What’s Your Data Quality Score?

 In Data

Did you ever think about the quality of your data? It’s a topic that’s not usually given enough attention. Data quality is more difficult to quantify than one might think at first glance, simply because there are so many dimensions. The day-to-day work of the fund office depends on data that is valid, accurate, consistent, available, complete, and timely — all of these are aspects of data quality. Every record of data that doesn’t meet these criteria can be the source of errors and exception processes that interfere with the goal of providing first-class service to members. When it comes to data – a focus on high quality really does lead to lower costs.

To quantify your fund’s data quality, I recommend creating a data scorecard, effectively a report card for your data. Each aspect of data quality (validity, accuracy, consistency, etc.) receives its own score based on the various sources and repositories of data at the fund, and these scores are combined to provide an overall data quality score. Following a disciplined process will often reveal stagnant pools of information, long past their freshness date, and will help you prioritize where to begin your data cleanup efforts.

 

Data Drives Fund Office Communications

Some measures of data quality seem obvious; of course we want our data to be accurate! How can we send mail to members with missing or incomplete email addresses? However, if your organization doesn’t have a defined process to keep contact information current, then much of the data – that once was valid, accurate, consistent, available, and complete – quickly degrades and becomes useless (and expensive) for the organization. Just like milk, data has a limited shelf life. In my experience, member contact information can be out-of-date for as many as 25% of members and the lack of an ongoing process for keeping the data fresh and accurate is the root of the problem. Consequently, 25% of the time and money spent on each mailing is wasted, and a quarter of your membership fails to receive the, often time-critical, messages being sent.

Superior member service relies on excellent member communications that, in turn, depend on high quality data. In fact, participants in MIDIOR’s 2014 Study of Public and Taft Hartley Benefit Fund Operations report that IT investment in communications and information delivery platforms is a key area of focus for their funds. But keep in mind that the mechanism for information delivery doesn’t matter if the contact information is out-of-date. This is the Achilles’ heel of fund office communications. Every fund has its own unique data quality issues, but a well-built data quality process and scorecard will allow your team to understand just how serious these issues are and how to structure a plan for improvement.

 

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