Visualization Parachute – Marico’s new BI oiling formula

By : |November 25, 2014 0
Combing tangled and untangled data, giving the gloss of analytics for sales without compromising on the strength of insight-roots – that could sound tricky but Girish Rao has straightened those IT tresses in style and beyond the cosmetic look. Smell it up

MUMBAI, INDIA: It is a well-known name, whether it is the global beauty aisle or the Indian shelves of wellness for hair care and beyond; but Marico, besides upping its ante in the innovation stack, is also strong and suave when it comes to IT.

Its vast presence in over 25 countries across Asia and Africa and a deep portfolio of brands like Parachute Advansed, Saffola, Hair & Care, Nihar, Mediker, Revive etc make it an imperative that when it comes to the IT shampoo and the sales conditioner, they blend seamlessly and well.

Just some time back, Marico had depended on daily sales reporting, something that the staff would prepare and email to senior management. However, such reports lacked flexibility and those crucial insights that management usually seeks out. Not to forget, the conspicuous absence of standardization and presence of inaccuracies that manual reports are perceived to trundle with.
But circa today, and you can see Marico’s sales guys analyzing hordes of data on retail behavior, sales and marketing, inventory movement, procurement of key inputs, etc. smoothly and effortlessly, as they keep gaining detailed insights into the company’s performance side by side.



The data is now apparently in visualized packaging and its pours out beautifully for teams from various departments in the company, offering easy-to-consume and highly customized dashboards/reports for decision-makers and management.

Girish Rao, Head of IT & Business Analytics and a noted name in CIO fraternity for his visionary approach and well-rounded savoir faire with IT and business; takes us through this interesting make-over with analytics, BI recently done at Marico.

What prompted and accelerated this change with how and where of data being consumed? What were you looking for and how did you fine-tune your transformation?

We evaluated all the BI and Visualizations tools available at that point of time (when we started this journey of analytics two years back). We wanted to equip some users with strong visualization form of data as operational and tactical data was already being consumed with SAP but tactical and mid-level users needed a different way of digesting it. So far we were dabbling with different tools and getting a sense of user requirements and then we started building small prototypes, getting data at one place and homogenizing it. After spending a lot of time there we came across Tableau, somewhere at the fag end of our evaluation and experimented with a trial version with a small set of users.

Having got a good feedback from users and seeing the turning point of it not being IT-Dependent, we considered it seriously.

Then? What next?

We could use same data for different departments and still found that end user-dependence on IT would be less. We went on to serious POCs in sales, supply chain and commodity chain areas. We also built a framework for enterprise-level requirements, for standardization, control etc. It can sync with multiple sources of data like SAP, IMRB, Nielsen data or front-end or back-end points and allows visualization for user. The Enterprise dashboard is still under implementation but individual POCs are running well. This is a bigger journey of how IT departments are changing and becoming less intrusive/control centers and more of catalysts. Other solutions needed IT’s role somewhere and here with Tableau, that part was greatly reduced and allowed to empower users, so this one has been a good choice.

How has it fared on expectations?

Now that it is deployed, Marico has standardized reports in a clean PDF format and customized dashboards with vizzes reflecting all manner of KPIs for managers to get the insights they need out of the data. Besides the ease of reporting, Tableau has also offered Marico significant cost savings. Marico has invested tens of thousands of dollars in Tableau, as compared to hundreds of thousands of dollars of investment in traditional business intelligence (BI).

Did this journey entail any challenges?

One has to make sure to do well when it comes to equipping users with semi-finished material and encourage them to run themselves instead of using canned reports; and on good data capturing, proper integration of data sources, apt homogeneity and standardization of framework, as well as on good cleaning up of master data.

Are the outcomes in line with overall strategy?

The results are pretty actionable, descriptive, comprehensible, and easy for decision-maker’s use. The hunch-factor is now replaced by better insights. From sales information, better reach of distribution points and stronger decision making to faster insights, lot of gains have happened.

Does it make more room for scope of predictive analytics?

We are working on two to three business aspects, but this is more of a journey of building models and will take some time. This is a long-drawn process since it may entail juggling of many vectors and with different combinations. Setting up the right models is the fundamental part here.

What else is being planned next at Marico?

We are considering a lot of things and trends with interest, like IoT or broader consumption of analytics or 3D manufacturing of non-key products. Use of IoT and upcoming manufacturing technologies and future-proofing these trends is what we are focusing on.

How do you sift between hype areas and areas really plausible and feasible for your roadmap, like IoT, for instance?

IoT borders on hype but possibilities are enormous and we have to start working towards that. It’s a question of whether you wait for a trend or technology to mature or you try it immediately. Cloud, for one, was also a new trend. As tools stabilize and frameworks get mature, it turned out to be beyond hype. The ideal way is to jump on a new trend before it hits the maturity curve, else you lose the accompanying competitive advantage. Do small prototypes, understand latent demand, get clarity, nurture the ecosystem around, and gradually scale up. Example, with analytics, the challenge is not so much around a hot tool but on cleansing of data and that is something you only realize when you start on it.

Have lines between traditional functions like marketing, IT, manufacturing blurring more strongly than ever?

It is a psychological change and a huge one in that sense. IT is not merely recipient of strategic decisions anymore but more of solution-creators rather than just implementation guys.

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