Future-Proofing Financial Planning: How CFOs Can Benefit from Autonomous Planning

Persistent inflation and slowing economic growth have led to a code-red situation for businesses globally. Market dynamics are in a constant state of flux; from a sudden shortage of raw materials to the risk of violating regulatory standards, just to name a few.

As a CFO, you need to rely on complex financial models and contingency scenarios to make decisions that better mitigate risk and ensure optimal business performance. This requires responding even faster (almost in near real-time) to opportunities and threats by cutting out the guesswork and instead executing plans on the fly based on accurate data analyses.

CFOs are currently transitioning towards autonomous financial planning and analysis (FP&A) in order to attain heightened agility. This entails the use of self-learning and self-correcting financial plans and forecasts that do not require any input from finance professionals or business analysts. In this blog, we have discussed what autonomous financial planning is, how it benefits the office of the CFO, and how you can adopt CPM tools that help build faster, more accurate financial planning and analysis processes that run on autopilot.

What Is Autonomous FP&A?

Autonomous financial planning involves working with a self-learning and regulating system of financial data consolidation, modeling, reporting, planning, and analytics facilitated by AI and ML. It can create forecasts and reports and make recommendations based on the changing market factors on its own. Consider it as the application of self-driving car technology to the realm of FP&A.

Under this model, you can act on actionable insights quickly without spending hours connecting the dots between various data inputs. This way, less time gets spent on oversight and more on execution.

Autonomous financial planning isn’t the same as automation; in fact, it goes beyond it. While the latter is about automating repetitive tasks with minimal human input, the former offers self-correcting financial decision-making, cutting time to insight significantly. CFOs, as a result, can become even more agile to respond to fluctuating market factors and better align their resources.

Why is it Important for CFOs?

Due to the impact of the 2020 pandemic, there has been a notable increase in the emphasis placed on autonomous financial planning. CFOs and FP&A professionals are now faced with the challenge of planning and forecasting with greater certainty while relying on multiple business inputs. This includes accurately determining credit limits for suppliers, establishing appropriate pricing, anticipating potential risks in the supply chain, and mitigating staffing shortages – all with the goal of maintaining cash flow and optimizing resource allocation.

On the other hand, businesses that rely on outdated FP&A approaches, like manual and error-prone processes based on Excel, will face an increased risk and be unable to keep pace with the rate of change. Here are a few reasons that explain the rise in autonomous financial planning:

1. Digital finance transformation: Digitizing financial and planning activities on par with operational and strategic initiatives is the cornerstone of finance transformation. This is driven by the need to collect, harmonize and process vast amounts of data via tools that provide consolidation, reporting, planning, and analysis solutions, to facilitate agile decision making.
2. Insufficiency of legacy FP&A: Finance professionals are shifting their approach to handling financial information by reducing their reliance on manual methods like spreadsheets. They are also broadening their focus from finance-centric Financial Planning and Analysis (FP&A) to a more cross-functional approach, and moving from historical data to more agile reporting processes.
3. Rise in artificial intelligence and machine learning: The post-ChatGPT world has led to a new wave of AI adoption and integration, where the simplest task can be accurately executed with a basic prompt.
   For corporate finance, AI and ML have the capacity to lean on historical data to make precise adjustments on pricing, expected earnings, and cost margins, all within minutes if not seconds. This agility is expected to become a major source of competitive edge for businesses to survive in today’s economic climate.
4. Greater uncertainty: While the pandemic has accelerated the adoption of financial transformation, slowing economic output, broken supply chains, and rising inflation has adversely impacted organizations’ ability to make business moves with confidence. CFOs thus need to process far more inputs and variables to be able to accurately assess risk.

4 Benefits CFOs can Achieve from Autonomous Financial Planning

We have looked at what autonomous financial planning is and why it’s critical. Here are 5 key benefits you can achieve from adopting autonomous financial planning:

1.     Reduce time-to-insight and time-to-value

The status quo would have CFOs work with data from multiple sources and departments. The processed data would serve as the basis for forecasting models and plans to generate actionable insights that best reflect evolving market conditions.

The only problem: financial plans and models have to be continuously fed with the latest data to maintain their accuracy. Because of this, turnaround times for analysis and planning are likely to become longer, which can create a misalignment between the decisions implemented and the current situation.

Autonomous financial planning, on the other hand, can help bridge this gap. Unlike legacy FP&A, it relies on a self-learning and correcting mechanism that would adjust according to the changing inputs and variables so it can provide the best recommendations for the most fruitful outcomes.

2.     Better data quality

Computers are usually thought to be far more accurate at making calculations than humans.

One characteristic of legacy FP&A methods is how error-prone financial reports and models can become. For example, the use of spreadsheets makes financial planning and analysis tasks wrought with missing, invalid, and unstandardized data.

However, under autonomous financial planning methods, data collection and integration from disparate sources processes are optimized with advanced AI and ML algorithms to prevent any errors from slipping through the cracks. The insights generated would be far more precise and in line with reality.

Automation can eliminate manual and repetitive tasks, but autonomy takes it a step further by removing human intervention in data preparation stages and optimizing decisions accordingly. With autonomy, you can focus on utilizing insights to create accurate and flexible plans that cater to multiple predicted scenarios.

3.     Improved cash flow earnings

Having autonomous financial methods can also lead to better cash flow management and earnings. CFOs can execute AI-assisted insights much faster to secure credit, limit low-priority spends, source quality inventories in time, and avoid production delays.

4.     Better compliance management

Companies that do not anticipate supply chain disruptions run the risk of violating various compliance and regulatory obligations. Failure to make payments on time, for instance, can result in contract breaches, legal disputes, and penalties. Additionally, the inability to obtain the necessary raw materials to manufacture goods that comply with regulatory standards can lead to non-compliance issues.

3 Mental Shifts CFOs Need to Implement Autonomous Financial Planning

Autonomous financial planning may seem like a passing fad or buzzword for numerous mid-sized and enterprise organizations. Nevertheless, according to Gartner’s research, 80% of CFOs plan to increase their investments in AI over the next 2 years to automate their FP&A processes.

“80% of CFOs we surveyed in 2022 expected to spend more in AI in the coming two years, for example. Around two-thirds of finance leaders we surveyed think their function will reach an autonomous state within six years”

– Matthew Mowrey, Senior Director Analyst @ Gartner Finance

However, there is still a hesitancy among CFOs to entrust decision-making to AI, which may impede the shift towards autonomous corporate finance. Here are 3 mindset shifts that must occur for this to be avoided.

1.     Shift from ‘control’ to ‘respond’ mindset

Although CFOs may recognize the potential advantages of adopting autonomous financial planning, they might be hesitant to delegate excessive authority to machine learning algorithms and AI to handle the task and remain agile in responding to unexpected developments.

Gartner analyst, Dennis Gannon remarks: “CFOs tend to see technology as a tool but rely on people to make decisions,” said Gannon. “Even when the evidence shows that technology makes better or more accurate decisions, people are still reluctant to trust it.”

To truly reap the benefits of autonomous finance, CFOs need to approach AI as a trustworthy mechanism that is capable of assessing risks and making decisions on the go. For this, they will need to broaden the scope of autonomous financial planning and test (or apply) across the entire organization instead of limiting it to finance teams to gauge its results.

2.     Bridge the skills gap in AI and machine learning

As the interest and advancement in AI and ML grow, so should the skills in processing different types of technologies to scale FP&A over time.

For example, companies will need to be adept at identifying and delivering various use cases such as blockchain smart contracts to expedite transaction processing times, predicting future trends using historical data through machine learning, and automated financial forecasting and decision making to lower turnaround times.

3.     Invest in scalable, cloud-based CPM tools

Corporate Performance Management (CPM) solutions have been instrumental in laying the groundwork for digital financial transformation, and they have the potential to facilitate the adoption of autonomous finance. Modern, cloud-based solutions, such as Acterys, have the capacity to create a self-regulating system, where business data is :

• Consolidated from multiple source systems
• Automatically modeled for optimal processing
• Automatically fed into a variety of financial reports
• Updated across multiple financial plans, forecasts, and what-if scenarios
• Consumed for generating insights from NPL through integrated AI tools like ChatGPT-4
• Reflected in analytics and visualizations
• The aim is to establish a link among departments and create an integrated data model (xP&A)

With the right CPM tool, you can lay down the foundation for a true autonomous financial planning ecosystem that is fast, reliable, and exudes hyper-intelligence in every decision it makes. This can open a whole new world of possibilities for CFOs as they will have greater transparency and insight into FP&A tasks and have higher confidence in executing decisions in near real-time.

Taking the Step Towards Autonomous Financial Planning with Acterys

Acterys is a unified, Power BI-based CPM tool that provides the right arsenal to CFOs to set up an autonomous system for performing FP&A tasks with unparalleled accuracy, flexibility, and speed. It revolutionizes autonomous planning by combining advanced AI algorithms and real-time data analysis for improved business decision-making.

Craig Schiff, CEO of BPM Partners, comments:

“Acterys fully leverages Microsoft technologies and provides dynamic planning. They support finance transformation; they have consolidation. What’s unique about them is that they offer bi-directional integration with both Power BI and Excel, either of which can be used as a primary interface. So if you like to work and live in Power BI, it can do that. You can pull up data and you could also push-back and write data from Power BI.”

Conclusion

It is crucial for CFOs to embrace autonomous financial planning to swiftly adapt to volatile market conditions and mitigate uncertainty. By implementing an AI and ML-powered financial reporting system that is capable of self-learning and self-correcting, businesses can achieve greater data precision and faster access to insights. This can enable them to capitalize on market opportunities and proactively address potential challenges to enhance overall business performance.

Key Takeaways:

1. Autonomous FP&A leverages AI and ML to create self-learning and self-regulating financial data consolidation, modeling, reporting, planning, and analytics systems.
   
2. Autonomous FP&A can generate forecasts, reports, and recommendations based on changing market factors without constant human input.
   
3. CFOs are increasingly turning to autonomous financial planning to cater to inflation, economic uncertainty, and market fluctuations.

    

4. Autonomous financial planning allows CFOs to respond faster to market dynamics, optimize resource allocation, and ensure better cash flow management.

    

5. Autonomous FP&A benefits CFOs by providing reduced time-to-insight, enhanced data quality, improved cash flow management, better compliance management, and assisting in mental shifts.
   
6. Acterys is a Power BI-based CPM tool that empowers CFOs to implement autonomous financial planning with accuracy, flexibility, and speed. It combines AI algorithms and real-time data analysis to revolutionize planning and decision-making.

FAQs

1. What is Autonomous Financial Planning (FP&A)?

Autonomous Financial Planning, or FP&A utilizes Artificial Intelligence (AI) and Machine Learning (ML) to create self-learning and self-regulating systems for financial data consolidation, modeling, reporting, planning, and analytics. It can generate forecasts and recommendations based on real-time changes in market factors without constant human intervention.

2. Why is Autonomous FP&A important for CFOs?

Autonomous FP&A allows CFOs to respond rapidly to the challenges such as inflation, market changes, and economic uncertainties, by optimizing resource allocation, improving cash flow management, and enhancing compliance.

3. What are the key benefits of Autonomous FP&A for CFOs?

The benefits include:

• Reduced Time-to-Insight: Quicker access to actionable insights.
• Enhanced Data Quality: AI and ML algorithms improve data accuracy and standardization.
• Improved Cash Flow Management: AI-assisted insights aid in cash flow optimization.
• Better Compliance Management: Anticipation of supply chain disruptions and enhanced regulatory compliance.

4. Why is data precision important in Autonomous FP&A?

Data precision ensures the insights and recommendations generated by autonomous systems are reliable. This precision allows CFOs to make informed decisions and adapt to changing market conditions effectively.