TCM: Data Drivers


Analytics solutions pull data from disparate sources to provide a big-picture view of operations and exposures.

By Denise Bedell

In the wake of the financial crisis, the job of the treasurer has increasingly focused on a few key areas—compliance and risk management, global liquidity and working capital management, and planning support. As it triggered a global near-freeze on bank lending, the crisis increased the pressure on corporate treasurers to be able to report quickly on the amount of cash held within the organization, to have a clear view of liquidity needs going forward and to understand risks facing the organization in order to protect its revenue and profitability.

Having good data and good analytics to support decision-making and help drive efficiency is key to effectively managing those tasks. Improved cross-technology integration is helping treasurers pull data from disparate sources, but strong data analytics solutions are needed to make effective use of that data and, ultimately, better manage working capital.

George Ravich, executive vice-president at banking systems provider Fundtech, says: “It is a new world in terms of the level of detail that corporates have now. They have access to real time economic and business data, and they want to know not what their balance is at end of week, but right now. This real-time access to data is now not only expected, but it is a necessity as companies deal with issues of liquidity.”

Treasurers’ demands go even deeper. Access to real-time data is not enough—companies must be enabled to sort through all the data at their fingertips to make use of the information. Dyfan Williams, managing director of Fundtech’s financial supply chain product, notes that data is, by definition, unstructured. “On its own, it is not much good,” he says. “You need to be able to put context around it, to be able to rapidly deconstruct and reconstruct it. And you need to be able to figure out in advance what questions you want answered in order to determine what data is relevant.” Companies are looking for analytics systems that can slice and dice data and return it in easily digestible formats to help people make decisions and increase efficiency.

In the past, decision support systems were far from seamless. For example, companies would download, or manually enter, data for forecasting—including cash positions, historical sales figures, economic forecast data and the like—into a spreadsheet and create a forecast from that to support financial planning and analysis. “Now the goal that drives a lot of companies is how to bring decision support together more efficiently and easily, and how much more quickly you can then take action,” says Craig Himmelberger, director of ERP (Enterprise Resource Planning) financials solutions marketing at SAP. “Being able to improve and increase the speed of decision-making is the highest value that can be achieved.”

Improving Risk Management
There are countless examples of how solutions that pull data from various sources into advanced data analysis solutions can help treasurers to improve treasury management. One that came to the fore during the recent crisis is counterparty risk management. In early 2007, few treasurers thought twice about counterparty risk; now it is a daily consideration. But the key to effective counterparty risk management is that all the necessary data be dependably assembled.


Saric: “We provide data enrichment to help with vendor management”

Says Paul Higdon, chief technology officer of treasury solutions provider IT2: “The effectiveness of this exercise depends firstly on identifying all relevant exposures—which may include bank account balances, deposits, money market instruments, bond and equity investments and FX and derivative positions.” The raw data then needs to be integrated so that the complete exposure information is made available to monitoring and management functions.

“That data includes market rates, prices and volatilities [for valuation purposes], and creditworthiness indicators such as CDS [credit default swap] spreads and other sensitive market indicators such as equity and bonds prices and indices, for evaluating probability of default,” notes Higdon.

On the supply-chain side, analytics systems can pull together information on enterprise-wide supplier contracts, creditworthiness and so on. Alex Saric, director of visibility solutions at Ariba, says: “We can provide data enrichment—for example OFAC (office of foreign asset control) or SDN (specially-designated nationals) information to flag if a supplier is on a US government blacklist—to help with vendor management.” This is useful not only for supplier selection and to raise flags during the selection process but also for ongoing supply chain risk management—to continuously monitor vendor strength.


Ravich: “Real-time access to data is not only expected but is a necessity”

Consolidating and analyzing data from all types of exposure to a given counterparty and combining it with creditworthiness measurements creates a complete and accurate picture that companies can monitor to take swift action when counterparty deterioration is detected. Having such detailed information on one screen—which is now quite possible through solution providers—would have been invaluable in 2008, when the counterparty risk burst onto treasurers’ radars with the fall of Lehman Brothers.

Improved Compliance and Working Capital Management
Data analytics are also proving invaluable in helping treasurers to better manage compliance and in improving efficiency of working capital. Ariba’s Saric says: “Companies are a lot more interested in proactively planning and ensuring they have adequate cash on hand and their supply chain is strong.” And given the continued uncertainty on the global economic scene—and concerns over the ongoing availability of liquidity—they are still looking to find more ways to reduce expenses.

One clear example of how data analytics help is in improving use of working capital in vendor management solutions. A system can retrieve contracts and payment terms with a given vendor, or set of vendors, from across the organization, determine where there is overlap in contracts or where one vendor is giving better terms, and use that to optimize payment terms across the organization. Saric adds: “For example, different parts of the company may have negotiated different contracts with the same vendor. You can consolidate those contracts and negotiate better payment terms with that vendor.”

Small Investments Can Make a Difference
IT budgets have generally risen above the levels seen during the worst of the crisis; however, companies are still very much aware of how and where their IT budgets are going. Although they may look to slightly longer time periods for return on investment, they still want to clearly see that ROI—either through qualitative measures, like better compliance or improved risk management, or through quantitative measures, such as reduced days sales outstanding or reduced cost-per-check. Many companies prefer to invest in smaller steps, SAP’s Himmelberger says. “People don’t want to rip and replace systems that are still functioning well, so a lot of the investments we see now are incremental, and companies are investing in systems that provide high-value decision support,” he explains.

David Williams, director of solution marketing for SAP BusinessObjects, adds: “One of the key drivers in the office of finance is how to improve organizational agility. The challenge is no longer capturing data but delivering it in a format that can be used by the organization to drive their business. That is why we are seeing such demand for applications that help to do that—speed or time to decision is critical.”