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Building a culture of analytics for all

April 23, 2018 -  Pooja Golakonda Senior Consultant, Presales, Infosys Finacle


Knowingly or unknowingly, we all do analysis and decision making in our daily lives. It could be deciding whether to hit the gym, which doctor to go to, which school to put your kid in and even for that matter whether to reward a bonus to your maid or not. The only difference when it comes to corporate life, we somehow are trained into the habit of taking instructions and following the same.
Corporates are readily equipped to build analytics driven products, but to build an analytics-driven culture is not easy. Culture cannot be brought in from outside, it has to evolve from within. It has to be lived. We can start by questioning ourselves – is it there at my workplace? Are we enough curious enough to understand the what and the why of what we do on a daily basis at our workplace? No points for guessing. Yeah we are still not there.
Internal clients – “Ohhoh… I am always left out”
To put it in simple words, analytics means structured problem solving. Not many at workplace acknowledge in the first place that there is a problem at hand to think and solve. Most workplaces understand and are geared up to provide analytics solutions to their external clients. But what about internal clients and where does analytics fit in? Will try to put across by way of examples – Do we use decision models to decide which clients to pursue? What is the expected client traction for the current product roadmap? Was analytics used to determine which category of opportunities resulted in best results? Can I prescribe what product features are required if I expect a % of turn around? This is where leaders can make a difference and educate their internal teams to identify the problem statement and inculcate the habit of applying analytics in the daily jobs being done. Walk the talk is the mantra.
“Curious for data and knowledge… I might just burn my fingers”
Once we cross the first hurdle to bring the team on common line to identify the purpose of analytics at workplace, the next road block is when teams have to overcome their own perceptions and fears. Some f the common myths that teams hold are – “The data is not there “, “It’s a lot of junk data and results may not be accurate”, “I will lose the power if I share the data”, “it’s too time-consuming, and the cost required to analyze is way too much”. A lot of us ask the right questions but how many of us try to get the right answers? I think the best bet here is to simplify the problem statement and encourage all to find answers. Organizations must transparently reward people to encourage sharing and analyzing data. Once a few rewards are won and the process is in place, the skeptics start losing ground.
“Old ways are always the best ways… why are u disturbing the set up!!!”
Then the next hurdle, once everything is in place, is to implement the outcomes of analytics and to get the team to adhere to new processes. That’s when the trouble doubles up. At times mix and match of teams and cross-skilling can deliver surprising results in overcoming resistance. The changes may not necessarily be only in numbers or end results, but also in identifying training needs, staffing needs etc. Here team leaders and managers need to support the team by giving them the training required and should give a quick view into the results as well.
“Trust Anchor”
The quality of data driven decisions in itself acts as a trust anchor for everyone. Decision making process does not always have to be behind closed doors. It can be more transparent and should involve employees at all levels who embrace analytics. For example, base level employees can contribute to data collection and can apply the tools to come up with the diagnostics for the higher-ups to view. A sense of ownership and a view into the entire decision making process results in increased employee engagement. A data-driven culture evolves and matures through such engaged employees.

 Pooja Golakonda

Senior Consultant, Presales, Infosys Finacle

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One thought on “Building a culture of analytics for all

  • Good approach Pooja, good one.

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