“There are two kinds of forecasters: those who don’t know, and those who don’t know they don’t know.” ― John Kenneth Galbraith
A forecast is by definition inaccurate, incomplete or simply wrong. Still, a good forecast is key to set priorities and organize the work of your team while managing expectations
across the organization. If your business forecast is still a copy of
last year's results with a few changes here and there, then this article
is for you! Read on as we develop three ideas that will help small and medium business leaders improve the quality of their forecasts and better communicate their progress.
But first, what is a good forecast and why is it important? A good forecast correctly captures trends, seasonality and future events
that could impact your business metrics within a specific time frame in
order to better prepare today in the face of a possible future/outcome.
Good forecasts are indeed extremely helpful to organize your team's
work, review your strategy and better set your priorities although being
often inaccurate - and, to a certain extent, that's ok. Here is an
Corporate treasurers are traditionally good forecasters
for a simple reason, if they run out of cash the business collapses.
Thus, they are constantly checking the business plan, account
receivables and payables, inventory and cash levels in order to improve
their cash forecast. As a result, one month forecasts are generally very
accurate while six month forecasts are much less so. However, longer
forecasts should signify a trend while giving treasurers time to work
upon its outcome: "after performing a thorough analysis of the treasury
schedule, the treasury manager realized the company may not be able to
pay its debtors on time in six months from now". In this case the
workable outcome could be: six months to obtain a credit facility in
order to pay debtors on time - which is a task that couldn't easily be
performed in one month.
As companies are ever more dependent on
accurate forecasts to organize their activities and optimize their
supply chains, managers should be able to provide and communicate on
reliable forecasts. Here are three things you can do to improve the
quality of your forecasts:
Choose a foreseeable time frame that would still give you enough time to act upon its possible outcome. Indeed,
when you look at a 30 days forecast you know exactly what to do but its
often too late to influence the outcome, while a 180 days forecast
gives you plenty of time to do something about it but you don't know
exactly what. Perhaps (and this depends a lot on your industry) a 90
days forecast is just what you need to figure out what to do while still
having enough time to materialize the outcome of your forecast.
you move along the weeks, a series of assumptions are now being
confirmed or dismissed, update your forecasting model and improve the
quality of your previsions. An easy way to do that is by simply
replacing forecasted periods by their actuals when they become available
so that you improve the accuracy of your quarterly forecast (more on
this in the table below).
By creating a good forecast you have a first mover advantage:
use it! Indeed, when you act upon the outcome of your forecast you are
doing so before others do. Which means that you can assess your strategy
earlier (usually after 30 days) and adapt if needed (you still have 60
Now that we've learned to create reliable forecasts, let's see how to communicate them:
table below is a structured way to communicate on your forecasts but
many variations exist (it really depends on your industry). The table
below is specifically aimed at a quarterly sales forecast
and has been divided in 4 columns (initial situation (end of December),
end of the first month (January), end of the second month (February)
and end of the quarter (end of March)). Keep in mind that the outcome we
are interested in is the Quarter and not the result of each month
individually, this is the reason why the quarters (sum of the months)
are presented separately. On each column, the grey dataset represents
the actuals (zero in December and 355 € by the end of March for Q1)
which are the sales the company has effectively made over the first
Below the grey datasets we have presented the Forecasts.
The yellow set is the initial forecast (often called Budget), the green
one is the sales forecast that integrates one month of actual sales. The
blue set is the best-forecast that integrates two months of actual
sales and one reforecast. On the last column we can compare the actuals
to the best forecast and see how they converged over time.
is the story the dataset is telling. The sales manager has initially
forecasted sales of € 350. After one month of work s/he had sales of €
90 (€10 below her/his initial forecast). Based on this first results,
s/he changed her/his strategy and by the end of February sales were € 20
higher than expected. As there was only one month to go and that
uncertainties had been reduced (compared to the end of December), the
sales manager has been able to reforecast March (now € 115 instead of
the initial €120) providing a best forecast of € 355 for the Quarter
which was in line with the Actuals that became available by the end of
Indeed, by using this method, actuals were "known" one
month in advance and the forecast turned to be quite accurate. The other
positive outcome is that by structuring the information this way, the
sales manager was able to communicate effectively across the
organization reducing uncertainty over time.
For as much as this
methodology may be helpful, when it come to forecasts, here is the best
(and perhaps wisest) advice one can get:
"Hoping for the best, prepared for the worst, and unsurprised by anything in between." - Maya Angelou
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all views expressed on this article are my own and do not represent the
opinions of any entity whatsoever with which I have been, am now, or
will be affiliated.