Predictive analytics is a fancy term for an approach that is as old as time itself. Humans have always sought to quantify and measure things in an effort to look into the future. For generations, prophets and visionaries have used predictive analytics. So it is only natural that, in modern times, the impulse to have some understanding of potential future events remains a key part of how our world operates.
Today, an organization's success or failure depends on its capacity to foresee change and respond quickly to it, such as the present global inflation crisis.
With massive data sets scattered across numerous spreadsheets, finance professionals aim to produce highly precise methods for forecasting outcomes. Without the help of technology and AI-based solutions, making sense of the data deluge is time-consuming and, in the face of such rapid change, a sure-fire way to limp behind the competition.
The combination of recent events, including the Covid-19 pandemic, escalating geopolitical tensions, supply chain disruption brought on by both the pandemic and the war, and most recently, the worldwide inflation would make any corporate leader's stomach turn.
According to research from the Business Application Research Center, the use of predictive planning is rapidly expanding. One in four organizations already makes productive use of machine learning and predictive algorithms as they look for ways to produce their plans and forecasts more quickly, more efficiently, and with better results.
How can businesses use these solutions to their greatest advantage in order to counteract the consequences of the present inflationary environment?
A three-pronged approach
A company's strategy can only be as effective as its planning processes. Finance professionals can adapt to the effects of current inflation in three ways: through business partnering, predictive planning technology, sensitivity analysis, and scenario planning.
1) Business Partnering
Economic uncertainty and business partnering are closely intertwined. The higher the uncertainty, the closer finance professionals need to partner with the broader business. In order to aid people through difficult economic times, they must assume the role of strategic advisor. Additionally, it calls for regular and meaningful communication with individuals from various departments.
Finance professionals are not just on the receiving end of the organization’s data pile, but rather positioned in the mix to assist in co-creating strategies for both managing and planning for the characteristic volatility of the current economic environment. As business partners, they can review the following factors for opportunities to increase revenue and/or reduce expenses:
Portfolio of products: examine the complete portfolio and seek chances to eliminate underperforming products, bundle products to boost sales, and raise prices.
Expenses: Take into account a zero-based budgeting approach and demand that the company review and justify all expenses.
Working capital: work closely with treasury to develop cash management strategies that maximize working capital.
2) Predictive planning technology
Given the growing significance of including external data sources, sensitivity analysis, and a review of multiple different scenarios, digital transformation in financial planning is more crucial than ever. And further: technology makes people happy and there’s evidence to prove it.
According to a survey of finance professionals by 2022 FP&A Trends, those who utilized technology to create their forecasts were more satisfied with it than those who employed other techniques. Only 39% of respondents rated forecast satisfaction as either good or great; however, that number leaped to 50% for organizations using a cloud-based planning tool and 63% for those using artificial intelligence (AI) as part of the planning process.
Predictive planning and AI technology make for a more robust and complete planning process. A solid cloud-based planning tool may also enable easier internal company collaboration, the implementation of external data sources, the application of AI and machine learning to highlight consumer behavior trends, alerts, and opportunities, and the comparison of various business scenarios.
AI is a technology that may be used to help increase forecasting accuracy by using historical and external data factors to detect patterns and data correlations that can help increase overall forecast accuracy. It does not and cannot take the role of human judgment. And it shouldn't. But it can augment human beings’ unique ability to make rational choices based on the data before them.
3) Sensitivity analysis and scenario planning
Sensitivity analysis is the process of taking a key input and seeing how a key driver changes because of that input. A sensitivity study can examine the cost of sand and see how different sand price points affect a building contractor's overall profitability. Finance experts can learn how each driver and input will impact the organization's overall financial health by running a sensitivity analysis on them.
In today's continually changing environment, a static budget with merely a point estimate is insufficient, and it is more crucial than ever to run several scenarios. Every organization should build plans for how it will operate and manage based on many scenarios that might take place in the upcoming months and years.
What will we do if inflation climbs even higher or remains persistently high for the next two to three years? is a question that every organization should ask itself. What will we do if a severe recession hits the global economy? These questions are the first step in modeling and planning for potential scenarios.
Predictive analytics is like every other type of analytics. The data you acquire is useless if you do nothing with it. The best way to cope with an inflationary environment along with all the other unforeseen occurrences that life brings our way is to act decisively based on careful analysis.