| |September 20208DECIPHERING ANALYTICSBy Anand Bhatia, Chief Marketing Officer, FinoBankA professional with extensive experience in the BFSI segment, Anand has as worked with Citi Group for almost a decadehen we see , hear or even speak the word Analytics it conjures up, Graphs, Charts, Numbers running all over a computer screen. It is often associated with a `Data Scientist' virtuously spewing jargon on Random Forest, K means, Rsquare or some such.Is that Analytcs? Partly , Yes. But there is more to it.Having worn different hats at different points in my career as a Sales Manager, Product Head, Co-Founder running a firm of Consumer Behaviorists and now as a CMO and Analytics Head , I have a more useful definition of what Analytics really is`Analytics is seeing what others see, hearning what oth-ers hear, read what others read, but be able to come up with thoughts and actionables that others DO NOT.'It hence goes beyond the models and the charts, for they are merely tools, as much as a jackplane is in the hands of a skilled carpenter. It is his skills, mindset and discipline which gives us a flawless table, not the tools.So what skills are needed to be good at Analytics? Clearly dexterity with numbers is a primary skillset and so is knowledge of mathematical models, data transforma-tion. But this is commodity. Increasingly teams in Analytics will need the follwing skillsets and tool to thrive and make a business impact.1. Mind-set ­ A near childlike curios-ity which is not jaded by repetitive tasks involved in the analytics process (Data Extraction, Preparation, Loading, and Reporting). This means that the analyst has to always be open minded to newer possibilities and different ways of look-ing at the same data. 2. Patience ­ An underrate virtue. Very often predictive analytics, projec-tions take time to play out in the market place. There are always contingencies, factors outside the control of even teams who are implementing the solutions. Since output is delayed/not in line with expectation there is always a clamour to relook the input. This is where patience and staying with a plan gets critical.3. Feedback Loop ­ No analytics proj-ect can be complete without a feedback loop. This is the Secret Sauce of this trade. Importantly feedback loops may often be beyond the control of the Ana-lysts e.g. ­ Frontline Sales Teams keying in all details of consumer interaction into the CRM. Hence the design of any process regarding Forecasting, Predic-tive Modelling needs to have the feed-back loop pre designed or based on KPIs which have fewer contingencies.4. Culture ­ This is where the Analyt-ics team needs the support of the corner office. The right Culture at an organiza-tional level means that the ground level feedback on consumer facing interac-WExpert Opinion
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