Measure success
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The metrics of data governance success must be tied to the desired business outcomes
Like any investment of time and money, data governance initiatives will be expected to produce measurable outcomes.
Which metrics are best suited to gauge success will depend on the strategic objectives laid out in the business case.
But whether it is an increase in sales or a reduction in regulation snags, it is vital that the measure of success is defined in the early stages of the project, says Gartner’s Lapkin.
“You measure the success of data governance by measuring the business outcomes,” she asserts. “That’s why it’s so important to establish these at the front-end.”
Howard warns, however, that precisely quantifying the results of a data governance strategy is a complex task, as data affects so many facets of the business.
A cross-selling initiative may, for example, lead to intangible benefits, such as employee loyalty, by driving up sales commission. Or it may fail to meet its revenue increase targets, but could “identify places where [the organisation] does or doesn’t have sales opportunities, which makes everyone’s job easier.”
“Data governance works like anything else in IT,” Howard surmises. “You justify the investment based on what you can quantify, and the rest is an added bonus."
