Data is everywhere, yet without the capability to turn information into actionable insights, data is merely the equivalent of raindrops falling endlessly into the ocean. The truth is that many companies are struggling to put their data to work, leaving a hugely valuable organizational asset largely untapped. A McKinsey study, “Designing Data Governance That Delivers Value,” found that employees spend around a third of their time on non-value-added tasks due to poor data quality and availability; those in finance spend more time on sourcing, aggregating, reconciling, and cleansing data, in addition to manual reporting, than any other group.
This conversation is not simply a finance one. IT teams are looking to simplify systems, reduce spend, and decrease the amount of effort needed to maintain legacy systems. Ever-increasing demand from the business for actionable data and insights means IT-centric processes are unfortunately becoming the bottleneck to organizational agility.
Finance is being asked to provide more frequent guidance than ever before and must shift its focus from delivery of core financial processes to providing guidance and strategic partnership across the enterprise—a shift made possible by accelerating digital initiatives and the cloud. Business leaders are asking for fresh insights and new ways of looking at business performance—often requiring the blending of multiple, disparate data sources. For finance, the pressure is on to turn data into action.
The challenge for finance is that legacy approaches, centered on manual processes, weren’t built to handle the massive amounts of data being generated and captured by modern enterprises. Even in these uncertain times, very few finance leaders plan to postpone initiatives to modernize their data management platforms—some are accelerating their timelines. This is significant, as research from The Hackett Group found that, going into 2020, 88% of finance organizations had a major transformation initiative underway, and 96% were planning to launch one in the next 12 to 24 months.
How does the relationship between the CFO and CIO work with the emergence of tools, such as cloud computing, which have transformed the delivery and management of IT? There is little doubt that we have entered a new era of technology ownership. As cloud enables finance to have better control over the way it manages data, the function also has an increased responsibility and a huge opportunity to drive the digital agenda.
According to Oliver Wyman’s report, “Digital Transformation of the Finance Function,” finance is well-placed to make the move from financial advisor to the owner of an analytical hub, empowering the business with real-time data and actionable insights. In addition, the emergence of automation is driving down the cost of delivering comprehensive insights back to the business, leading to increased expectations of what finance could and should deliver.
Below, we look at five steps finance can take as it moves toward becoming a decision-ready organization.
Any report that requires IT resources or input represents a potential delay. That can hold up decision making and lead to a host of potential problems for finance and its stakeholders. Legacy systems handed the governance and management of data to IT by default. That’s just how things work in the on-premise world. Today, data ownership needs to be managed by those closest to the business. These teams, including finance, must be empowered to own the definition, implementation, and maintenance of critical components such as the financial data model, accounting rules, mappings, calculations, and metrics. Decision-ready organizations must be agile; they must have data at their fingertips in order to make fast calls based on the latest information.
Directly linked to the point on data control, increasing the speed at which insights can be gathered and shared is also becoming a finance priority. Finance users must be able to efficiently manage and transform data for any type of reporting, analytics, or planning use case. Time to insight relies as much on the user experience as it does on having the right data.
Financial analysts understand the value of using data preparation tools that are both visual and intuitive, helping them create stories to share better insights with executives. This shift to finance being the shapers of their own future demands tools whereby financial analysts can create, maintain, and adjust data transformation pipelines without the need to code. In other words, with little or no IT intervention.
One of the biggest challenges facing finance professionals, and indeed the broader business, is a lack of data consistency. For example, if finance and HR hold two different contradictory versions of headcount data, but this was accrued from a variety of sources, coming to any form of consensus is going to be problematic.
Today, more than ever, businesses need to see the same set of facts, provided by reporting and analytics tools that meet the needs of a growing set of stakeholders with different needs. The impact of the COVID-19 lockdown brought this need into sharper focus, as finance and accounting users, managers, and executives, as well as lines of business, all required a consistent and collaborative view of performance data. Without in-person meetings and “water cooler moments” in the office, the trust and integrity of data becomes paramount.
To build this complete view, finance should be able to seamlessly integrate real-time financial transactions and historical data from legacy systems, in addition to operational data from industry-specific or homegrown solutions, with flexible dimensionality directly from the general ledger.
One of the biggest challenges facing finance professionals, and indeed the broader business, is a lack of data consistency.
Part of the ongoing collaboration between finance and IT is about enabling the CFO function to create, maintain, and adjust its own financial data model without the need to code. The shift to the cloud enables finance to take advantage of data models that are explicitly designed to adapt to change. On-premise tools lack flexibility and require IT input at virtually every stage, from deployment through to management and the creation of reporting data. At the same time, with data and reporting contained in one platform, IT involvement can be reduced when creating reports or running analyses, improving efficiency and reducing overall costs associated with decision making.
Building a flexible data model is explicitly intended to support change, for example, to accommodate the addition of new data sources, adjustment of mappings, addition or removal of dimensions and attributes—without the months of effort commonly required with legacy approaches. Getting to this point, whereby IT enables finance to become the master of its own destiny, requires a cultural and technological shift, but this is something that both parts of the business must embrace if they are to become less transactional and more strategic.
Similarly, IT can empower finance and its users, allowing them to control how data enrichment rules are defined and configured. In today’s world, where companies have amassed a sprawling estate of tools, having a single point of maintenance for accounting rules across all operational activity is key. At Workday, we see that with many of our competitors, these rules often exist in separate silos, creating unnecessary maintenance overhead.
Data should be actionable, integrated with financial processes, and extensible, available to data science teams for advanced analytics and modeling, as well as application developers for building custom extensions and interfaces.