Data Visualization Helped Madras Cements Turn Big Data into Big Ideas
A simple change in the way you visualize data can lead you to a new world of insights as Madras Cements discovered.
Varsha Chidambaram Aug 08th 2013

Let’s put some commonly held myths to rest. Big data doesn’t reveal earth-shattering information about your customers or about your business. In fact, big data doesn’t reveal anything. If anything, big data is term to describe the current state of the digital world which is creating, and capturing digital data made possible by technology.

What’s the big fuss about big data then? Service providers want you think it’s huge because they want to sell you solutions that will help you do capture and store data. They however, will not help you decode the various cryptic patterns and lead you to discover what your customers want or the market is demanding. Even Dan Brown can’t help you with that.

The fundamental problem is that traditional forms of data interpretation have stuck to text or table based report like Excel sheets. But humans are visual creatures. Our ability to quickly interpret visual information is far greater than that of written words. The data deluge we are witnessing further compounds the problem. Our attention spans are shrinking, there’s a constant overload of information and our ability to retain what we read is abysmal.

Data visualization or the art of interpreting data through info graphics, color-codes, geo-mapping, and 3D modeling among others is paving the way to make complex data into simple, consumable information sets. And N. Vardarajan, AVP-IT of Madras Cements is one of the few Indian CIOs who has successfully embraced it to spectacular business results.

Madras cements is the fifth largest cement manufacturer in the country and second biggest in Tamil Nadu. It had all the traditional IT instruments that it needed to function efficiently. An ERP, business intelligence software, a great supply chain, and an efficient workforce, and yet  the top-line didn’t grow as much as expected. It’s true in cement industry; supply has always been higher than demand and competition is tight. But the demand too was growing, so  how could Madras Cements leverage Information Technology to  tap the potential for top-line and bottom-line growth?  

 This was  the challenge faced by the company.  The IT Team of Madras Cements knew there was lot of scope and untapped potential in managing information. Their ERP was generating rich data but the lack of visualizations was hindering the company's ability to leverage it and get better insight.  It led to the conclusion that  the only way to avoid it was to radically change the way the end users saw, read and interpreted data on any device, whether it was desktops, laptops, mobiles ot tablets.

Information can be presented in many ways. But complex information such as a salesperson performance or cement outlet performance benchmarking or location mapping of the company's wagon movements are best understood not through numbers but through color coding and representation on a map.

Hence, Madras Cements decided to integrate its entire business intelligence system with the enterprise version of Google Maps, while its Ramco ERP application provided the underlying data. Super-imposing its data onto Google Map layer, led to some stunning results.

All across India, over 300 field salespersons access reports and transactions on a daily basis from the company's ERP system and integrated Google maps based BI. Management at Madras Cements started using Google Maps for visual analysis – for monitoring benchmarks, and identifying discrepancies and deviation.

The technique followed is called “Geocoded Color Banding”. They assigned color codes to denote a range of performance. For e.g. performance beyond expectation was assigned a dark green, expected performance green, average orange, below average a red and very bad performance is given dark red. Such color coded icons are depicted on Google Map using longitude and latitude data captured. For example, the delivery time from factory to each customer outlet can be shown as color coded dots with the dots placed on their longitude and latitude values.

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Now using the tool, the dark red dots among predominately green dots quickly pointed them to areas of weakness and anomalies. More than 60 such KPIs/parameters can be visualized as color coded icons or regions on the map. This brings out additional insights than what is normally available through a table or a chart. For example, it is very useful to compare and benchmark information such as dealer outlets, delivery points, marketing region or sales person performance.  The tool allows choosing a particular Geographical entity (like Kerala) and analyze the chosen KPI based on a slice (say district, customer Point, etc). It helps to analyze patterns of distribution of these color dots on the selected area.

For example, the company monitored one KPI called “Ontime Delivery Index”  of its shipments to customers to measure if shipments were reaching on time.  Understandably, all areas around the factory performed well since they time taken to reach was much shorter. But amidst all the green or light green dots emerged a single orange spot. The business started to ask? Why was he delivery to this particular dealer so late despite its proximity to the factory?

“We’ve also noticed a 10-12 percent increase in sales. But that’s just quantitative data. The customer satisfaction that has improved is immeasurable!”

A little investigation revealed that a particular customer was located on a hilly terrain, because of which it was taking more time for delivery when a truck used was less powerful or old. When the problem was identified, logistics took up the matter with transporters and advised them to use better trucks for that particular location. From the next dispatch, the deliveries were on time.

 “Insights like these would be impossible without such a visualization tool based on maps. Such data, known as “geographically significant iInformation” forms bulk of Marketing Performance BI,” explains Varadarajan.

The tool has an Exception Module which alerts management immediately when any performance parameter downgrades in color (say a green moves to an orange, indicating that performance is dipping) and prompt them to take corrective action before it’s too late. This module also helps to analyze and focus only exceptional items for a particular KPI, say Dark Reds, instead of viewing all data. Another aspect of this tool is that no data is entered for this purpose. The data is captured as physical process is done (like invoicing, Accounts receivable etc) and KPI is built on this vast volume of data. This ensures transparency and objectivity. There is an inbuilt Issue Tracker which can be used to raise queries to concerned salesperson (through mail/sms) based on the depicted data and to track responses/action taken.

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Madras Cements’ sales and marketing divisions also benefited from this system of BI based on Google Maps. The field sales team now has the capability to easily view information on their mobile devices – information ranging from competitor distribution networks in their area, to the best and worst performing dealers and salespersons. This not only enabled them to make better sales strategies on-the-go, it also helped management improve their market penetration strategy based on competitiveness in a particular market. They can now locate their cement warehouses and outlets and key customers on Google Maps vis-à-vis critical operation information, empowering them to devise effective supply chain strategies and enhance customer service. Google Maps based BI helped to visualize data at various levels of detail, for example, which regions were experiencing strong growth, which dealers were performing best, or had the most potential for growth. Google Maps also made it easier to identify and analyze performing markets with the potential for growth.

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The results have been stupendous. Madras Cements reduce penalties, losses and damages arising during the wagon clearance process by up to 70 percent, and improved consignment clearance time by up to 40 percent.  Since implementing Google Maps, the company has successfully captured 20-30 percent market share in these specific markets. “We’ve also noticed a 10-12 percent increase in sales. But that’s just quantitative data. The customer satisfaction that has improved is immeasurable!”, says Varadarajan.

Big data can only lead you to bid ideas is if you ask the right questions. But technology can take you a little further, if you have the right tools.

For example, the company monitored one KPI called “Ontime Delivery Index” of its shipments to customers to measure if shipments were reaching on time. Understandably, all areas around the factory performed well since they time taken to reach was much shorter. But amidst all the green or light green dots emerged a single orange spot. The business started to ask? Why was he delivery to this particular dealer so late despite its proximity to the factory?