The evolution of technology has brought many benefits to FP&A. The latest innovations provide real-time access to data and automate laborious tasks, freeing up time for FP&A professionals to focus on value-added work.

But with any change comes potential mistakes. To help FP&A professionals avoid missteps with their technology, AFP brought together a panel of experts for a webinar discussing data management, enterprise performance management (EPM) software implementation, balancing finance and IT responsibilities, and the trust factor that is crucial to data-driven decision-making for executives.

Mistake 1: Using too many tools

FP&A teams are using an excessive number of tools — more than half of practitioners report using more than eight tools for planning and more than 10 tools for reporting, according to the 2025 AFP FP&A Benchmarking Report: Technology and Data. This leads to inefficiencies and data inconsistencies, and speaks to a lack of an overarching technology strategy, as companies tend to choose software that meets a specific need without thinking about how it fits together with the current systems.

“There are a few problems that come into play,” said Rosemary Linden, President of Momentum CFO. “One is inefficiency. Let's think about this. When you have eight to 10 different tools, that means there are eight to 10 different applications that you and your team need to learn and master. They are also expensive to maintain — you likely have licensing fees for each one, and you may also need IT and external consulting support.”

It's very important to make sure everything is talking to each other, and that data is flowing consistently between the systems. Using multiple tools increases those risk factors and introduces the risk of data inconsistency.

“You need to have really good data governance,” said Linden. “Make sure your data is clean and flowing from one system to another so that when you produce reporting, or you produce plans and forecasts, you know there's a single source of the truth — that you're not going to get different results from different systems.”

While a “best of breed” approach (multiple vendor solutions for various business process domain areas) may work for some organizations, “you must complete the appropriate cost-benefit analysis,” said Philip Peck, Vice President, Finance Transformation & Advisory Services for Peloton Consulting. “Is it better to take that path or to choose an integrated technology solution platform from one vendor that addresses the balance of your FP&A and finance business need? The latter approach is specifically designed to mitigate issues associated with proliferation of tools and technologies.”

Mistake 2: Undervaluing the relationship between finance and IT

What is the right amount of technical skills for finance to have, and what needs to remain with IT? It’s clear that as technology advances, finance professionals’ need for technical skills also increases.

“I have been a long-term believer and a supporter of integrating basic technical skills into your core finance strategy,” said Kavin Soni, Financial Analyst for Google. “It helps in the long term to hire people who have both basic finance skills and essential technical skills like SQL & dashboarding because candidates would be able to start delivering from day one, and that would also decrease their dependency on IT counterparts.”

Still, it is generally agreed upon that IT should remain in charge of security, system maintenance and governance.

“There’s a difference between what FP&A does and what IT does,” said Linden. “FP&A should focus on business intelligence and data visualization, while IT ensures system security and functionality.”

Linden argued that it’s valuable for FP&A professionals to be ‘super users’ of the systems crucial to their work, such as an EPM, but that their knowledge doesn’t need to go beyond that. “It’s valuable to understand how to use BI and data visualization tools to present information and tell a story to executives, as well as to know how databases work — but you don’t necessarily need to do the coding,” she said.

Bryan Lapidus, FPAC, AFP’s Director of FP&A Practice, added, “There's a certain base level that everybody needs for technology, but then you have to make a decision: Do you want to join a finance and technology specialty group? Do you want to stay on the finance side, or do more in management or as a business partner? Everyone has to decide which path they want to branch off on once they've hit that base level of technological competence.”

Mistake 3: Underutilizing your EPM system

The FP&A Benchmarking Survey found that 71% of FP&A professionals use an EPM tool on at least a quarterly basis, but they’re primarily using it for control and consolidation, not for advanced planning and forecasting.

EPM tools are serving as “catchers’ mitts, a repository for plan and forecast information, a single version of the truth,” said Peck. “But we’re not leveraging their full capabilities like scenario planning and integrated business planning. That's the secret sauce and the value-add that a robust, world-class EPM solution should deliver.”

In order to unlock the full capabilities of an EPM tool, you must first have a thorough understanding of the underlying data. Where organizations fall short, Soni explained, is when “you have this new tool that is onboarded and now employees are advised or recommended to use this tool without really understanding the data underneath or how it connects to different things.”

Implementing a new EPM system requires a plan that accounts for the initial deployment, ongoing maintenance and alignment with the ever-evolving organization. “The ‘measure twice cut once’ adage applies here,” said Peck. “Both when you're doing your deployment, and then ensuring you have the proper support system for that EPM ecosystem as the organization continues to evolve.”

To that end, you have to have full management buy-in for these tools. “Management may sign off on implementing the EPM, but they're not thinking further down the road about what it takes to maintain that system, upgrade that system and make sure that the funds are available in the budget for that,” said Linden.

Few organizations factor EPM maintenance into their budget despite its importance. “You can't skimp on the maintenance,” emphasized Lapidus. “Once you've gone through the effort, you've put it in place — you're not done. There is maintenance, there is upkeep. And the more sophisticated it is, the more complex your system is, the more you're going to have to spend on that maintenance throughout.”

Mistake 4: Overlooking trust in data-driven decision-making

Many finance professionals have a story to tell of management finding one number that is incorrect, or that they don’t trust, and tossing out the entirety of the report. If management is struggling to trust the data finance is presenting, it could be due to a lack of standardization, poor tooling or inconsistency between data sources.

If the output is not trustworthy, “as an exec, I would get confused, not use any of the tools and then fall back on the things that I know,” said Soni. “I would make decisions based on judgments and intuition.”

Soni went on to suggest that educating management on the power of data and improving its reliability — through better standardization, planning and maintenance — could increase trust in data-driven decision-making.

“Executives tend to be smart, and many, if not most of them have lived inside of their organizations for a long time. They know what's underneath the iceberg,” said Peck. “It’s their job to layer in the human element on top of everything that's brought to them.”

Another factor to consider is whether finance is doing a good job of explaining the data. “Maybe you think you're explaining it well, but the executives don't,” said Linden. “Seek feedback. Just like you might seek feedback on whether your EPM system is meeting the needs of the end users, conduct a team effectiveness survey. Ask for feedback from executives about the information they're receiving and what might make it more useful to them.”

Ultimately, data and judgement should be complementary; data should inform judgment, and decision-making should build on top of data.