There is no way around it: disorganised data paralyses decision-making and can jeopardise the future of your business. Don’t believe us? We are specialists in data governance and management , and we’ve seen our fair share of examples like this playing out. Here we share a story of an organisation in crisis. Warning: it’s a data management tragedy.
Consider this: an automobile manufacturer realising that the demand for fossil fuel motors was heading south, wanted to establish themselves in the electric car market. A golden opportunity dawned for digital transformation.
How Not To Organise Your Data
Before they could make any decisions, they recognised they needed insights from accurate data to help with the transformation. After much contemplation, they came up with six questions. All had to be answered within a week.
Number one: “how many buildings do we currently own that can be converted to electric car manufacturing plants?”
Simple enough right? They are, after all, gigantic blocks of concrete – quite difficult to lose. By consulting their core datasets, they could identify which buildings they own, but first they needed someone to supply a location spreadsheet and another person to supply a “facility purpose” database. They would then need the penguin plant classification modelling files, and to combine all the location facility records to find the overlapping values.
A veritable nightmare? Almost certainly. Once they had matched their datasets, updated their records (which it turned out had not been touched since 2014) and even located a colleague who ‘was somewhere in Tasmania’, it would still take at least a month before they would have the necessary data to begin the necessary work.
Behind this was one core problem. The company lacked any form of data management. This example of disorganised data resulted in a lengthy, laborious and costly problem to solve. It left the company languishing in a data mess, when they should have been seizing the opportunities before them.
Lessons Learned
In this case, well organised data in digital transformation is an essential foundation. This is why we help organisations improve their data-related architecture, modelling, risk assessment, quality remediation and training: – to prevent businesses suffering from disorganised data, like this automobile manufacturer did. If you are looking to maximise returns on investment and use data to optimise your decision making, then set up a consultation with us today.
