Editor’s note: Marcus Silversides is the head of data at Researchbods. This is an edited version of an article that originally appeared under the title “6 steps to building confidence in your data.”
The importance of having confidence in your data as a researcher goes without saying. Whether you’re reporting results, breaking bad news or otherwise, you need to be able to swear by your data.
You may be making recommendations for a new product, advising on messaging or comms or sharing a shift in consumer behaviors. Either way, your data will likely have a significant financial impact, so you need to be able to stake your life upon it (though no reasonable company will hold you to that!)
How many times have you given a client or stakeholder feedback knowing it’s not what they want or expect to hear? This could be the CMO’s pet project or a campaign that an entire department has already sunk many hours into. How can we build confidence in our data? How can we ensure our data has integrity?
Data integrity refers to the accuracy, validity and completeness of data throughout its lifecycle. Data might lose integrity and become compromised through replication, alteration or data loss. Anything with the potential to change data after the fact could result in it being compromised. Data might even be compromised from the point of collection, through inappropriate collection methods and techniques or source selection.
This is a given. You need to know your subject to have any chance of identifying things that look out of place. General reading around a topic and comparison with other existing data sources can help give you an idea of what to expect, as well as highlight deviations and anomalies.
They will have the background data, sector sales data and more. Don’t bank on it being volunteered, but you can bet your bottom dollar it’ll surface if the research data doesn’t meet their expectations...