Improving forecasting for 2023 and beyond

Traditional forecasting methods have been found lacking, so follow these steps to enhance quality — starting with alignment on the forecast’s purpose.

The last few years have seen unprecedented risk and volatility, making the task of forecasting financial performance fraught with uncertainty. The cumulative impact of COVID-19, global supply chain disruptions, war in Ukraine, and surging inflation has upended traditional methods for developing forecasts. Techniques such as trend analysis, variance to budget, and rolling forecasts have been found lacking at a time when insight into possible future performance has never been more important.

No industry or geography has been immune. In June 2022, US Treasury Secretary Janet Yellen admitted she was wrong to forecast that inflation would be a temporary blip. Oil prices surged from $65 to $120 a barrel between December 2021 and March 2022. The global rate of inflation more than doubled in the year to March 2022. Inventory levels in many areas went from scarcity to excess in less than six months. The Wall Street Journal reported in June 2022 that US retailer Target was taking steps to cut prices to shift excess inventory. UK-listed companies issued 72 profit warnings during Q1 2022, the highest number in two years.

Developing credible forecasts of future financial performance is arguably a management accountant’s most valuable forward-looking role. Managers use forecasts to develop strategies, decide on optimal resource allocations, communicate expectations to stakeholders, and set internal performance and compensation targets. It is disappointing that despite the massive investments in technology, data, and analytics in recent years, there has not been a commensurate improvement in forecast quality and accuracy.

There are many explanations — or possibly excuses — given for the inability to develop accurate forecasts. Most obvious is that the future is unknown. Excuses include unprecedented market conditions, faster or slower variations in key indicators, or changes in consumer behaviour. All sound reasonable, but they are not the only explanation for forecast failures. A number of other factors can negatively affect forecast accuracy:

  • Forecasting to budget: Organisations spend significant time crafting very detailed budgets that often form the basis for setting compensation plans. Every period, variances to budget are reported and analysed. Managers are under pressure to take corrective action to ensure that the organisation will get “back on budget” later in the period. This can lead to an artificial manipulation of numbers in the forecast model to show a result that closes any variance to budget regardless of whether such manipulations are realistic or achievable.
  • Failure to understand the purpose of the forecast: For a forecast to be useful it needs to be an objective view of what the organisation thinks the future will look like based upon the best information available at the time. Unfortunately, forecasts often show what we would like the future to look like rather than what we actually think it will look like. Budgets and plans can be aspirational, but forecasts need to be rational to be credible.
  • Management bias: Frequently, rigorous forecasts are developed using the best available data and analysis, only for management to make some “top line” adjustments that are not supported by facts or analysis but serve to present the outcome management wants to see.
  • Ignoring risk and uncertainty: The future cannot be forecasted with precision, so it’s pointless to develop a forecast that provides a single view of the future. However, too many forecasts rely on a single set of assumptions that fail to address alternate scenarios and known risk factors.

As we look forward to 2023, it is prudent to review how we can improve forecasting to deliver an outcome that is fit for purpose. Here are six practical steps finance professionals can take to improve forecast quality:

Be clear on the purpose of the forecast

The starting point for improving forecast quality is to ensure alignment across the organisation on the purpose of the forecast. Ideally, the forecast should represent the organisation’s best estimate of future performance based upon the best available data.

Eliminate bias

Leaders must emphasise that bias, subjectivity, and manipulation not based on rational assumptions are unacceptable. One of the most important tools is to decouple compensation from forecast (and budget).

Any time budget and forecast outcomes are directly tied to rewards, there is an incentive to try to game the system. Revenue-generating functions seek to negotiate the lowest possible number while expense-incurring functions try for the highest possible number.

This maximises the probability that the forecast number can be achieved or exceeded but does not provide a sound basis for making effective resource allocation decisions. For example, if sales negotiate a low target and then easily exceed it, there may not be adequate inventory to fulfil all the orders, as the production schedule was based on an artificially low forecast.

Measure forecast accuracy

When I served as head of corporate planning for a large global bank, I introduced a metric that looked at each business unit’s forecast accuracy over an extended period of time. With the agreement of the CFO, this was added to the scorecard of each business that was provided to the CEO. The simple act of measuring forecast accuracy and holding each business accountable reduced forecast variances by more than 50%.

Explicitly address risk and uncertainty

Use sensitivity analysis and scenario planning to communicate the impact of uncertainty and variability on key variables. A leading Asian electronics company develops forecasts under different sets of assumptions around four key variables that can materially impact future financial performance: raw material price inflation, exchange rates, shipping costs, and competitor pricing. Over time they have been able to identify that almost 90% of forecast variances are driven by one of these four variables. By developing alternate forecast views under different assumptions for these four variables, management is equipped with valuable insight on the range of future financial outcomes under different circumstances.

Communicate confidence levels

Not all numbers in a forecast are created equal. Some numbers can be forecast with a high degree of confidence; for example, expenses that are quantified in long-term contracts. Others — and, unfortunately, they are often highly material items, such as sales — are very difficult to predict with a high degree of accuracy. A number of organisations communicate confidence levels in each element of the forecast so management understands the likely areas of uncertainty. This can be done in a number of ways: Use colour codes to indicate confidence, ie, green for high, red for low; or use ranges, with a wide range indicating lower confidence and a narrower range greater confidence.

Ditch a forecast that is no longer credible

Forecasts can be a valuable tool for guiding planning, investment, and execution. However, more valuable than strict adherence to a forecast is to be smart enough to (1) identify when a forecast is no longer valid and (2) agile enough to adapt your behaviour and actions.

Moving forward with confidence

Of course, we do not have a crystal ball, so forecast variances can never be fully eliminated. However, by adopting a rational, common-sense approach, we can have confidence that forecasts represent the best view of the future available at the time. If a different outcome manifests itself, we have a basis for isolating the drivers of the variance, identifying corrective actions, and building that meaning into future forecasts. As data availability expands, analytical tools advance, and experience increases, we will be able to develop forecasts more frequently, in shorter time frames, and with increased confidence.

David A. J. Axson is a former partner with Accenture, co-founder of The Hackett Group, and former head of corporate planning at Bank of America. He currently serves as part-time CFO of To comment on this article or to suggest an idea for another article, contact Oliver Rowe at


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