The Importance of a Data Quality Framework
Data quality is critical for sales excellence but it is also crucial for optimized marketing and in fact almost any line of business involved in dealing with customers and leveraging customer data.
If there is a data quality problem within the business, then it most likely stems from either a people, process or technology problem.
Over time, the business acquires and adopts bespoke systems and off the shelf products. The technology stacks that these solutions are built upon may use a wide range of technologies that happily coexist but don’t necessarily integrate well. Systems without adequate controls over how data is captured and maintained open up a myriad of opportunities for introducing bad data.
System users are for the most part nontechnical and do not fully understand how their actions contribute to poor data quality. Users also often don’t understand the implications of poor data quality and how it impacts their work effectiveness and that of those upstream and downstream of them in their particular role.
Systems themselves are often configured around the defined business processes that are present. When this is combined with the relative competency and tribal knowledge of the users, you land up with systems that are often optimized for the status quo and not for the ideal operating model. Systems of course also don’t have to be all-digital, part of them could be manual or semi-automated. The reasons for making these choices should be reconsidered in the longer term to determine if adjustments represent opportunities to introduce improvements.
New technology and “big things” are brought to market every day – this makes it hard to decide what to really consider if you want to transform your business into a data-driven one.
If your business considers data as only as valuable as the insights it produces, the actions it affects, and the results it generates then it follows that the data needs to be as good as it possibly can be in order to maximize on all of these aspects.
A business that cannot ensure data integrity gives up its most powerful tool — and loses a potentially massive competitive advantage.
The What Works Community pilot from East Ayrshire Council, Southend Borough Council and Pembrokeshire County Council recently learned about the value of good data practices at their first “residential”. Led by Eric Reese, an experienced training director of the GovEx Academy at Johns Hopkins University’s Center for Civic Impact, he has designed a custom program for local authorities to help improve their data infrastructure and practices and thus strengthen their capabilities in data quality and analysis. The findings of their self-analysis of top data problems were revealing inconsistent, inaccurate, missing and incomplete data were the biggest complaint areas. At the end of the residential, they were tasked with formulating a data action plan.
To do such a thing, you need to have some sort of framework. A data quality framework.
