The new A and B of the Finance Function: Analytics and Big Data

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1 White Paper The new A and B of the Finance Function: Analytics and Big Data - Evolution of the finance function from bean counter to business partner There s no escaping the fact that finance, and the very nature of its transactions have changed enormously in less than a decade. The finance function has grown beyond simply supporting the business by providing robust forecasting, squeezing liquidity without affecting the business and refinancing. Business acquisitions have brought in multiple legacy systems across businesses with data structures that are out of date or misaligned with the organization s objectives. Lack of clarity on key business metrics lead to data structures not being aligned appropriately. The finance function is now seen as the custodian of business wide information, and is pivotal in structuring data sets that align robust information to the key business metrics. As custodian, the finance function becomes a conduit between the businesses and external stakeholders. Influenced by the rise of global businesses, leaps in technology and the changing investment scenario, the finance function of today is proceeding towards a much more significant role. While organizations have improved the back office operations, the potential of the finance function to create value by supporting decision making remains a challenge. The key enablers which can take the finance function to the desired state of being a business partner are Big Data and Analytics. Finance needs to effectively communicate the results of its analysis of financial information to the operational decision makers. Operations can help finance implement a more analytical and decision based approach to complement its traditional quantitative analysis.

2 While customary reporting tools can only reveal what happened in the past, leveraging analytics enables the finance function to precisely foresee and cater to changing customer needs, business demands, and other impending events and conditions. This paper discusses how the finance function will evolve with the combined forces of Big Data and Analytics and the levers that can help catalyze this change. 2

3 About the Author Balaji Venkat Chellam Iyer Balaji is a member of the Transformation - Finance and Accounting team within the TCS Business Process Services unit. He has 17 years of experience across global markets with domain expertise in Finance and Accounting. He has been part of global finance transformation and re-engineering projects over the lifecycle from due diligence - feasibility to implementation and performance optimization, and has helped clients by developing solutions specific to their business objectives and needs. 3

4 Table of Contents 1. Overview Analytics The Rising Storm The Emerging Big The Big Impact The Finance Function and Predictive Analytics Securing The Enterprise Finance Risk Perspective Conclusion References 09 4

5 Overview 1 The finance function of today is much more than the bean counter of the past. This evolution of the finance function to a business partner allows better focus in application of financial disciplines such as managing for value, performance management, risk management or analytics in the decision making process. Managing for value requires a cultural change in the way information is reported, with finance teams providing much more than metrics and statistics. They share insights and assist in focusing the business towards value creation. Finance as a business partner is responsible for collaborating with the Chief Commercial Officer to plan and implement strategies, challenge the operations with alternative strategies, thereby maximizing value and aiding the Chief Technology Officer in planning and controlling budgets. Finance professionals bring more than just financial measurements the business can relate to. They provide invaluable commercial insights to strategy formulation and implementation based on both their big picture view of the business, as well as their ability to delve deep and understand the granular detail of every business transaction. Organizations now have access to unprecedented amounts of data captured through their Enterprise Resource Planning (ERP) systems, Customer Relationship Management (CRM) tools, Point of Sale applications and the internet. The ability of the organization to convert all of this to meaningful information determines the quality of the decision making process. There are several analytical tools available for predictive performance management, which provide in-built strategic planning, budgeting, forecasting, consolidation and reporting. The current trend veers towards integrating reporting and analysis. Data and Analytics must be at the core of fact-based decision-making. In the evolution of the finance function, Big Data and Analytics are the game-changers ahead. Big Data can unravel unseen opportunities for an organization and will help the finance function assist decision makers in several ways. This paper also draws upon the global trend study conducted by Tata Consultancy Services (TCS) on how companies are investing in Big Data and deriving returns from it. TCS surveyed 1,217 companies in nine countries in four regions of the world (the US, Europe, Asia-Pacific and Latin America) in late December 2012 and January As part of the study, TCS also conducted in-depth interviews with more than a dozen executives across industries about their Big Data initiatives. The survey was conducted across all industries and 13% of the total respondents were from the finance or accounting department across industries. Figures 1 and 2 give a breakup of the sample by industry and geography. Hi-Tech, 18.0% Banking/Financial Services, 19.8% Latin America, 11% Utilities, 3.4% Energy & Resources, 3.4% Life Sciences, 5.1% Consumer Products, 5.4% Asia Pacific, 16% North America, 48% Travel/Hospitality/ Airlines, 3.0% Retail, 9.8% Media & Entertainment, 3.0% Manufacturing, 14.0% Insurance, 7.5% Telecom, 7.8% Europe, 25% Source: TCS Big Data Survey Report Figure 1 Distribution of Respondents by Industry Source: TCS Big Data Survey Report Figure 2 Distribution of Respondents by Geographies 1 bean counter' - the term has several different meanings. The common usage these days is as a name for a rather pedantic accountant, the implication being that, while the layman is content to buy beans by the bag, fussy accountants want to know exactly how many they are paying for. 5

6 Analytics The Rising Storm Analytics strategy is one of the many investment initiatives aimed at making a company more efficient, but it is a significant one. Financial discipline integrated with analytics strategy can have a multiplier effect on overall returns on investment. Further, the resulting insights and smarter decisions also help drive the company forward faster. Organized data and analytics across the enterprise can create a virtuous cycle of continual, synergistic improvement. Similar to other areas of the business, financial leadership must now be able to respond cogently and convincingly to inquiries about competing on analytics. As the competitive environment becomes more complex, company stakeholders demand in-depth intelligence for more refined risk assessment and to help navigate their responsibilities. Effectively analyzing the market and meeting stakeholder expectations along with sound financial oversight of strategic initiatives make the implementation of a forward-looking analytics strategy even more critical to successful enterprise planning and growth. Data and Analytics must be at the core of fact-based decision-making. In its simplest form, business translates into three basic activities: products and promises, selling those products and promises, and servicing the customer. Creating more value for customers does not mean simply producing and promoting products. Most businesses need to innovate in terms of marketing and services while pricing products as smartly as possible and avoiding risk assessment mistakes. Be it manufacturing dry goods or offering mortgage, insurance or health care services, integrating large data sets with advanced analytics is becoming critical for sophisticated market segmentation and market-savvy pricing. More accurate cost predictions can be achieved by several means, but some are more expensive and less dependable than others. The systematic implementation of analytics in conjunction with smart decision-making helps minimize risks for companies while providing customers with quality products at optimal price points. Some companies are rapidly maturing in their analytics expertise, replacing internal efforts for similar or better external analytics data and products. For smaller outfits, a highly accurate predictive modeling initiative can be licensed as a product for less than the cost of one full-time employee per year. In equivalent terms, that one in-house resource must be able to build data warehouses, be an expert in the business, create and validate predictive models, determine estimates and manage those models in multiple systems. A mid-size business can often achieve superior results using externally sourced analytics products that can provide better value than the output from two or more staff equivalents. The larger the company, the more rapidly it can leverage analytics solutions to reallocate resources to strategic implementations that cannot be efficiently licensed off the shelf. Simultaneously, such companies gain speed-to-market benefits for their products and build competitive advantage with their customers as innovators. These same analytics acquisition processes apply to the operations, logistics, maintenance and supply chain functions. Lack of attention to operating costs translates into higher costs and customers will quickly notice and react. If resources don t support initiatives that promote ease of doing business, customers won t even notice because they will already have found another provider. All these factors are fertile ground for analytics to help increase performance and growth. Ultimately, keeping a business grounded in sound financial reasoning and leveraging the science of predictive analytics to do so is how companies will thrive or fail. The Emerging 'Big The game changer is Big Data and harnessing it using the right analytical tools. Why has data become such an issue? There are many reasons. 6

7 As market dynamics continue to evolve, expectations continue to shift about what should be disclosed, when and to whom and in this scenario, Big Data is dominating the strategy discussions. The accepted definition of Big Data now comprises Volume (amount), Velocity (speed of creation and utilization) and Variety (type and sources of unstructured data). The TCS Big Data survey corroborates that while companies are still using structured data (51%), as shown in figure 3, there is an increased need to use unstructured or semi-structured data. The survey also reveals that companies that expect much bigger Returns on Investments (ROI) on Big Data use more external and unstructured data than do companies expecting lower or no ROI. In a generic sense, Big Data refers to large data sets that cannot be addressed using legacy data management tools. Such data requires next generation techniques and technologies to aggregate, analyze and visualize. Semi-Structured Data, 21% Structured Data, 51% Unstructured Data, 27% The 'Big' Impact Source: TCS Big Data Survey Report Figure 3 - Structured, Unstructured and Semi-Structured Dataacross Industries for Big Data Initiatives According to TCS' global trend study on Big Data initiatives, a little more than half of the respondents said they had undertaken Big Data initiatives in When asked whether Big Data initiatives had improved decision-making, an overwhelming majority (81%) said they had. Finance and accounting managers see the most value in Big Data for the two activities: measuring risk and improving budgeting and forecasting, as shown in figure 4. Measuring risk Budgeting/forecasting/planning Determining financing amounts for customers Identifying amounts for customers Identifying bad credit risks Identifying areas of external theft Identifying accounting irregularities Identifying areas of internal theft No Benefits, 5 - Very High Benefits Source: TCS Big Data Survey Report Figure 4 - Potential Benefits of Big Data for Improving Finance/Accounting Activities 7

8 However, there are also many challenges in making the most of Big Data and the value it holds in decision making and bringing agility into the business. Most of all, finance managers need to determine what data they need to make different business decisions. This is followed by getting other functions and units to share information and putting the data into meaningful formats so as to facilitate decision making, as shown in figure 5. Getting business units to share information across organization silos 3.3 Determining what data to use for different business decisions 3.4 Putting our analysis of Big Data in a presentable form for making decisions 3.2 Being able to handle the large volume, velocity and variety of Big Data 3 Determining which Big Data technologies to use 2.9 Source: TCS Big Data Survey Report Figure 5 - Top Five Challenges for Finance for Getting Value from Big Data Not a Challenge, 5 - Very High Challenge Big data can bring to the surface unnoticed prospects for a company and assist decision makers in several ways: Unravel : Readily available data can reduce search and processing time, adding significant value to an organization. Making data available to relevant stakeholders in a timely manner can reduce time-tomarket and improve quality. Analyze : Organizations can collect and manage increasingly detailed performance data on every aspect and use it to analyze variability in performance. This can aid in recognizing the source of the issues and taking necessary remedial action. Innovate: Big Data can provide insights to help improve existing products and create new products and services. The Finance Function and Predictive Analytics The TCS Big Data 2013 Survey supports the view that the finance function today is warming up to leveraging Big Data. Predictive analytics is leveraged to assist the finance function in taking proactive decisions relying on the patterns and trends they uncover from historical data. The plethora of data gathered by the finance function including information relating to accounts, transactions, demographics and other business functions contain vital intelligence that often goes unutilized. Analytics utilizes this Big Data and enables finance to prepare for the future by learning from the past. 8

9 The ability to anticipate illegal or suspicious activities and transactions such as identity theft and money laundering can be prevented. Predictive analytics can also be employed to combat newer tactics used by fraudsters. Unlike traditional reporting tools that only shed light on what happened in the past, leveraging analytics empowers the finance function to accurately anticipate and cater to changing customer needs, business demands, and other impending events and conditions. Securing the Enterprise Finance Risk Perspective Effectively apportioning capital among the contending demands of an organization s operational base goes a long way in determining the extent to which the enterprise can compete and fulfill its mission. How well an organization manages its capital and financial resources is one of the strongest indicators of longevity and success. Every enterprise of any appreciable size and with significant obligations will follow similar guidelines when assigning capital offset to prepare for the outcome of an event or plan. Managers in a variety of disciplines finance, risk, audit must deal with the risk associated with their capital allocation decisions. Clearly, there is a distinct relationship between capital and risk and the analysis that joins them. Improving the use of capital within the organization is crucial, with the use of state-of-the-art predictive analytics on financial management contributing greatly in this regard. Adverse consequences from operational risk can essentially translate into a sudden, unintended increase in demand for capital. Such a situation can immediately drain capital from the company s essential operations and affect the credibility of the company s financial position. With adverse consequences hanging in the balance, the expense scenario takes the form of pay now or pay more later. While efficiencies arise primarily from a more effective allocation of capital, the absence of adverse surprises directly resulting from good business intelligence and a proficient risk management regimen are also critical. Conclusion It is evident from the TCS Big Data Survey results that predictive analytics and Big Data are now considered integral to accomplishing the financial goals within an organization. Together, they can contribute significantly to reducing cost and risk, while improving business performance. As market dynamics continue to evolve, the role of the finance function keeps evolving to new levels. However, it is the finance function s responsibility as the business partner and custodian to ensure the business stays rooted in sound financial reasoning. And aiding the finance function in this task will be the combined forces of predictive analytics and Big Data. References 1. Tata Consultancy Services, The Emerging Big Returns From Big Data A TCS 2013 Global Trend Study (March 2013), accessed May 19, 2013, 9

10 About TCS Business Process Services (BPS) Business Process Services (BPS) at TCS is about managing and executing business operations. Our domain expertise helps deliver core business processing across industries, analytics & insights and support processes such as accounting, HR and supply chain management. TCS partners with customers to accelerate co-transformation, and generates business value for customers through delivery excellence, risk management and through innovative models such as Platform BPS which delivers process as a service. With annual BPO revenues of greater than US$ 1.4 billion, TCS is one of the largest BPS providers with 47,500+ employees servicing 225+ customers across the globe. Contact For more information, please contact us at bpo.imo@tcs.com Subscribe to TCS White Papers TCS.com RSS: Feedburner: About Tata Consultancy Services Ltd (TCS) Tata Consultancy Services is an IT services, consulting and business solutions organization that delivers real results to global business, ensuring a level of certainty no other firm can match. TCS offers a consulting-led, integrated portfolio of IT and IT-enabled infrastructure, engineering TM and assurance services. This is delivered through its unique Global Network Delivery Model, recognized as the benchmark of excellence in software development. A part of the Tata Group, India s largest industrial conglomerate, TCS has a global footprint and is listed on the National Stock Exchange and Bombay Stock Exchange in India. For more information, visit us at IT Services Business Solutions Consulting All content / information present here is the exclusive property of Tata Consultancy Services Limited (TCS). The content / information contained here is correct at the time of publishing. No material from here may be copied, modified, reproduced, republished, uploaded, transmitted, posted or distributed in any form without prior written permission from TCS. Unauthorized use of the content / information appearing here may violate copyright, trademark and other applicable laws, and could result in criminal or civil penalties. Copyright 2013 Tata Consultancy Services Limited TCS Design Services I M I 06 I 13