Steve Player is managing director of ThePlayer Group. He is also programmedirector for the Beyond Budgeting RoundTable in North America.steve@theplayergroup.com

Steve Morlidge works as an independentconsultant. Previously of Unilever, he isalso a former chairman of the EuropeanBeyond Budgeting Round Table.steve.morlidge@satoripartners.co.uk

Steve Morlidge and Steve Player are the authors of therecently published book Future Ready: How to MasterBusiness Forecasting, John Wiley and Sons ISBN 978-0-470-74705-6

FINANCIAL MODELLING AND FORECASTING

MASTERINGFORECASTS

The poor quality of business forecasting is a majorheadache for managers all over the world. The scaleand nature of the problem is highlighted in thequarterly analysis by Ernst & Young of profit warningsissued by UK quoted companies such warningstotalled 282 for the whole of 2009, following a record449 in 2008, with an average for each of the pasteight years of over 300. These companies' share priceshave fallen on the day of the warning by an average ofbetween 10% and 20%.

Clearly, then, increased economic turbulence, suchas that experienced recently, makes anticipating thefuture more problematic. Yet it also makes it moreimportant. Few businesses can afford to wait and seewhat happens before taking action.

It is no surprise, therefore, that in a survey last yearby CFO Europe magazine the ability to forecast resultsis the number one internal concern for chief financialofficers worldwide, ahead of such issues as attractingFE

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Accurate results forecasting is the leading internal concern for those heading upfinance functions. Below Steve Morlidge and Steve Player explain how to improvethe quality of your business forecasting.

scouring the academic and management literature, wethink we have an answer to improved forecasting.

Interestingly, during this research it became apparentthat the key to successful forecasting lies not only inwhat you need to start doing, but also in what youneed to stop. In particular, traditional budgetingpractice, and the mindset associated with it, is part ofthe problem and one of the habits that needs to be letgo.

Below, organised around six principles of forecastingmastery, are some ideas, and some related questions(plus answers).

1. Mastering purposeThe purpose of forecasting is not to predict the future.The purpose is to anticipate what might happen, givena reasonable set of assumptions about the world. Armedwith this information, managements take decisions,either to help bring that future about, or to change it toone that is more desirable. To achieve this you should: stop using budgeting processes and chart of

accounts to produce forecasts; and start recognising the crucial distinction between a

target (what we would like to happen) and a forecast(what we think will happen) as well as the necessaryand inevitable existence of gaps between the two. Inaddition, you should design forecast processesaround the decisions that they support. This requiresthat they be:

timely: in good time for decisions to be made(which might not coincide with accountingperiods);

actionable: using less but different detail fromthat used for budgeting;

reliable: unbiased, with acceptable variationrather than absolutely accuracy;

aligned: complementing other sources offorecast information rather than in competitionwith them; and

cost effective: rather than low cost.

and retaining qualified employees, balance sheetweakness, counterparty risk, managing IT systemsand supply chain risk.

Producing reliable forecasts has never been easy, butthe situation has become critical in recent years asother previously tried and trusted techniqueshistorically relied upon have bent and buckled underthe stresses of the current economic environment.

For instance, even in normal times most budgetsare out of date within two quarters, and in 2008 and2009 the majority were rendered redundant withinthree months.

So we have a major problem. What is the solution?Unfortunately, the professional literature focusesalmost exclusively on forecasting technique theapplication of complex mathematical solutions to therelatively simple problem of how to forecast the valueof a single variable in the near future. What we reallyneed, however, is a simple solution to the complexproblem of how to forecast the value of a set ofinterrelated variables into the medium term.

A PRACTICAL SET OF WELL-GROUNDED PRINCIPLESHappily, after five years of plundering the knowledge ofmany practitioners in a range of disciplines, and

7FINANCE & MANAGEMENT June 2010

What decisions will be made with the aid of yourforecast? This usually involves starting, stopping,rescheduling, changing or creating some form ofactivity.

What information do you need to make thesedecisions and is it provided as part of the forecastprocess? Usually this involves understanding theincremental impact of any changes you might wantto make to the portfolio of activities. Often thisinformation is not readily accessible to decisionmakers.

Can you eliminate information that is not relevant fordecision making purposes? If you can it willstreamline the forecast process and help improveforecast accuracy.

QUESTIONS (1)

An analogyWe find that sailing provides a useful analogy for helpingpeople think about forecasting (Figure 1). Before settingout to sail from point A to point B (your target), it isimportant to prepare a plan. In our line of business wenormally call this a budget. But we may soon findourselves in an unexpected place (C), because theassumptions we made about the world when we preparedour budget (tides and wind or market conditions andcompetitors actions) have proven to be false. At this pointit is often not sensible to try and get back on plan.Instead, we need to forecast where we are heading so thatwe can take action if it is not where we want to go (eghitting the rocks, poor business performance). If ourforecast shows us heading towards trouble (D), we need tochange our action plans (move the rudder, tack or perhapschange price and promotional activity) to steer backtowards our goal.

2. Mastering timeForecasts are necessary only because we cannot react fastenough to events as they happen. That is why supertankers need radar but speedboats do not. Forecastprocesses therefore need to be designed around decisionmaking lead times and the nature and rate of change inthe environment. As a result you need to: stop producing forecasts that extend no further than year

end, according to accounting timetables; and start producing rolling forecasts (ie with a consistent

horizon), as and when needed.

3. Mastering modelsForecasts are the output of some form of a model ofthe world. These models may be explicit andquantitative, but they are often held in the heads offorecasters: judgemental models. There is nomathematical silver bullet; forecasts will alwaysinvolve the use of judgement in some way, but thisalways carries a high risk of bias. Model choice needsto take account of the relative strengths andweaknesses of the different approaches, so: stop relying exclusively on one approach to

forecasting; and start using different types of models in combination,

exploiting their relative strengths and mitigatingtheir weaknesses.

4. Mastering measurementGiven that businesses are seldom stable for long, theperformance of even the best forecast will deteriorateunpredictably unless there is some form of feedbackon its performance. Continuous measurement offorecast error is needed to calibrate forecast models totake account of shifts in behaviour, and to improvethem through a process of learning. In business,forecast performance is often not measured at all, andwhen it is, usually the wrong techniques and processesare used. You need to: stop relying on informal approaches to the

assessment of forecast quality; and

Which forecast variables tend to follow a clearhistorical trend? These may best be forecast usingstatistical extrapolation techniques. Research hasshown that simple techniques usually give moreaccurate results than complex ones.

If forecast variables do not follow a simple historicalpattern do you have a good grasp of drivers ofperformance? If so, it may be appropriate to use adriver based model to produce your forecast.

Which variables are best forecast using judgment?This will most likely include most of the variablesimpacted by decision making. Wherever judgementis used you need to take steps to reduce the risk offorecast bias.

QUESTIONS (3)

FIGURE 1

How long does it take to enact a decision? Thedecision making lead time will determine howlong your forecast horizon should be.

Are there many potential decisions with shorterlead times? If there are, you may need sub-horizons that contain more detail.

How frequently do elements of your forecastchange in a way that impacts decision making?This will determine the frequency at which youneed to refresh your forecast and is likely toinvolve updating some forecast elements morefrequently than others.

QUESTIONS (2)

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Forecasts are necessary only because wecannot react fast enough to events asthey happen

start routine and frequent measurement of forecasterror over short time horizons. Focus on detecting bias,rather than attempting to measure forecast accuracy.

5. Mastering riskPerfect prediction is impossible, so forecast processesshould include the generation of alternative potentialoutcomes, to promote situational awareness and tohelp generate an appropriate range of responses. It isimportant to differentiate between risk (unavoidablevariation around a forecast) and uncertainty(discontinuities). To accomplish this: stop exclusively forecasting single point outcomes;

and start incorporating the assessment of alternative

potential outcomes into the routine forecast process.Post lookouts and build contingency plans so thatyour organisation is able to respond quickly andeffectively should circumstances change.

6. Mastering process Reliable forecasts are the result of the conscious design anddisciplined operation of a routine process, not intuition orad hoc analyses, so: stop treating forecasting as an optional exercise; and start building forecasting into the fabric of your

management processes.

CONCLUSIONIn many businesses, the forecasting process is badlybroken. As a result, managers are flying blind or, worse,they are using instruments that provide misleading signals.The remedy is at hand: a set of simple principles, which ifthey are rigorously applied, guarantee a reliable and costeffective process. All that is needed is a structuredapproach to implementing them, the courage to dispensewith some legacy processes and mindsets and thecollective will and discipline to stick to the principles,especially when (as will need to happen at some stage) theforecast produces an unwelcome message.

Analysis of profit warnings, Ernst and Young,www.ey.com/UK/en/issues/Transactions/Restructuring/Profit-Warnings

Top ten concerns of CFOs, CFO Europe,www.cfo.com/article.cfm/13606188/c_3805465/?f=archives

REFERENCES

Do you have a clear, well communicated forecastpolicy? Most businesses do not, so it is notsurprising that forecast quality is poor. As aminimum, this should state that forecasts shouldbe unbiased with no systematic error andsubject to acceptable levels of variation.Unsystematic error should be at a level that doesnot compromise decision making.

Is forecast error routinely measured andappropriately followed up? If not, it should be.Ensure that you eliminate bias as soon as it isspotted, but take care not to react where there isinsufficient evidence of bias.

Are forecasts ever overridden or adjusted? Avoidthis wherever possible. If they are altered,maintain records to ensure that any adjustmentsmade consistently reduce bias.

QUESTIONS (4)

Does your organisation only produce single pointforecasts? If so, start producing range forecasts.Be careful to distinguish between routinevariation around a forecast and the potentialdiscontinuities changes in the pattern ofbehaviour.

Does your organisation produce multiple,competing forecasts? If so, stop immediately. Ifthere are genuine, potentially valuable,differences of opinion, capture these in yourrange forecast process.

How quickly can you respond to unexpectedchanges? For a range forecast to be useful youneed to know how you would react to a range ofpotential outcomes. This may simply involveminor changes to your portfolio of activities, butcontingency plans are required to deal withpotential discontinuities, particularly if theythreaten the survival of the organisation.

QUESTIONS (5)

What process do you use to produce forecasts? Ifforecasts are to be relied upon, you need astandardised process that is consistently appliedand constantly improved.

What other business processes feed, or are fed by,the forecast process? It is important thatappropriate linkages are built into your forecastprocess. In particular, there should be a closelinkage between forecasting and the resourceallocation process, since money and other forms ofresource are required to enact decisions.

Who is responsible for what? There is no one rightway to allocate responsibility for forecasting. Goodforecasting requires a mix of technical aptitude,domain knowledge and objectivity; attributes thatare unlikely to be found in a single individual orfunction.

QUESTIONS (6)

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FEATURES

FINANCE & MANAGEMENT June 2010

FINANCE & MANAGEMENT FACULTYThis article was first published in Finance &Management, the monthly magazine of ICAEWsFinance & Management Faculty. The faculty helpsmembers in business to perform at their best. Formore information on the benefits of membershipsee icaew.com/fmjoin

Copyright ICAEW 2010