a tactic – often doesn’t come with any clear success / fail KPI’s. It allows a lot of wriggle room for ambiguous assessments of whether it worked or not. However any self-respecting Data & AI strategy should not allow this. After all, it is designed and executed in the name of improving the use of data and measurable outcomes within an organisation. A good Data & AI strategy should have measures to determine its success.

Data & AI Strategy metrics that matter

Commonly raised metrics are based around uptake and usage (software vendors are particularly fond of these). This seems based on the hope that the apparent usage of tools is inherently a good thing for a company that will somehow lead to – I don’t know – increased synergy?

Dilbert Utilising Synergy

Dilbert Utilising Synergy

Sometimes they are measured around data coverage by the EDW or project completion.  However, if I was to put my CEO hat on, I would want to know the answer to the question “how are all these Data & AI users improving my bottom line?”. After all, if the Data & AI tools are being heavily used, but only to manage the footy tipping competition, then I’m not seeing a great deal of ROI.

The metrics that matter are the Corporate metrics.

A good Data & AI Strategy should be implemented with a core goal of supporting the Corporate strategy, which will have some quantifiable metrics to align to. If not, a good Data & AI strategy isn’t going to help you much as your organisation has other problems to solve first!

In a simple case, imagine a key part of the strategy is to expand into a new region. The Data & AI strategy needs to support that by providing data & tools that supports that goal, enabling the team in the new region to expand – and should be measured against its ability to support the success of the Corporate strategy.

This is why at FTS Data & AI, our first step in defining a Data & AI Strategy for an organisation is to understand the Corporate strategy – and its associated metrics – so we can align your Data & AI strategy to it and create a business case to justify why you need to embark on a Data & AI strategy in the first place. The metrics are the foundation that prove that there is deliverable value to the business. This is why the Corporate Strategy sits at the top of our Strategy Framework:

Data & AI Strategy Framework

Data & AI Strategy Framework

We have extensive experience designing strategies that support your business. Contact us today to speak with one of our experts.

James Beresford

James Beresford

James has 20 years experience delivering Data & AI solutions for customers from hands-on technical implementation to strategic planning and design. Helping organisations run smarter and more efficiently is his passion. He has a deep history in the Microsoft Data and AI technology stack, which is one of today's most compelling platforms for Enterprise Data & AI solutions.

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