Simply having lots of data does not necessarily translate to having lots of insight. Strategic and useful data-driven insight requires effective advanced analytics. As Rick Rodick, chief financial officer at TELUS International, explains, “My biggest concern is what we don’t know. Even if you have access to the data you need, you could be making some wrong decisions if you don’t understand the data properly.”
Advanced data analytics can have a transformative effect on the finance function in a range of areas, such as enabling continuous monitoring, increasing the accuracy of forecasting, and improving decision-making.
But, in practice, not all finance functions are making the best possible use of data analytics. Where are the opportunities for CFOs to use this capability more effectively, and what barriers may be preventing CFOs from adopting analytics to their most valuable extent possible?
From a global perspective, it’s clear that there is room for improvement when it comes to the adoption of data analytics across the finance function. In our “Finance Redefined: Workday Global Finance Leader Survey”—which gauged the views of over 670 CFOs and senior finance leaders around the world—we found that only a minority of CFOs are making extensive use of advanced analytics across key areas of finance today. By advanced analytics, we mean sophisticated approaches and tools that unearth deeper insights, generate recommendations, and make use of predictive techniques.
The survey found that financial reporting was the area where CFOs are most likely to be using data analytics, with well over a third using it for reporting (see list below for the full list of business processes). At the other end of the scale, only a quarter were making extensive use of data analytics to provide self-service data for business leaders.
Business processes where advanced analytics is gaining the most traction in finance (listed in order of priority):
Respondents did indicate that they plan to make more use of advanced analytics in the future. However, the forecasted improvements are modest: in three years’ time, for example, 39 percent plan to use advanced analytics extensively for risk management, up from 31 percent today.
Given that advanced analytics has so much to offer, why have many CFOs yet to fully embrace their potential? When asked about the barriers standing in the way of developing data-driven business insights, CFOs identified challenges in integrating finance and non-finance data as the primary stumbling block. In second place was the problem of system inefficiency, with respondents saying systems issues were leading to their finance teams spending significant time aggregating and reconciling data.
The issue of integrating financial and non-financial data has become increasingly important in recent years as finance leaders have widened their nets to gain insights from larger pools of data. By bringing together finance and non-finance data, CFOs can achieve a more holistic view of the business and benefit from greater operational insights. Non-finance data might include customer data, point-of-sale information, or insurance claim data. It could even include weather data, which may be highly relevant for sectors where demand for goods can be positively or negatively affected by different weather conditions, such as retail and hospitality.
CFOs and senior executives who make better use of non-financial data reported faster forecasting, better responsiveness, and more accurate forecasting.
“A lot of companies are trying to use data in different ways,” comments Naved Qureshi of Genpact. “Finance traditionally just uses whatever works within the finance organization, but they are increasingly using non-finance data from within the company—and also unstructured data from outside.”
The benefits of this approach can be considerable. Research carried out by FSN on “The Future of Planning, Budgeting, and Forecasting”—in collaboration with Workday—found that CFOs and senior executives who make better use of non-financial data reported faster forecasting, better responsiveness to market changes, and more accurate forecasting than those who have not increased their use of non-finance data in the last three years. Those professionals who use non-financial data effectively were also twice as likely to be able to forecast beyond a 12-month horizon.
But while there are many benefits to this approach, integrating non-financial data with more traditional finance data is not without its challenges. For one thing, non-financial data will often be unstructured or semi-structured, in contrast to highly structured financial information. This type of data may, therefore, need to be processed before it can be integrated successfully.
Simply getting hold of the necessary data can also be a challenge. Organizational silos can mean that CFOs need to communicate effectively with different functions in order to gain access to non-financial data, which may be held in different systems across the organization. On another note, it’s also important to identify any regulatory constraints which may apply to certain types of non-financial data, such as customer information.
Making data widely available across the organization lets individuals readily access the information they need, enabling them to make more accurate decisions.
In order to get the most out of non-financial data, CFOs may, therefore, need to overcome certain challenges—whether that means convincing different business functions that access to their data will benefit the company or addressing technical integration issues.
Another notable finding from our research was that only one-quarter of finance teams are making extensive use of self-service data for business leaders. CFOs who are not focusing on this area may be missing an opportunity, as the concept of the democratization of data has gained traction in recent years. Making data widely available across the organization lets individuals readily access the information they need, enabling them to make more accurate decisions. This can be a powerful tool in engaging different parts of the organization and encouraging them to play an active part in strategic initiatives.
In the context of finance, the democratization of data could include empowering business leaders across the organization via the adoption of self-service analytics. By taking this approach, CFOs can enable their peers to combine different data sets and gain a clearer understanding of how the decisions they are making could impact the bottom line.
While the research indicates that overall only a quarter of finance teams are currently tapping into these opportunities, there were significant differences between the different industry sectors polled. For example, 41 percent of finance leaders in the investment management sector said they are making extensive use of self-service analytics. And while insurance also has a relatively high response, other sectors lag behind:
TELUS International’s Rodick is one finance leader who believes that self-service analytics can transform the speed and effectiveness of decision-making, with his team working on a self-service scorecard for the company’s executive team. “The information will be at their fingertips and will then trigger more questions,” he explains. “So, if someone sees something abnormal in the KPIs, they can reach out to finance to dig in—and hopefully we’ll already be digging in. But the idea is they have access to some data right out of the gate.”
For the full research findings behind the “Finance Redefined” global study, read the report here.