How to account for inflation in modern forecasting
Inflation has been a hot topic on the news lately, and for a good reason. Rapid shifts in inflation can have dramatic and potentially damaging impacts on virtually everyone and everything, from the average human to global enterprises. Rapid increases in inflation lead to rising costs.
Suppose businesses don’t anticipate sudden increases in inflation in their forecasts. In that case, they can suddenly find themselves experiencing smaller or negative profit margins as COGS rise or see an increase in employee turnover as rising consumer prices force workers to seek higher wages.
A race against the clock
The primary challenge when accounting for inflation in traditional forecasting is the time it takes to create forecasts – it is tough to make sudden adjustments to forecasts when they take weeks to months to generate. Gartner supports this point by noting that 76% of financial controllers say updating financial models to reflect business realities is one of their top time-consuming initiatives today. Additionally, the same Gartner article notes that building flexibility, agility, and strategic thinking into activities like forecasting, planning, and budgeting is a top priority for CFOs.
Fortunately, Neal Analytics offers a modern forecasting solution that can help.
What is modern forecasting?
Modern forecasting is a method of generating on-demand forecasts and is designed to be more accurate than traditional forecasts. On-demand forecasting is achieved by leveraging cloud-enabled technologies like a modern database, automation, and machine learning models in conjunction with internal and external data sources. Examples of internal data might include company financial figures, production planning figures, payroll, and other internal data that might impact a given forecast. External data, on the other hand, could potentially include virtually any data point that might affect your business, including everything from weather predictions for an outdoor retail company, to tracking commodity futures pricing for manufacturing or CPG firms, to inflation.
By accounting for external and internal factors beyond historical data, a machine learning-based modern forecasting solution enables organizations to increase the accuracy of financial forecasts and reduce forecast generation timelines from weeks or months to just minutes.
How can modern forecasting help account for inflation?
The primary way modern forecasting helps account for inflation is by leveraging up-to-date inflation data to adjust financial forecasts as the organization generates them. Since modern forecasting can generate ad hoc forecasts in just minutes, organizations can regularly check on how changes in inflation might impact their business during the forecasting period.
Keeping a regular pulse allows organizations to react quickly or even predict market changes, helping to avoid lost profit during periods of high inflation or spiking costs. Additionally, by keeping informed on inflation, organizations can keep tabs on how it impacts their employees and better account for it when providing raises to account for the cost of living.
One important limitation is that Neal’s modern finance solution is not designed to predict inflation itself. Instead, the solution can pull and leverage inflation prediction figures from an external data source.
Do you want to learn more about using Neal’s modern finance solution to account for forecasting? Contact us.