Generating accurate management information is at the heart of effective
planning, budgeting and forecasting. Although it isn’t a topic that excites
executives, getting forecasting wrong can have a devastating effect on the
confidence of shareholders, customers and employees.
A recent global survey from KPMG/Economist Intelligence Unit found that poor
forecasting costs, on average, 6% of a company’s share price when analysts and
investors react to a significant mismatch between outlook guidance and actual
results. Poor forecasting costs money, jeopardises investor and shareholder
trust and limits business performance.
Forecasting through uncertainty
In today’s increasingly uncertain business environment, effective forecasting
becomes even more vital. The recent credit crunch and uncertainty about the
impact of the fallout from the US sub-prime mortgage crisis have increased
strain on all listed companies, putting them under immense pressure to inform
the market of losses and quantify, where possible, the level of future
The market abhors a vacuum so where guidance is not forthcoming it is making
its own assumptions. The credit crunch has also renewed the focus of analysts,
regulators and the market on the robustness and quality of scenario analysis
performed as part of the forecasting process.
There is a very simple explanation as to why companies are generally poor at
forecasting. It’s because they do not treat it seriously enough, seeing it as an
art rather than a science. In fact, it is a science, and failure to accept this
can hit businesses hard.
Executives estimated that poor forecasting can be equated to share price losses
of around 6% over the past three years. However, the real impact goes deeper
than that, accurate forecasting is at the heart of any performance management
process as it provides the reliable foundations on which heavyweight strategic
decisions can be made. Companies which were ‘good’ forecasters saw their share
prices rise by 46%, more than one-third more than other, poorer, forecasters who
achieved a rise of 34% over a three-year period.
Often, the forecasting process takes a significant length of time, with the
result that people lose interest in the numbers. Many organisations have a
tendency to ‘play it safe’ when it comes to forecasting, with 46% of firms
surveyed posting actual results more than 5% greater than forecast.
When looking for solutions to forecasting issues many finance directors or CFOs
turn to technology. Across the survey, more than one- third of organisations
identified their existing technology as a barrier to effective forecasting.
Nearly all organisations questioned still relied on spreadsheets as part of the
forecasting process with 40% relying solely on spreadsheets.
The best way to maximise return on investment in technology is when it’s part
of a wider finance transformation programme. Simply implementing new technology
within the forecasting process will not solve wider underlying data and process
Although 63% of firms relied on the finance function to take responsibility
for forecasting, the process needs to include all areas of an organisation. To
be effective, the forecasting process has to be linked to the overall planning
and performance measurement process for the firm, with the same key performance
indicators used as drivers for re-forecasting as those used to measure
performance against strategy. This will increase the relevance of the
forecasting process to employees and will help them understand the impact of
their function within the wider organisation.
Forecasting needs to become a tool that is used to facilitate a process of
challenge between the finance function and business heads within the
organisation. Improving the frequency of forecasting to monthly rolling
forecasts with full quarterly reviews will help to embed the process within
organisations, especially if the discipline is also maintained to explain actual
performance against forecast, both for over and under performance.
Improvements to timeliness and data quality can often be made simply by
looking at the data used and processes to obtain that data to identify
efficiencies and implement basic process reengineering. A clear process that is
easy to understand will permit ownership of data to be made more accountable
with a corresponding positive effect on data quality.
Turning to the problem of under forecasting, while it is arguably human nature
that is to blame for the fact that so many companies seem to underplay their
forecasts in order to comfortably exceed them, this costs money.
If infrastructure and processing capacity decisions are made on the basis of
forecast data, then new systems may not be able to cope with actual volumes. In
addition, low forecasts can limit supply for example, if a manufacturing firm
doesn’t have the raw materials in place because it has under forecasted orders
it may not be able to meet customer demand.
Almost certainly, the trend for actual results to exceed forecasts will
reduce the lifespan of systems as capacity limits are reached before planned
dates. With more accurate forecasting and improved scenario analysis, better
investment decisions could be made regarding project spend.
The survey highlights deeper issues with underlying data and timeliness which
need to be addressed as part of an overall improvement programme if the
organisation is to truly benefit. Technology alone will not deliver the
improvements it needs improvement programmes to address the process and
cultural issues to deliver lasting benefit.
CFOs need to treat forecasting more as a science and not an art driven by gut
instinct and intuition. Organisations which perform well in this area prove that
it’s possible. They apply proper rigour to the process and use it as a
management tool. In addition, they embed forecasting discipline into the culture
of the organisation. None of this is easy, but, done correctly, it can add
measurable, long-term value to any business.
Gary Reader is a partner at KPMG Financial Management Advisory
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