Continuous insights help finance lead with timely decisions
Forecasting capabilities are shifting into a higher gear, and finance leaders need to make sure they’re ready to accelerate the value they bring to the business.
The development of more powerful AI tools has created an opportunity for finance leaders to leave their static forecasting methods in the past and deliver continuous forecasts that inform business strategy in real time.
During a webcast on modern forecasting for finance leaders, Grant Thornton professionals discussed the benefits that AI-enabled forecasting can deliver and how finance leaders can bring these capabilities to life within their organizations.
“The pace of change that’s facing CFOs has made the traditional planning cycle harder to rely on,” said Mike Hennessey, Partner — National Finance Transformation Lead for Grant Thornton. “Finance teams can become more adaptive, data-driven and decision-ready while maintaining trust, governance, control and confidence.”
The opportunity is clear, but adoption remains uneven. Many finance teams are still stuck in static planning cycles, as less than one-fourth (22%) of the webcast audience reported using continuous or rolling forecasts. Continuous forecasting gives businesses the insights they need to pivot quickly when conditions change in their environment, enabling agility and real-time reaction that maximizes value creation.
The driver behind these insights is an AI-driven forecasting model that updates immediately when underlying business drivers change. When volume, headcount, pipeline, price or external factors shift, the model shifts with them.
Currently, the gap between a shift in one of those factors, which constitutes a business signal, and the forecast update it should trigger is too long because FP&A teams spend close to half their time gathering and reconciling data instead of interpreting it.
AI frees them to interpret the data and provide better, faster input into strategic endeavors. AI also can look across a wide set of business signals and weigh all of them at the same time to fully understand their effects on a business.
“You have live scenarios running against the same governed data model that you can interrogate immediately when a business driver changes or when leadership questions arise,” said Austin Rowe, a Manager in Grant Thornton’s Finance Modernization practice.
Clean data delivers better insights
The key to it all, though, is the data that feeds the models, said Protos Security Senior Vice President Ryan Wessendorf. Protos recently engaged Grant Thornton to assist with its transformation to an AI-driven, continuously updated forecasting model, and the company’s first step was to address the data that would be delivered to its AI platforms.
Protos has a talented data and finance team that spent months probing the various dimensions of its data to make sure it was clean. This was challenging because Protos has undergone significant M&A activity in recent years, so its data needed to be integrated and normalized carefully.
Processes also needed to be updated so that future data would be cleansed and auditable before it reached the AI platform.
“Once you have normalized data that you can rely on over time, you have a solid baseline to work from and you can trust the output of the model,” Wessendorf said.
Strong data governance creates new opportunities at companies that are data-rich but insight-poor because their information is fragmented across systems:
- Revenue and pipeline data reside in customer relationship management systems
- Supplier and vendor data reside in a procurement tool
- Payroll data may be scattered across regional human resources platforms
“Every one of those systems is doing its own job correctly, and collectively the fragmentation makes a single trustworthy answer difficult to produce,” Rowe said.
To prepare data to enable AI-driven forecasting, organizations need to:
- Connect reliable automated feeds.
- Resolve data across the entity so that the same customer isn’t represented in different ways across different systems.
- Create fixed business logic and consistent definitions so all systems work from a single source of truth.
“AI is a magnifying glass on data quality,” Rowe said. “It makes good data more useful and bad data more dangerous. Without a clean source of truth and a disciplined taxonomy, you’ll get wrong answers faster instead of a better forecast.”
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Resistance to change must be overcome
Another challenge to finance modernization can come from employees who are skeptical of AI. When AI platforms replace the manual spreadsheet manipulation they have been performing for years, finance employees might be skeptical and ask whether their jobs are in jeopardy.
Management needs to show these employees how AI actually will enable them to focus on the most impactful parts of their jobs and use the skills that will add true value to the business. Instead of making entries into spreadsheets, they can probe deeply into the data that AI provides to discover, for example, the reason that margin is compressing in the Midwest.
Armed with this information, finance employees can propose solutions that will benefit the business.
“We’re giving them back time to not just empower them and empower the firm, but to make them better as individuals and professionals and allow them to accelerate their growth,” Wessendorf said.
At the same time, even though employees are not manually building the data files, their judgment is essential. For example, although AI is building variance reports, human expertise is required to understand which variances are real, which are just noise and which need immediate correction from the business.
When finance employees work in this manner with advanced technology, they bring faster, more beneficial insights to leadership. This enhances the value of the finance function and the people who work within it.
“You get credit for making a massive impact every time by bringing real insights to the table,” Wessendorf said.
That’s the ultimate value of AI-driven forecasting. It gives FP&A a more important seat at the steering wheel and drives the business in the right direction more quickly as AI shifts operations into a higher gear.
Watch the full on-demand webcast for additional insights.
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This Grant Thornton Advisors LLC content provides information and comments on current issues and developments. It is not a comprehensive analysis of the subject matter covered. It is not, and should not be construed as, accounting, legal, tax, or professional advice provided by Grant Thornton Advisors LLC. All relevant facts and circumstances, including the pertinent authoritative literature, need to be considered to arrive at conclusions that comply with matters addressed in this content.
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