Advancing Analytics: The Path Forward for Finance Leaders, Part One

Today’s CFOs have an eye on more than just the bottom line. They are watching the horizon, predicting what’s coming, and charting the course ahead.

As your organization’s finance leader, the opportunity to better understand the landscape and your business has never been greater. Advances in analytics—powered by digital technologies such as automation and machine learning—give finance teams deeper business insights, and the ability to identify performance issues, predict scenarios, and change outcomes.

It also means finance teams no longer have to look back in time for answers. Advanced analytics can help them look forward and better forecast the future with predictions such as what products and customers are most profitable, or which customers are more likely to pay their invoices on time.

At the same time, technology enables the automation of more financial processes, from accounting to auditing, freeing up finance teams to focus more on analysis and partnering with the business.

Most CFOs recognize the critical need for greater analytics. According to IBM’s “Elevate Your Enterprise, Chief Financial Officer” study, CFOs cite analytics as a key source for the discovery of new growth opportunities, supported by the integration of enterprise data with external market and competitor data.

But despite the value, finance teams remain challenged with putting data and analytics into use. In Workday’s “Finance Redefined: Workday Global Finance Leader Survey,” results showed that only 35 percent of respondents are making extensive use of advanced analytics in key areas such as planning, budgeting, and forecasting.

What are the difficulties? The reasons cited by finance leaders are often the same—disconnected systems and data, too much time spent on transactional work, issues with business partnerships, and a lack of talent. At a recent industry event, Matt Schwenderman, principal at Deloitte Consulting LLP, highlighted two key issues finance faces when it comes analytics: technology and talent. “Analytics is a key way that finance supports a more digital operating model, but we don’t necessarily have the technologies and the talent aligned with that,” he says.

CFOs realize they must begin addressing these challenges now. Without the use of analytics, companies run the risk of making the wrong decisions, ultimately stalling growth and impacting performance.

In this two-part blog series, we will look at three key areas (based on various research studies and interviews with finance leaders) that are critical for advancing analytics in the finance function: a core technology foundation, strategic business partnerships, and leadership.

A Core Technology Foundation

While many finance organizations aspire to advance their analytics, most are still focused on getting the technology foundation right. According to Schwenderman, some are having more success than others. “We have some organizations that are doing incredibly creative and avant garde things with data and insight-driven decisions,” he says. “Others are still relying on what I refer to as human middleware—moving spreadsheet-driven information throughout the organization and walking into very important meetings with varying sets of the same results, arguing about what’s the right number.”

Finance teams often work with data that is spread across disparate systems, with different data definitions. There is no sole source of financial truth to work from, making it difficult to trust the accuracy of data and analyze it for insights. In fact, system inefficiency was cited by finance leaders as the second-highest barrier standing in the way of developing data-driven business insights in Workday’s “Finance Redefined” study.

Jim Kendall, vice president of finance solutions at Aon, one of the world’s leading professional services firms, describes how managing disparate finance systems in locations across the globe impacted Aon’s ability to analyze the business. They faced the same challenges with HR systems as well. “As we’ve grown through acquisitions, the diversity of our systems and processes became a real issue for us,” he says. “It was difficult for leadership to have a global view of our people and financial results—we didn’t have a single source of analytics across finance and HR.”

How can system inefficiency impact performance? Consider global companies that sell the same products and services in multiple countries. They are using different financial systems and applying different data definitions to activities in each region. As a result, each location may be interpreting and reporting on the performance of the same product and service lines differently than required by the corporate office. This can lead to faulty analysis and impact decisions, such as parts of a business appearing more profitable than they actually are.

Many organizations are moving financial management off legacy finance systems to a cloud-based global system.

Working between multiple systems also makes it difficult for finance teams to focus on analysis—they are spending more time gathering and reconciling data. Robynne Sisco, co-president and CFO at Workday, saw this firsthand in previous organizations she worked for. “Each month finance would have to close the period, access the data, reconcile it, format it, and analyze it. By the time we delivered the numbers to the business, it was two weeks after the period ended and too late to take action,” she says.

Finance must address these systems challenges if they want to advance their analytics. In “Advanced Analytics and the CFO,” a Harvard Business Review Analytic Services white paper sponsored by KPMG, R. “Ray” Wang, principal analyst and founder of Constellation Research, emphasized the importance of addressing these barriers. “Companies must embark on this process and systems improvement journey in order to lay the necessary foundation for advanced analytics,” he says.

Wang suggests several ways to begin this process: “Standardizing data definitions; integrating and rationalizing core financial systems; and leveraging the cloud for scalability, standardization, and coordination among systems are key first steps in that journey,” he says.

Many organizations are moving financial management off legacy finance systems to a cloud-based global system, enabling finance teams to standardize processes across their organizations and bring all financial data into a single system. Cloud-based finance systems that have analytics built into the application give finance the ability to transact, analyze, and report on real-time data all from the same place—capabilities not possible with traditional systems.

Having this foundation gives finance the access and confidence to use data effectively. When it comes to  analytics, “The first thing is having credibility in what you are producing. If you have that credibility, you can progress faster and forward more quickly,” says Schwenderman.

A Single Cloud-Based System for Finance

Kendall describes the benefits of moving to a global cloud-based system for finance and HR at Aon. “Having a single system for finance and HR has improved our analytics capabilities, enabling us to take action directly from reports,” he says.  “Our colleagues around the world have access to real-time data that allows them to better understand how the business is running and how their actions impact profitability and expenses. We can drill into the variances that matter, understand why, and take actions all in one system.”

Kainos Software Limited, one of the longest-standing independent digital technology companies headquartered in the UK, also moved off legacy systems to a single system for finance and HR to support the company’s rapid growth and strategic goals. Peter McKeown, group head of finance at Kainos Software Limited, says the change has had a significant impact on how finance works with data. “Having finance and HCM on one platform ensures one source of the truth for all HR and financial information, increases the buy-in across the business, and reduces the number of errors or reconciliations required,” says McKeown.

He also says his team is now focused on more strategic work. “Implementing the single cloud-based system helps me empower my senior staff to spend less time in the weeds or on finance processing, allowing them focus more time on value-add activities.”

Having the right core technology foundation to work from will be paramount.

As finance teams work to better leverage the data they have, many are also thinking about how to leverage technologies such as artificial intelligence and integrate external data to improve analytics. Predictive analytics can be used to help finance evaluate patterns within different types of data and then identify risks, such as anomalies that might indicate fraud.

Bringing in external data—such as CRM, point-of-sale, or data from industry-specific systems—into the finance system of record can help leaders better understand performance, such as the operational drivers behind revenue and expenses. Schwenderman describes why this is important. “The more we can add those external data sets, the more precise our predictive models can be. Then I can make better resource allocations as a CFO. I can provide better guidance to the street and generate greater shareholder value.”

Sisco underscores the importance of having the right technology foundation. “As companies look to advance their analytics—by leveraging technologies such as machine learning and bringing in more operational data—having a single version of the truth becomes even more important.”

But many finance organizations still have a ways to go when it comes to making these advances. In the Workday “Finance Redefined” study, finance leaders cited the ability to integrate finance and non-finance data for deeper insights as the number one barrier to greater analytics.

Having the right core technology foundation to work from will be paramount. The Harvard Business Review Analytic Services white paper “Advanced Analytics and the CFO” affirms this, stating that, “Machine learning and artificial intelligence (AI) will shift the focus from operational efficiency to enhanced data and insights, which can deliver a quantum leap in performance. CFOs need to ensure they have baseline digital capabilities—specifically around data and processes—to capitalize on these future investments.”

(Read part two of this blog series, which looks at two other areas that are key to advancing analytics in the finance function: strategic business partnership and leadership.)