Data-focused financial planning hasn’t reached its full potential
The lack of quality data and automated processes can hinder the rate of transformation at many businesses. Studies suggest that the potential for improved IT-finance collaboration is very under-explored. It’s important considering how much financial data supports the development of a positive strategy.
Jason Child, the CFO of Saas business Splunk, describes his time at Amazon within the Financial Planning & Analysis department. In 1999, his team performed a cost-benefit analysis of the free shipping system, a key driver of significant growth at Splunk. They compared free shipping to a 10% discount on each order and quickly found that free shipping generated far more business.
A focus group explored the feasibility of this idea with their CEO and created the concept of a 5-day delay on free shipping, separating it from those that pay for shipping. It resulted in the development of Amazon Prime, which has close to 200 million members, each paying $13 a month. This process is an example of data-focused financial analysis (FP&A), and the potential it has in transforming a value proposition, operational model or even the entire business plan.
Like most data-driven processes, FP&A is influenced by reporting, control and compliance. Inefficient data processes and inadequate financial reporting results in costs in the region of $7.8 billion every year, according to a study by DataRails.
One of the most common problems finance teams face is the overall quality and reliability of their available data. While they may have access to accurate information, the data is vulnerable to inaccuracies due to being shared with other members over time and analysed by multiple teams. Often, data is shared internally via manual copy and paste processes. Financial businesses work in a complex, data-demanding environment but are falling behind when considering automation and data integration processes.
Collaboration between IT and Finance is critical in scenario planning as businesses continue to shift towards a stage of recovery after the pandemic. A report by Workday stated that nearly half of C-suite leaders were concerned their business was incapable of analysing real-time data and making informed decisions or responding quickly to unpredictable changes in the market. Finance leaders are experiencing challenges in delivering, reconciling and assessing high volumes of data. These hurdles are mainly due to less than half of those working in budgeting and planning activities claiming to use digital technologies to do their analysis. In contrast, around three-quarters of sales and marketing teams typically use automation. In short, it is of no value to having an answer to a question a few months down the line when you have to make a critical decision on something in the next few days.
Strategic FP&A is vital for integration, performance management, risk analysis and forecasting for multiple business areas. The reality is that finance teams are allocating too much time towards manual tasks like account reconciliation, investing time in managing and data organisation rather than analysing the information.
Since the pandemic, financial planning and analysis have progressed as businesses actively look for a greater understanding of their figures. Despite the movement in this market, many FP&A professionals still rely on manual tasks, such as correcting errors, updating reports and collecting data.
Factors like operations, technology and productivity all take a lower priority to the bottom line. Revenue forecasts are at the top of importance for CEOs because, ultimately, that is what defines capital flow in a business. Despite this clear recognition, only about 1% of the biggest companies in the world achieve their finance forecasts accurately, according to a study by KPMG. Discrepancies can cause a decline in investor confidence and result in a negative impact on share prices.
Gartner predicts that by 2024, nearly three-quarters of all new FP&A projects will expand beyond the finance world into other business areas. Cloud-based solutions are supporting the potential of extending automation past FP&A to other areas such as HR, sales and supply chain management.
Traditional systems working with finance operations still predominantly depend on manual entries and are more susceptible to errors and discrepancies. AI-based software has increased financial automation. Businesses that apply financial automation can accelerate and improve particular processes like financial close. Often this involves a long monthly process for recording and reporting transactions. Automating selected steps to this area can improve accuracy and reduces time applied to laborious tasks.
Other technologies such as robotic process automation (RPA) allow the auto-creation of documents from the predefined text and screen scraping to validate and consolidate financial data. KPMG predicts that businesses can gain cost savings of nearly 75% by automating finance operations, providing a quicker turnaround and reduced human intervention. Automation cannot replace the human element in financial planning. Instead, it can allow financial analysts to shift their focus away from daily reporting to focus on more insightful analytics and dynamic planning.