Keep calm and believe in Analytics
By Kavitha KK, August 16, 2017
Is the turbine No. 10398 about to fail?
Should I stop drilling for oil here now?
Is the multi-million $ loan given to customer A at risk?
Critical questions needing data here and now! Not tomorrow or the day after. Now!
I did say Data is big. That data plays a critical role in every facet of business (and life). And businesses cannot afford to not focus on it.
You now start tapping into the various data sources in your business – the ATM, the Turbine, the heart-rate monitor, every click on your eComm site, the SCADA and so on. There is also the data that comes in from non-machine sources. Human observations, readings, intuition continue to be indispensable (at least for now), and make for very important data sources. Then there is the market research that showing you how things are likely to shape up. (The researchers are indispensable too!)
How then do we make sense of all this data that’s coming in different sizes, shapes and times? And just getting this data, can we get answers to our big questions? The answer is no. Far from it. If you are not applying techniques and technologies to get real-time analytics, then all your data is as useless as the fifth wheel. There, but not often used.
What then, do we need to do? All the data that is collected and cleansed needs to then be put through scientific and mathematical calculations, compared against historic patterns and trends, to identify if your turbine No. 10398 is indeed producing lower-than-usual power and why. What’s more? With smart root-cause analysis, you should be able to identify which part of the turbine is not working optimally? Is it the turbine at all, or something extraneous that’s making the power production dip? Can I know if my turbine no. 10398 going to fail? If so, I need to know now!
The same parallel can be applied to any industry. When Banks have given multi-million dollar loans to businesses, they need to know the risks involved in real time. It becomes important to tap into every source of data available. The data on the health of their business, the policies and frameworks of their business and their vendors and suppliers, their credit history, the partner ecosystem and data from social media, can all be collected and put through rigorous predictive analytics frameworks to help you decide, at real-time, on how risky the proposition is. Or predict if the loan you gave away is at risk.
This brings me to the point that having all the data does not ensure that you can realise its true power. The power ultimately lies with what you do with it. You can have your data watched round the clock by solutions with inherent predictive analytics capabilities, which can alert you when something is likely to go wrong a day, week or month from now. Now, wouldn’t you like that?
Make your data count. Get to know your future. The best way, they say, to predict the future, is to create it. Here’s my take on that. The best way to predict the future is to let your data do it.
No, you don’t need that crystal ball any more.