The Data Made Me Do It
In a workplace culture where we need to complete tasks faster than perhaps feasibly possible and make more profit than the market has to give, we’ve noticed a worrying trend with data. It’s become a safety net rather than a guide, a scapegoat rather than a security blanket.
We’re obviously huge fans of data and accurate insight, we base our own revenue and the revenue of our customers on it. We don’t, however, listen to it if, in context of what we know for sure about a business, or an industry, or a product, or a market, it doesn’t make sense.
It has become common place to listen to data regardless of any nagging concerns that it might be leading a strategy up the garden path. More often than not this is because taking a bet and ignoring some cold hard data and listening to your gut is a scary, scary thing. Don’t be led by fear. Data is there to give you insight. It should be considered alongside other factors and not listened to blindly. If every business is listening to exactly the same data and acting on it in exactly the same way, how are you to differentiate yourselves. It’s an advisor, not a dictator. Remember that.
You Can’t See the Floor for Data
If data was a tangible object lying about the office place, a lot of businesses would appear pretty dysfunctional. Employees would struggle to get through the doors and to their desk. They’d be on that programme about hoarders, collecting and storing any old data with no knowledge of why or when they might use it. We understand how this happens. It’s no problem keeping data ‘just in case’ as long as the correct repositories and filters are there.
A problem tends to occur when all the data is collected with no strategy in place making it harder to make sense of at any point.
A strategy which identifies the data required to support business decisions, the age at which it becomes less relevant, the correct repository and filter and an understanding of the context in which the data should be viewed really needs to be in place to make the hoarding worthwhile.
Low Quality, Inaccurate Data
Bad data isn’t better than no data. No data means that you have to rely on your knowledge and expertise. Bad data means you ignore what you know and listen to nonsense.
We know you know the obvious issues with cheap, inaccurate and hole-filled data but do you keep an eye out for innocent anomalies in an otherwise accurate set, that could set your data way off kilter? False data caused by the odd unprecedented stat causes a raft of problems from flawed strategic decision making to smaller pipelines to ineffective marketing campaigns. The easiest way to avoid the situation is to have your system flag anything that deviates too far from the norm so that you can investigate.