Companies today are under increasing pressure to make better business decisions in less time, with less risk, while producing higher quality results. Their challenges are enormous, as are the many issues that can arise and potentially jeopardize their success.
One of the most pervasive problems companies face is the consistently poor quality of the internal data that they use to draw conclusions and make decisions. Poor data quality is not a new problem, but now solving it is easier than before because companies no longer have to rely on methods that require them to ‘boil the ocean’. Streamlined approaches to data governance that incorporate new processes and data stewardship technologies enable more agile methods for improving data quality.
The problem with data governance programs thus far has been that most companies were taking a top-down approach, while more pressing short-term business demands were derailing efforts and distracting resources. Executives responsible for these programs and line-of-business managers, whose cooperation was needed to make the processes successful, were always scrambling to make their own revenue numbers, launch new products and meet other required business objectives, rather than focusing on the often laborious data governance process, which only produced intangible results.
As a result, today only a very small percentage of companies actually have an active data governance program in place because, in most cases, a top-down approach just doesn’t work. In a typical top-down waterfall approach to data governance, a company spends six months forming a committee, another six months defining and stating the problems, another six months gathering requirements, and another six months arguing about terminology. By the end of a two-year process, a bunch of people have wasted their time in endless meetings with little to show for it.
A BETTER APPROACH
An alternative to top-down data governance, and a much better way to address the problem, is for companies to adopt a more agile approach. By introducing more agile processes, companies can achieve quick wins by implementing data governance processes and policies in smaller pieces, learning from and adapting the approach with each segment, taking time off in between increments to focus on pressing business goals, and then coming back together to address another data domain, while making steady progress over time.
For example, with an agile approach, a company could decide to focus its efforts on a master data management project for its customer data that it could actually solve within six to eight months, which is quite different from a top-down approach that takes years just to get started!
Companies that want to try an agile data governance approach should follow a number of guidelines that will assist them in a successful implementation. Before we get into the specific details of an agile process, let’s take a step back and consider some of the broader issues that are key to the success of any project.