Using Analytics for Competitive Advantage in Asia
As Deloitte reports, finance is the function most driven by analytics, where it is most used in financial planning and analysis, financial control, statutory reporting and treasury. While the firm’s survey focused on Singapore, many corporates in other parts of Asia likely face similar challenges. Those that do employ data analytics to best advantage, however, are increasingly gaining ground on their competitors.
As data analytics becomes even more important for corporates in Asia that want to gain a competitive advantage, a key question is where they should focus to get the best return. From strategy to risk management, industry experts have found that analytics offers opportunities for corporates to outpace their rivals
According to the treasury technology group Kyriba, at a strategic level forward-thinking CFOs are asking treasury to collaborate with other departments to adding meaningful insight and analysis that impacts the organisation’s strategy and financial results. Along with using the analytics internally, some corporates are also using supplier analysis to generate a risk profile and also to help suppliers use key metrics, which can result in earlier payment of invoices.
For financial planning, Kimberly Clark Asia’s chief financial officer (CFO) Rodney Olsen was reported by
as saying that his firm uses data analytics for financial planning, to show how key drivers can affect top-line results and to enable managers to react faster to local market dynamics.
At a more operational level, Wolters Kluwer Financial Services’ market manager Matthias Coessens tells gtnews that he sees companies in Asia using analytics for intraday profit and loss (P&L) attribution. Specifically, it is employed to identify the root causes of fluctuations in P&L per portfolio of trades as well as to analyse different risk factors, so that traders and product control officers have the information needed to ensure that transactions are aligned with the firm’s risk strategies and profitability goals. Coessens also sees analytics being utilised for liquidity risk management, which is orientated towards intra-day analysis of risk indicators, in order to facilitate optimal management of liquidity and funding.
Banks Aim to Assist
To perform analytics, industry experts report that Asian corporates increasingly aim to hire skilled individuals, ranging from data mining experts to user experience staff who can help executives fully understand what the data actually means.
Banks are also working to help their corporate clients with analytics, using the companies’ own data as well as aggregated data about its competitors.
DBS Bank, for example, has created free cash flow for its clients through its working capital advisory service. This develops industry and peer benchmarking using a database of 65,000 companies in order to produce customised analysis of client’s operations and concise action steps using diagnostic tools.
Citi told the
Wall Street Journal
it is experimenting with new ways of offering commercial customers transactional data aggregated from its global customer base. Clients can use this to identify new trade patterns and look for signs showing which big cities might be the next emerging markets. It has also used its data and benchmarking analytics to evaluate customers’ treasury practices and suggest alternatives that can mitigate risk or increase shareholder value.
Bank of America used its analysis of customer behaviour on its website as well as call centre logs to understand its customers. Having found that its end-to-end cash management portal was too rigid for its customers, BoA launched a more flexible online cash management product.
Internally, a number of banks are working to overcome their own legacy system issues and processes by developing or installing new systems that can aggregate data across different silos in order to gain a holistic and intraday view of their positions, liquidity and exposure.
Despite the focus among leading corporates in Asia Pacific on using data and building sophisticated models to analyse it, a majority of companies are still behind the curve. While the easier path is to continue relying on analytics for basic tactical issues, companies that do so risk being outflanked by more nimble competitors. It’s the innovators who will leverage data analytics to gain a competitive advantage and push ahead.