Identifying cost culprits and optimizing business using analytics

In the uncertain business environment of 2009, business analytics grew robustly driven by cost cutting measures. Akhtar Pasha describes how Indian businesses are using analytics to identify enterprise-wise cost culprits in order to optimize their business processes

Maximizing business intelligence (BI) to improve decision making, increase efficiency and productivity is an imperative in today’s world. Additionally, the credit crunch and recession created a sense of urgency prompting companies to keep their fingers on the pulse of business and find ways to work faster, smarter and better. It's no surprise that BI and analytics, which provide visibility and insight into business operations, have grown in importance and become an area to watch starting in 2009 and this area will continue to gain traction in 2010 as well.

Given the economic realities, effective BI solutions in the coming year will be those that help organizations rapidly tackle specific, immediate business needs without taxing their valuable IT resources. These needs include reducing costs, increasing revenue, eliminating inventory and improving customer satisfaction.

Consider this interesting bit of information put forth by Dr. Y. L. R. Moorthi, a professor at IIM, Bangalore. He asked “Who is the biggest in the music business in India? You would think that the answer is HMV Sa-Re-Ga-Ma. Sorry, the answer is Airtel. By selling caller tunes (that play for 30 seconds) Airtel makes more than music companies make by selling music albums (that run for hours). Incidentally Airtel is not in music business. This sort of competitor is difficult to detect and even harder to beat (by the time you have identified him he has already gone past you).” Perhaps businesses are also trying to make intelligent decisions based on hard facts to survive.

There have been some key developments in analytics, and let’s look at them first.

Innovative use of BI

“During 2009, we saw the biggest growth for the BI and analytics market in a single year. Our enquiries tripled and this was perhaps the biggest growth we have seen in this space in the recent past,” said, Girish Venkatachalaiah, Director - Information Management, Software Labs, IBM India. He added that analytics was growing twice as fast and that this was primarily driven by automation of transactional systems (ERP) that had led to the accumulation of data and set information stores exploding. Further, the credit squeeze and shrinking economy had put additional pressure on profits as a result of which businesses across growing verticals started using analytics to optimize their business and trim costs.

Ashit Panjwani, Executive Director-Sales, Marketing & Alliances, SAS Institute (India) Pvt. Ltd., said, “The economic downturn of 2009 has opened up a new window of opportunity for vendors. Large businesses have started applying analytics to identify cost culprits across departments (in addition to pre-sales and customer services) and reduce wastage.”

Though the sales of enterprise application software remained muted for most of 2009, the market for BI and analytics saw some large projects kick off and these were not merely about applying analytics to gain a 360 degree perspective of customers or to cross/up-sell as was seen in banking and telecom. We saw BI moving from a simple query and reporting tool to analytics and predictive analytics applied across departments to gain enterprise-wide visibility.

For example, a PSU bank is using analytics to improve its working capital by deep diving into the profiles of its corporate customers. It means that analytics has become an important survival strategy for businesses. Similarly, another PSU and one of Asia's largest direct selling MNC organizations (selling white goods) with multiple consumer products is trying to achieve data harmony by cleaning its customer data (addresses) existing in multiple systems and reported in multiple formats. A FMCG company is using analytics to check the incentives passed on to retailers for using their shelf space. Manufacturing companies are using it to reduce their production wastage and optimize spend management as well as spare parts availability.

The bulk of the traction was seen in government projects, BFSI for risk analysis and management of churn, compliance, non-discretionary spend, customer intelligence and to identify best customers, customer retention, warranty analysis and optimizing and cutting costs in the supply chain. Panjwani added, “Customers want to gain enterprise-wide visibility with analytics. They are going department-wise and, after demonstrating success and benefits, rolling out enterprise-wide.”

Sanjay Mehta, CEO, MAIA Intelligence, said, “In 2009, we saw most predictions going awry. However, analytics was used as a means of cutting costs by many businesses. Customers are not ready to wait for a long term deployment as they face rapid growth in data volumes, M&A, government regulations and competition. So instead of the traditional approach to BI that involved building a data warehouse, customers have started directly using the predictive analytics model.”

Having said that, let us investigate this trend and its impact on businesses across key verticals such as government, BFSI, telecom, software houses, FMCG, brokerage houses and how they are using it end-to-end to manage their growth, optimize, reduce costs and improve their top line revenues.

We've seen a growing dependence on BI and analytics across industries to drive better, faster decision-making and reduce risks. Customers are telling us that BI is no longer a nice-to-have, but a must-have to survive and thrive in today's increasingly competitive market. Sunil Jose, Sybase Software India & Sub-continent Region, said, “The Indian business analytics market will grow rapidly on account of IT adoption across verticals, increasing competition and globalization. Indian companies are now viewing business analytics solutions as a competitive differentiator and a strategic tool in an effort to overcome challenges and increase revenue growth and profitability in troubled economic markets. This will pave the way for increased demand for business analytics tools.”

Surya Bhardwaj, Vice President, Applications, Oracle India, said, “The recent economic situation is forcing enterprises to look at IT as an increasingly important lever to drive their businesses. Analytics solutions are helping companies respond effectively in a volatile market while maintaining operational efficiency—it also addresses the difference between market leadership and a struggle for survival.”

Query and reporting moves to business analytics

For more than 40 years, IT focused on operational efficiency. Companies used to use IT to automate front and back office operational systems that resulted in tremendous gains in operational productivity, but the same technology consistently failed to meet the needs of decision-makers. Business users were frustrated because although they understood the business and the data, they still had to spend so much of their time finding it, massaging it, and having to do it all over again when they needed to run a report with fresh data.

BI has moved on from query and reporting tools, though standardized and efficient reporting remains the best way to start any BI project. Areas that are getting a boost from BI initiatives include customer, risk and product management. CIOs these days are talking about how their core business can get the agility needed to act profitably in as real time a manner as possible and they are looking at all areas within the enterprise for leveraging the same. Organizations need fast, flexible reporting systems that allow them to quickly access and analyze data. “Business Intelligence is moving beyond simple point systems like reporting or mining. Today's requirements are more rounded than they ever were in the past. Customers are therefore looking to analytics to integrate directly with their internal business processes and to do so quickly and effectively. The definition of BI has changed in the way that now, to fully leverage the value of data, companies are turning from decisional BI to operational BI. It is evolving from basic reporting to ‘what if’ analysis,” said Jose.

Today, analytical excellence is the name of the game. Winners and losers are determined by the quality of predictions and decisions and immediate access to information across the enterprise is mandatory. BI is an enabler for competitiveness.

Maneesh Sharma, Head-Business User & Platform, SAP India, said, “At a time when the economy is on the path to recovery, Indian enterprises are identifying opportunities to streamline operations in order to maintain their bottom lines, shore up shareholder confidence and create a competitive differentiator. Indian companies are certainly seeking investments in BI solutions that will help gain instant access to the information necessary to make better decisions. The first priority for enterprises should be on the type of IT deployment that provides the biggest bang for your buck. Business intelligence delivers the greatest immediate impact with an instant ROI.”

Let us now closely examine how businesses are leveraging analytics end-to-end.

Identify cost culprits

Madhav Pathak, Managing Director, CRIS (Center for Railway Information Systems), said, “There is a comprehensive set of reports in the Freight Operations Information System (FOIS) to support activities and decision making at all levels in the organization. These reports are custom-built without using any BI tools. We have taken up an Enterprise Data Warehouse initiative which would provide these reports, and more, in the future. We shall select a BI reporting tool to go with this solution. Meanwhile, we are using BusinessObjects to analyze earnings or vacancies in passenger carrying trains, which is part of the Passenger Reservation System (PRS).” BusinessObjects’ software allowed the Indian Railways to be more granular in analyzing information regarding a passenger’s travel behavior and patterns. This, in turn, helped a more dynamic reassignment of capacity and this has allowed the Railways to add or cancel coaches as required. Tatkal bookings and other quotas can be reallocated based on this information. In the next stage of BI, CRIS will collect data on customer needs. They would want to know which passenger groups travel on which lines, why they travel, when they travel, and their class preference.

Konkan Railway is using IBM Informix Dynamic Server for its Railway Application Package (RAP) system to help manage, analyze and maintain train running information, schedules and reduce passenger delays. Real-time data is fed into the management system that uses smart analytics to respond to information in real time—whether it is scheduling delays, abnormalities or passenger queries. The RAP solution helps minimal staff manage all aspects of Konkan Railway’s business, from real-time management of train-running, collecting ticket revenue, managing finances and HR, to automatically coordinating station platform lighting with train-movements. Konkan Railway has significantly improved its ability to analyze, maintain and present data, helping reduce the likelihood of passenger delays and cultivating better decision-making. Additionally, by automating the light-switching at stations with train arrival-departure, the system has helped cut such energy costs by 20%.

Spice Communications runs Sybase IQ data warehouse analytical and reporting processes to identify sources of revenue loss and uncover gaps in its service offerings.

Mehta cited the example of Reliance Mutual Fund which is using 1KEY analytics end-to-end to manage its business. The company uses 1KEY intelligence that pulls the data from nine mission critical applications used by fund managers, risk team, treasury, research, sales and marketing, MIS, operations and IT.

Using Sybase IQ's concurrent user scalability, ICICI Bank supports over 150 users without any performance degradation. The bank uses data warehousing for campaign management and reporting. Data feeds are provided to different departments like credit cards, customer profiling etc., to identify those customers most suited for up-sell and cross-sell offers. The data warehouse is employed to identify customer trends, spending analysis, etc. Beyond these predictable analyses, ad hoc queries are run on the warehouse.

To boost revenue growth

Sharma of SAP said that BI helps businesses weed out inefficiencies from the organizational ecosystem by providing clear, simple and up to date information targeted to individuals and groups of people in a business; to help them make the informed, timely and accurate decisions. As a result, it helps in cutting cost and fattens the bottom line. Further, it enables organizations to make well informed business decisions to create competitive advantage. For example, manufacturing customers would require spend analytics extending enterprise performance management (EPM) into business operations, giving business users organization-wide the ability to pinpoint potential opportunities for cost savings, rationalize suppliers in tune with corporate strategy and track compliance with vendor contracts.

For example, Bharat Forge Limited (BFL), the world’s largest forging conglomerate, is using the 1KEY Agile BI Suite to meet reporting and analytics challenges associated with its greatly accelerated business growth. The software is able to generate complex reports as per the company’s needs. BFL is collecting a massive amount of manufacturing, customer, and business data through a variety of channels. As a part of the project, the MAIA team and its partners will connect to the SAP system and generates reports like Variance Analysis, Cost Reduction reports, Exports Tracking report, Actual Consumption vs. Budget report, Daily Production report and so on. To start with, data from the manufacturing, finance and operations will be connected to 1KEY’s visual information dashboards and content-rich reports for insights into inventory, costs, customers, profitability and key business areas including revenue management, reservations, management reporting and performance analysis. BFL will also use 1KEY for market performance analysis, operations, strategic account management, and global sales analysis on a daily basis.

Similarly Max New York Life (MNYL) is using SAS to maximize its share of wallet and retain valuable customers. Firstly, using SAS analytics it has profiled its best customers to ensure that it takes appropriate measures to retain them. Beyond this, it realized that a mere 7% of new revenue came from cross-sales to existing customers and only 1% of customers owned two or more MNYL policies. In the first quarter, after implementing SAS, sales to existing customers jumped from 7% to more than 20%, which—depending upon the macro economic performance—the company can further increase to 25-30%. Additional information revealed that 9% of the company’s customer base contributed 1% of its revenue–that’s something which it didn’t know before, and it can now act on this knowledge.

The biggest challenge that Marico faced stemmed from its own growth. From being a largely domestic FMCG company, Marico grew at a measured pace to become a company that began to cater to international markets too. With its turnover doubling in three years, seven acquisitions in 35 months and its brands quickly gaining popularity and occupying leading positions, Marico’s biggest challenge became its old, worksheet based budgeting, planning and finance reporting system. This system wasn’t capable or flexible enough to incorporate the drastic upsurge in business. Finance teams faced a number of problems when it came to collating data, managing various budget versions and reporting leaving them with a vast increase in manual work, no time for critical analysis, and a strong need for an automated budgeting, planning and reporting solution. Using IBM Cognos TM1, Marico has streamlined its capacity planning and costing and budgeting process and has taken it to a new level. This analytics tool has helped Marico shift its focus from data crunching to data analysis. Through Project Edge, Marico found that IBM Cognos TM1 helped take the time and weight of collating, aggregating and reconciling data off its shoulders, led to a marked increase in flexibility and was refreshingly easy to use. Employees found that they had more time to analyze financial performance, identify opportunities and influence better business outcomes, giving them a significant edge in the area of Financial Performance Management, just like they wanted.

Reducing IT costs; tracking operations and SLAs

MindTree’s internal IT infrastructure consisted of the SAP environment on Microsoft platforms. The company’s finance team used Excel spreadsheets for annual planning and budgeting. The existing process was decentralized and lacked efficiency, control and transparency. MindTree felt the need for a robust enterprise-wide reporting and analytical tool. The company used tools bundled with SAP BW, which were cumbersome and lacked power. Sudhir Reddy, CIO, MindTree Limited, said, “Implementing the Cognos solution facilitated a planning exercise that involves senior management across multiple locations worldwide. It reduced the complexity and cycle time of the annual planning process. It enabled complex simulations in a relatively easy manner. It gave reports on periodic plan vs. actuals data to stakeholders. It facilitated easy planning for 60 users from EF, IG, Practice and Geographical heads who give plan inputs and four analysts from finance and business. It brought us a 128% RoI within the first year of its implementation.”

The IT team at Reliance Mutual Fund uses 1KEY to track and manage all the SLAs for its nine applications and vendors. It has given the company sufficient proof points on application downtime vis-à-vis agreed ratio, as the fund’s business directly depends on applications and IT systems. Similarly, the company has created metrics and SLAs that used 1KEY to manage the AMC of hardware systems.

Another example is that of ICICI Bank that pulls data from approximately 14 sources to feed Sybase IQ. The number of source systems and data required on the warehouse is ever increasing. The system uses analytical data from various divisions of ICICI Bank like its Retail Banking (liabilities and assets), call centre, Internet Banking and Demat units, supporting over 3.5 TB of data to take business critical decision.

Enterprise credit risk management and corporate performance

IDBI Bank uses a SAS Credit Risk Management Solution to measure, manage and mitigate credit risk across its retail assets by using its data mining and statistical analysis capabilities. The bank was looking at enhancing its risk management initiative in retail banking in line with its plans of being Basel II compliant. For this the company needed a solution that would assist it in understanding the creditworthiness of customers and define preapproved credit lines for individuals. Additionally, it wanted to facilitate the development of analytical models using superior statistical techniques and intelligence. Currently, IDBI Bank uses the SAS Credit Risk Management solution for the performance monitoring of Home Loan Score Card which has been recently implemented in the bank and has been developed by an analytics consultant. In addition to this, the bank uses SAS for its data mining and statistical analysis capabilities for generating the monthly Portfolio Quality Report. In the near future, IDBI Bank envisages using SAS for developing and recalibrating the statistical models internally. With increasing over-leveraging risk these days, SAS tools will help it achieve its objective with respect to Customer Relationship Management (CRM) to have more profitable customer relationships.

Debashis Roy, Vice President - IT, CESC Ltd is also thinking of using analytics on its OLTP (mySAP) data to gain business insights. He said that CESC had four business zones—North, South, East and West. Its high-net-worth customers in each of the zones typically would consume more than 5,000 units of electricity in a month. The company’s objective is to identify these high profile customers using analytics. “We can further cut the OLTP data into giving meaningful insights zone-wise (zones that give more revenues and are most profitable so that CESC can focus more on those zones) and map it against time (consumption peaks/low) etc.,” he said.

Analytics in energy forecasting

Each power utility cooperative has unique characteristics. For energy purchases, the cooperative must contract months in advance. If there is a wrong bet about the weather or energy needs, power utilities end up at the mercy of the spot market. Panjwani said, “If they don’t buy enough, they end up paying whatever the market price is at that point of time. The flip side is that if they buy in excess, they would have to sell it for whatever price they can get. Customers in this space are doing pilots for energy forecasting so that their earning and margins do not suffer.”

India Inc. has taken a giant leap into business analytics. The story is quite absorbing as it captures how businesses have started applying analytics end-to-end in optimizing their business functions and cut costs to safeguard their margins, profits, meet customer expectations and reduce risk. We expect the trend and momentum to continue in 2010.

akhtar.pasha@expressindia.com