When extolling the virtues of data quality, particularly to a leadership community, it pays to focus not just on the corporate gains but also the personal benefits that better quality data can offer.
Improving data quality can often be a thankless task. You make changes to a resource that many senior managers don’t truly appreciate the value of. When you present the improvements, management can appear more interested in the cost of investment than the benefits recouped.
This is why it’s important to explain what avenues better quality data offers the individual, particularly in the area of enhanced decision making.
An example may help demonstrate this point.
One of my past employers had always captured location data for its utilities infrastructure. Because this address information was rarely used by field staff, it was particularly incomplete and erroneous.
No one regarded this data as useful, so it was ignored from an improvement project. But as a personal exercise, I cleaned up the missing data. This, in turn, enabled me to enrich the data with a geocode (a latitude and longitude coordinate).
Data quality improvements like this open up opportunities to enrich and extend data in ways that can create exciting opportunities for improved management decision-making. They create additional dimensions and lines of questioning that managers can ask of the data.
For example, following the enrichment exercise I created a simple business intelligence dashboard that allowed managers to place all their utilities assets on a map and perform detailed interrogation of the data. I then started to integrate other operational data that was relevant to three other managers (fulfilment, fault management, plan and design, etc.)
By improving the data, we were not only able to show shorter lead times and generally smoother operational processes, but each manager had a new window on the performance of their teams that they could instantly interrogate. For example, they could visualise the sequence of jobs that engineers were taking by location to see if more effective route planning could be utilised, particularly in urban areas.
Regional managers were able to compare their teams' utilisation and lead times against neighbouring regions so that they could understand where challenges such as distance and geography played a role in reducing performance.
There were many more benefits, but if you'd asked the managers what would they like to see, they'd never have envisaged these insights because they felt they were unobtainable. By improving the quality of data we opened up new dimensions of discovery, and as a result they valued the data quality investment far more because it was tangible to them; it helped their working lives by allowing smarter decisions to be taken.
Never forget the corporate benefits of data quality, but also look for those personal gains that data quality brings. They can often be the catalyst to gain greater data quality adoption.
