AI in FP&A – Enhanced Reporting in an XP&A World

Do you know if your organization is using the best corporate performance management (CPM) reporting process possible? Does the CPM software leverage Artificial Intelligence to produce better reporting? Many organizations resort to ad-hoc analysis to bolster finance and operational reporting. But management reports built with legacy financial reporting tools are not flexible enough to react to what’s happening in the business during turbulent times. Meanwhile, current reporting methods typically focus on what happened in the past and give little insight on how to improve the organization’s performance going forward. Now is the time to take the best of modern finance reporting and extend it across the enterprise through the power of Artificial Intelligence. Read on to learn more.

AI for Intelligent FP&A – Reporting in an xP&A World

Financial Planning and Analysis (FP&A) transformation in a data-driven world is well underway. Today’s best planning solutions, however, are more accurately described by Gartner’s [1] new terminology “eXtended Planning & Analysis (xP&A).” According to Gartner, XP&A is the evolution of planning, combining financial and operational planning on a single composable platform. With xP&A, business planning, and forecasting are not only streamlined and integrated across every part of the organization but also supercharged with artificial intelligence (AI) (see Figure 1).

Why does this matter?

The Office of Finance is the central hub of the enterprise, and with xP&A comes both an expansion in responsibility and an increase in demand for reporting, analysis, and insights. As the consumer, line of business managers want the reports to be progressively more forward-looking and, in some cases, predictive in nature.

In response to the constant pressure to provide the golden source of reporting, Finance has begun to enable AI enhancements that assist with forecasting and operational analytics to increase collaboration across the organization and drive more effective decision-making. The result is accurate, fast, and forward-looking enterprise reporting that helps accelerate the xP&A journey.

Artificial Intelligence Defined

While still a concept many companies are trying to understand fully, AI is not only real but also the future of FP&A and its subsequent evolution to xP&A. In simple terms, AI leverages computers and machines to ingest information and instructions, learn from interactions with human beings, and respond to new situations to mimic the problem-solving and decision-making capabilities of the human mind. AI goes beyond technologies that merely automate rules-based activities such as robotic process automation (RPA).

AI can recognize patterns and learn to adapt to new situations, giving Finance leaders a substantial competitive edge.

Why are organizations turning to AI-enriched reporting?

Many Finance leaders agree that their business partners in Sales, Marketing, Operations, and HR want a better understanding of the information they receive from Finance, and they expect Finance to simplify it for them. The Office of the CFO thus faces constant pressure to deliver timely, accurate reporting to support effective business decision-making. While not the complete solution for FP&A, AI is a powerful tool that enables Finance to better meet the business’s needs and expectations for reporting.

Reporting demands of the next-generation FP&A Model

Every Finance leader feels the challenges of producing monthly reports in the traditional FP&A environment and then chasing down supporting data to explain the never-ending anomalies. Imagine walking into the office knowing that the AI-powered xP&A platform has obtained the anomalous data, reviewed the data, corrected the data, and explained the correction within the core financial reporting packages – all without human interaction. The updated data can then be fed into various reports that drive organizational intelligence. As a result, managers can better understand the organization’s performance in conjunction with priorities and understand the health of the enterprise (see Figure 2).

Traditional FP&A   

•   Annual Planning/Quarterly Forecasting
•   High-Level Financial Plan
•   Data Siloes & Disparate Systems
•   Top-Down/Bottom-Up
•   Dependent on Expertise of Planners

New xP&A

• Continuous, Real-Time Planning & Forecasting
• Granular Operational Models & Solutions
• Unified Platform for Planning
• Driver-Based Simulations, Scenario Planning
• Augmented with Predictive Forecasting & AI/ML

Conclusion

Will AI eliminate all the uncertainty in the world of Finance? The answer is no, but the promise of folding AI services into the FP&A functions is very achievable, giving Finance new ways to ask WHY.

Every individual up and down the Finance team feels the squeeze as time begins to tick away on month-end activities. As an example, forecast validation is slow, tedious work as Finance perpetually checks and rechecks numbers to support management reporting. For many organizations, the simple response is to throw more bodies at the problem but doing so doesn’t generally provide the gains those organizations were seeking.

But what if a single team member could be trained to run infinite forecast validations to increase forecast accuracy, freeing up the rest of the team to collaborate with business partners to improve performance?

In some organizations, that single team member, called AI, has already proven that it can take on the heavy lifting of forecast validation. That leaves Finance to focus on questions that really matter, leading to elevated business partnerships and delivering accuracy across the enterprise.

Learn More

To learn more about how FP&A teams leverage AI for more than just reporting, stay tuned for additional posts, or download our interactive e-book here.