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Big Data for Finance

From Rob Jenkins, SAP Global Center of Excellence (Originally posted on the SAP Analytics blog)

Big Data is often mentioned as one of the game-changing technology trends that every company must capitalize on to stay competitive. Most CIOs are familiar with how Big Data can be leveraged for transforming marketing (like multi-channel promotion effectiveness), manufacturing (defect prevention) or distribution (dynamic routing systems). In this era of technology innovation, the traditional constraints of storing and analyzing the 5 V’s of Big Data – variety, velocity, volume, veracity, value – have been all but eliminated.

The advances in massively parallel computing and columnar storage databases, along with the price declines in DRAM-enabling in-memory processes, have enabled performance gains by 10,000 times. And the innovation around capturing and analyzing unstructured data (such as social networking data) with user-friendly business analyst tools that require no programming brings a whole new perspective to analyzing and improving all business processes – from employee recruiting to product development to sales to customer retention.

Yet to date, finance hasn’t been a focus area for applying Big Data and analytic technology. As many CFOs expand their role to become a strategic decision-making partner of the CEO and take on operational oversight (including IT), they’re seeking ways to utilize Big Data and analytics to optimize finance processes for increasing efficiency and business insight. In fact, a recent study by Tata Consulting Services found that finance had the 2nd-highest level of expected return on investment (ROI) from Big Data.[i]

Businesswoman touching digital tablet in office

Big Data and Analytics Technologies Improve Finance Processes

CFOs know they need to translate data to decision in real time for competitive advantage.   Market signals can improve forecasting accuracy. Customer sentiment and buying behavior can improve price promotion modeling and “demand-shaping.” Assessing and proactively managing changes in customer payment behavior impacts working capital (DSO). Daily forecasting at retail store level optimizes the supply chain. Currency and commodity markets move in microseconds, so understanding the need for additional hedging in real time is critical.

And every CFO understands the need to focus on fraud detection by analyzing signals with real-time visibility to transaction data. Big Data and analytics techniques and technologies can dramatically improve the efficiency and effectiveness of all finance processes.

“Better, faster, cheaper” is the mantra for CFOs, and with Big Data there’s no need to use short-cuts such as averages. This means running more simulations with no latency – which leads to better decisions with live data. It also means reducing manual processes by simplifying data integration to eliminate reconciliations caused by duplicate and incorrect data.

Finance now has the ability to enable real-time scenario analysis based on market and internal process signals to optimize financial planning and analysis, consolidation and close, collections, and treasury and risk compliance, just to name a few.

Impact on Financial Planning and Analysis

From the development of strategy to budgeting/forecasting to reporting, Big Data and analytics cannot only transform the process but they can also change the way the organization thinks about business model agility. Imagine the CFO’s team using correlation analysis to determine which market signals impact revenue to increase forecast accuracy. Combing the analysis with visualization and spatial analysis BI tools can greatly enhance communication and understanding.

Or consider the ability to perform accelerated cost assignments using relevant drivers on massive data volume to arrive at accurate profitability by granular business dimension. Finance could drive cross-functional collaboration on product/service pricing by leveraging historical sales data to derive insights into demand elasticity by channel or customer category.

Impact on Accounting and Financial Close

Accounting, close, disclosure, and close governance can all be improved with Big Data and analytics. Finance can significantly reduce the time to close the books through accelerated runtimes for period-end reports and using statistical analysis on historical data to automate real-time accruals. Employee productivity is enhanced through self-service information access with visualization enabling rapid review, analysis, and reporting.

Intercompany transaction anomalies can be flagged for managing risk, while journal entry elimination and reconciliation is automated. Business rules and role-based workflow enhance close governance through exception-based approval routing.

Impact on Treasury and Financial Risk Management

Big Data and analytics enable the treasury team to gain immediate insight into liquidity information through real-time, centrally-managed cash forecasts. This zero-latency insight accounts for currency movements and signals if and when there’s a need for additional hedging.

Risk policy compliance is ensured with instant net-open positions (like commodity prices) monitoring. From an internal control perspective, fraud prevention can be enhanced by exposing problematic patterns in payables operations, cash balances, and journal entries.

Impact on Finance Operations – Credit and Collections, Payables, Supply Chain

Changes in customer payment behavior can signal cash flow problems. Reacting quickly, or using analytics to determine when to proactively manage payment terms or arrange alternate financing, can make the difference in getting paid fully on time and not getting paid at all. Some customers are more economically sensitive and liquid than others, and patterns can be amazingly predictable by analyzing the right variables.

Big Data and analytics can also identify process errors, such as duplicate payments by vendor or unusual changes in account balances. Supply chain negotiations can be approached with an entirely new strategy using price and transaction data to define shipment terms and reorder points while maximizing inventory turns and minimizing unit cost.

The Take Away

By applying Big Data and analytics across the portfolio of finance processes, the CIO and CFO can partner to transform the finance function’s efficiency and effectiveness. This enables the vision of “finance as a strategic partner” to become a reality.

[i] http://sites.tcs.com/big-data-study/big-data-roi-logistics-finance/