The Depreciating Value of Data
- by 7wData
CFOs are increasingly being called upon to inform, support and contribute to upper-level strategic decision-making, and in many businesses, financial analysis has replaced financial reporting as the main priority of the CFO.
This change must be reflected in the methods and tools CFOs use. While financial reporting looks back, stating facts about what has happened, financial analysis for strategic decision-making must always look forward, using current data to consider what might happen in the future.
This shift brings with it a change in attitude. Financial reporting was about meeting key deadlines, whether annual, quarterly or monthly. But using financial analysis to aid real-time decision-making requires data that is up to date all the time, not just at certain key moments. It is not enough for data to be just-in-time, it now needs to be real-time.
A piece of data that is truly "real-time" should accurately reflect the world that it models. To make an effective decision in real-time, you need accurate, real-time data.
A piece of data that is correct for today may no longer be relevant, useful or correct the next day. In some industries, the effect may be even more extreme: A piece of data that is correct at 9 a.m. might be considered out of date by 10 a.m.
It does not matter how good your decision-making is if that decision relies on out-of-date data. Businesses that do this are relying on the assumption that what was correct when that data was measured is still correct today - this can be expensive.
Millions of people rely on the real-time navigational information that sat navs provide to get from A to B. But what if, instead of providing real-time information, the directions the sat nav gave were five minutes behind? Instead of showing a driver where he is now, the sat nav would show where he was five minutes ago.
Every time that driver reached a junction, he'd have to make an educated guess about the direction to take based on out-of-date information, and then five minutes later he'd discover if he was correct or not. Sometimes he'd get the decision right, but often he'd get it wrong, and he would suffer consequences for this poor decision -- in this case, a delay to his journey.
Decision-makers aren't truck drivers, but they can be misled by poor information in the same way. The difference is, instead of a wrong turn costing 10 minutes of time, it costs a Business millions of dollars.
Collecting and using data requires three steps:
In the past, each of these steps involved manual work, significantly slowing the process.
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