In brief
Would you trust data-driven insights if you knew the data quality checks had been neglected? What, even, is the point of a person saying they are data-led if they do not ensure their data is clean?
For Accomplish, nothing is more important than the integrity, confidentiality, and availability of our clients’ data, so we thought you would appreciate this summary of the checks we perform.
Benefits of data quality checks
The Client Behavior Benchmark is built on data from our client’s systems that must conform with the industry-level data dictionary built in order to enable comparison.
On receipt of the data, Accomplish performs crucial quality checks before incorporating any items into the Benchmark. We look for breaks in patterns from past performance, outlying items, and potential errors, e.g. getting your fraction the wrong way around and calculating your product-per-client ratio as 0.67. This is an obvious mistake because clients don’t buy less than 1 product, so we propose the data owner double checks their source info.
Benefit #1: before our clients even receive our analytics and insights, they gain peace of mind that their data has been scrutinised, challenged, and passed.
Benefit #2: we believe in our dataset, which stimulates us to draw insights, hypotheses, and recommendations confidently, and to defend genuine outliers.
Benefit #3: our clients trust the analytics because they have experienced quality control directly.
“With Accomplish’s insights, we don’t argue about the data, we spend time developing response plans.”
How about you? How does this compare to your data quality checks?
