A report by KPMG and ACCA (the Association of Chartered Certified Accountants) really serves to underline a topic that I discuss regularly – and that’s the role data quality has in business intelligence (BI) strategy and the success of BI projects.
Executed well, a BI project is sure to benefit any organisation. Decision makers need to act faster than ever before and for that they need instant access to accurate information. Without it, it becomes harder for organisations to adapt to change or operate efficiently.
On the topic of efficiency, organisations are spending increasing amounts of time manually processing and trying to draw conclusions from data. Not only can it be prone to mistakes it creates a heavy administrative burden and often when it’s done it’s already out of date.
But organisations need to understand that BI is not a cure to all these issues, otherwise expectations may be unrealistic.
Worryingly the report indicates 17% of respondents were ignoring the information gained from their projects. However the problem is not stubborn executives, it points to lack of trust in the data. 31% of respondents had concerns over their data quality.
“Inaccurate data has eroded C suite trust, encouraging them to base their operational decisions on instinct rather than insight”, notes John O’Mahony at KPMG. This he adds is causing distrust and systemic underinvestment in finance technology.
I believe a successful business intelligence strategy can help any organisation, but as with any project its success is based upon understanding needs then ensuring the project will be fit for purpose.
One way to help ensure success is looking at delivering the project in stages, rather than trying to achieve everything in one go and adding data without restraint. Try a BI proof of concept , prove that it works then build on the success to gain the buy in of key stakeholders.
Another factor, and probably the most important, is really understanding what it is you want to achieve. Just pumping information at users, or worse still giving them the wrong data, is not going to be of use and they will soon lose faith as the stats from the report demonstrate.
I have seen examples where businesses are trying to process large amounts of data and most of it they don’t need. It’s much more efficient to understand what is required and then bring together that data in a meaningful way. That doesn’t mean more detailed information isn’t available, it may just be that it’s achieved by drilling down into that detail only as required.
The right business intelligence solution can aid any organisation. BI doesn’t have to be a daunting, unachievable task. However for organisations to really see success they need to get a fundamental grasp on their data and the story they want to tell with it first.