In a time of financial insecurity and the rise of AI technology being integrated to many sectors and areas of life, Matt Rodgers, Managing Director, EMEA at OneStream Software, dives into the current state of financial forecasting in uncertain times.
As we enter a new financial year, finance leaders feel confident about the year ahead. The impact of factors like Brexit, the pandemic and inflation, which once caused significant anxiety, appear to be receding. A glimmer of optimism pierces the fog of uncertainty that has shrouded businesses in recent years.
However, there is still a degree of caution from UK CFOs. While finance departments are feeling optimistic, significant business decisions, such as expansion plans or new product launches are still on the back burner. All this points to a hint of continued uncertainty and financial forecasting technology will be the golden ticket for finance departments looking to make considered business decisions for the coming years.
Finance departments should be thinking beyond traditional finance tools and look to use financial forecasting technology that incorporates Artificial Intelligence (AI) And Machine Learning (ML). In the age of uncertainty, AI and ML are on the side of finance departments, offering the most up-to-date forecasts to make better future financial decisions.
Strategic planning and modelling
Strategic planning and modelling, built on trusted, verified financial data, are the cornerstones of sound financial decision-making. They propel long-term strategy, allowing you to analyse multiple potential scenarios at once.
But it doesn’t stop there. These models go beyond static plans. They empower finance departments to stress-test assumptions and adjust key drivers, pinpointing how even minor changes can impact your financial outlook. This foresight allows for proactive adjustments, maximising chances of business success.
Furthermore, strategic planning and modelling allow finance departments to delve into ‘what-ifs’ scenarios. This is where AI and ML come into play. AI/ML for predictive analytics can create thousands of demand planning forecasts on a daily and weekly basis to better understand key drivers and have more accurate forecasts and plans, leading to better resource allocation, inventory and labour plans. This comprehensive analysis ensures finance teams select the path that best aligns with long-term goals.
The power of foresight
The CFO role is changing. They are being asking to do more, predict more and drive the business towards growth. Strategic planning and modelling equip finance departments and leaders with the power to understand how these external factors can impact your financial health. A crucial advantage in an ever-changing landscape.
Demand-based forecasting models will show how changes in key drivers, such as business initiatives, prices, interest rates, weather, etc., have on product demand.
Having a better understanding and more accurate forecasts of demand means more accurate inventory and labour planning and resource allocation which leads to reduced costs and improved the bottom line. For instance, consider a company heavily reliant on imported materials. By analysing the model’s sensitivity to commodity prices, you can assess how a rise in oil prices might impact demand and, ultimately, profitability. By understanding and anticipating the impact of external forces, strategic planning and modelling become far more than just financial forecasts. They transform into powerful tools for safeguarding your company’s financial health and navigating the ever-changing currents of the market.
Moving beyond the spreadsheet
The incorporation of purpose-built AI and ML enables finance teams to overcome the constraints of manual data entry and analysis inherent in spreadsheets. Repeated processes, such as data entry, invoice processing and reconciliation, can be seamlessly handled by AI algorithms. This not only reduces the risk of human error but also increases overall productivity.
Relying too much on manual intervention leads to a lack of control and repeatability. Too much time is wasted manipulating data while too little time is left to draw the insights needed for strategic decision-making. Instead, AI can analyse large sets of data, predict future outcomes and help companies focus on new growth opportunities. AI can help perform thorough scenario analysis and risk management, preparing a company for inevitabilities when change is happening both internally and externally.
AI doesn’t just automate manual work; it can also put the power of data science into the hands of finance leaders. This can only be a good thing, as finance teams have historically relied on data scientists to help make sense of their data. However, data scientists have little to no finance background and the outputs are still capturing past activity, instead of being forward-looking.
Unlike Generative AI or AI automation, true purpose-built AI can help guide the business by addressing specific business challenges. For example, finance leaders can leverage this technology to identify the impact of their product forecasting in real time based on current key drivers combined with historical data and business intuition. This granular level of insight into the business is crucial to drive strategic decisions, allowing the business to remain agile and better allocate resources in response to changing market conditions.
Achieving this level of precision and sophistication is only feasible with AI. This revolution is not just about tools. The eventual outcome will be business leaders ready to lead with confidence, enhanced risk management and better cross-functional collaboration and overall productivity. We will see a new workforce generation equipped to contribute their skills to the evolving world of finance.
Embracing the potential while mitigating risks
As with any powerful technology, predictive finance comes with its own set of considerations. Issues like data privacy, algorithmic bias and the potential for misuse require careful attention. However, by fostering collaboration between financial institutions, technology developers and regulators, we can harness the immense potential of predictive finance technology while mitigating the risks.
Predictive finance technology is not a crystal ball, but it is a powerful tool that can illuminate the path toward a more informed, efficient and inclusive financial future. As we move forward, embracing this technology with a critical and responsible mindset will be key to unlocking its full potential and reshaping the financial landscape for the better.