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Revenue Forecasting Methods & Techniques [Expert Tips]

Having an accurate 12 month revenue forecast is a vital component of the budgeting and planning process in a Professional Services organization.  Get the forecast too high and you could end up taking on too much cost too soon.  Get the forecast too low and you won’t be able to resource up in time to take advantage of your business pipeline.  Either way you are impacting your profitability negatively.

Unless your business pipeline has a large proportion of annuity contracts surely it is near to impossible to get a 12 month forecast correct with any degree of confidence? You’d think so, but that isn’t the case. Over the past 15 years I have been using a simple approach which every year has proved extremely accurate if you have at least 10 customers and prospects.  I’ll be honest I don’t know fully why it works, but history proves it does in practice.  I also know that everyone who has tried it in other organizations I have spoken to has had similar results and found it a straightforward and valuable sales planning technique.  So this is how it works if you want to try it…

Step 1 - gather the initial data

Organize a session with each of your account owners to review their active accounts and prospects.  Ask them to provide estimates of the revenue opportunity at a headline level for each of these accounts over the next 12 months against three different estimating criterion.  The three estimates are known as low, medium and high and are derived based on the following classification:

Low – this is the business which is currently contracted at the account.  For example, if you have a consultant on an existing engagement at $1,000 a day which has 20 days to complete then the ‘low’ number for this account would be $20,000.

Medium – this is the best guess of what the account owner thinks will be revenue won at that client over the next 12 months.  I typically set the expectation that the account owner should imagine that if he or she is not accurate within plus or minus 10% of the medium forecast number at the end of the 12 month period they will metaphorically lose their job.  I frame it in this way to stress to them that I don’t want the number low-balled or overestimated.  I say I know I am asking the impossible but need them to take this approach and use their best judgment – I won’t be setting targets based on these individual numbers (and indeed you should not – see my blog on setting incentive sales schemes).

High – this is the best guess of the revenue you would win if you won every opportunity in the account over the next 12 months and you had no resource constraints (i.e. you could staff every project you won fully).

Note that the 3 numbers should be cumulative.  For example, a $100,000 forecast as low and additional $200,000 forecast at the medium level and an additional $150,000 forecast as high would be expressed as:

low          $100,000
medium  $300,000
high         $450,000

Step 2 - validate the data

You should review these estimates face to face with the account owner.  Simply getting the account owner to describe out loud their thought process in deriving the estimates has the effect of teasing out where they have under estimated or over estimated (tends to be the former).  If you are in a organisation where multiple people are involved closely with business development (for example, where you have a Project Manager/ Consultant leading an account from a delivery perspective as well as a Sales Person assigned to the account) then try and get each person independently to come up with the estimates and then bring them together to seek consensus.

Step 3 - consolidate the data for your company

Consolidate the information from each of the account owners and you are now left with something like the following:

Client NameOwnerLowMediumHigh
AcmeJohn$100,000$500,000$1,000,000
ArchillesBrian$-$-$3,000,000
Brandon PlasticsJane$250,000$250,000$250,000
Chumley PharmaceuticalJane$1,000,000$1,100,000$1,200,000
Detroit CarsJane$200,000$500,000$2,000,000
Franklin MotorsBrian$10,000$1,000,000$1,500,000
Mangrove EstatesJohn$250,000$250,000$450,000
Norman EngineeringEmma$700,000$1,000,000$1,300,000
Peidmont WinesEmma$50,000$100,000$250,000
QuiverBrian$-$-$500,000
Reed ElectronicsJohn$450,000$650,000$900,000
Stream SolutionsKeith$40,000$100,000$200,000
Wright BrothersJohn$30,000$400,000$600,000
ZelstraJohn$500,000$1,000,000$2,000,000

Step 4 - total each of the low, medium and high numbers

The most important point about this technique to appreciate (and to ensure your account owners appreciate too) is that it is the total for each of the low, medium and high forecasts across your whole business that we care about and not the individual estimates.

We fully expect in a Professional Services organisation that over a 12 month period most of these forecasts at an individual level will not be accurate.  In the example above we might be starting the bidding process at Quiver for a highly competitive project worth $500,000 (hence forecast only as high) and we eventually end up losing it.  In all likelihood another similar deal (or several smaller deals totalling an equivalent value) which we don’t know about today will come along that we can win.  Alternatively, we might actually win the Quiver deal but Reed Electronics might run into financial problems and have to cancel the $450,00o on-going project (forecast as low).  The point I am making is that during the normal course of operation of a Professional Services business over a 12 month period the ‘total’ figures we derive will be accurate.  However, the individual items from which they were calculated will not hold up for closer inspection.

So for the example above we get a total for low, medium and high of:

LowMediumHigh
Total$3,580,000$6,850,000$15,150,000

 

Step 5 - calculate the forecast revenue

The final step is to calculate the 12 month forecast.  The total revenue number that you will actually achieve over the following 12 months is a figure 30% of the way between the medium total and the hight total.  The formula for annual forecast revenue is: ((high-medium) * 30%)+ medium.

So in the example above the low/ medium/ high derived 12 month revenue forecast would be: $9,340,000.

Does it really work?

The simple answer is yes.  Indeed, the more accounts you have the more accurate the forecast proves to be.  This makes it an extremely valuable technique in the budget planning process.  In reality however successful your business is then you can never achieve the high forecast as you will never be able to resource people quickly enough to fulfil the projects you win.  So the revenue you achieve ends up being 30% above the medium number.  I’m not sure scientifically why it ends up being 30%, but I’m just happy that it always does!

If you want to measure trends in what you are closing and extrapolate the results to produce more detailed forceasts then try looking at my blog on measuring the health of sales operations.

How can I use this information in the planning process?

In the budgeting and planning process then this low/ medium/ high derived forecast number can be used to cross reference (or validate) against the ‘bottom up’ forecast derived from headcount.  In a simple example we might say that we employ 50 consultants and we plan to recruit 2 additional consultants a month at an average day rate of $800 with an average of 14 billable days a month.  We’d end the year at 74 consultants and our ‘bottom up’ forecast would be $9,027,200.

If we had the derived low/ medium/ high revenue forecast as shown in our example of $9,340,000 then I’d be comfortable that we have got the budget set correctly.  If we had less consultants initially or planned to recruit at a slower rate then our ‘bottom up’ forecast would be significantly lower than this, in which case we are unlikely to have enough resources to win the business forecast with this technique.  Alternatively, if we have a significantly higher headcount driven forecast than our low/ medium/ high derived forecast then we will have too much cost built into the business and we need to re-plan.

What else can I use the information for?

I have also used this information to organise my sales team and focus my sales strategy.  In the example I’ve been using I’d group together the accounts under each account owner then analyse the data.

Client NameOwnerLowMediumHigh
ArchillesBrian$-$-$3,000,000
Franklin MotorsBrian$10,000$1,000,000$1,500,000
QuiverBrian$-$-$500,000
Norman EngineeringEmma$700,000$1,000,000$1,300,000
Peidmont WinesEmma$50,000$100,000$250,000
Brandon PlasticsJane$250,000$250,000$250,000
Chumley PharmaceuticalJane$1,000,000$1,100,000$1,200,000
Detroit CarsJane$200,000$500,000$2,000,000
AcmeJohn$100,000$500,000$1,000,000
Mangrove EstatesJohn$250,000$250,000$450,000
Reed ElectronicsJohn$450,000$650,000$900,000
Wright BrothersJohn$30,000$400,000$600,000
ZelstraJohn$500,000$1,000,000$2,000,000
Stream SolutionsKeith$40,000$100,000$200,000

For example, typically I don’t like a business development person to be allocated too many accounts which only have speculative opportunities – this would be indicated by a large difference between low and high numbers.  Additionally, if there is little or no difference between the low, medium and high numbers then the account is better managed by a delivery focused person than a business development/ salesperson.  In the above example there seems little point in having Emma working on business development at Brandon Plastics as there is no upside and it would be better managed by a Project Manager or Lead Consultant with some sort of profitability target.

Another thing you can do is have more than 10 accounts allocated to an individual business development/ salesperson then you can start to use the derived low/ medium/ high forecast total across their accounts to verify sales targets.

In Kimble we allow you to record and analyse this information.  I’d be really interested what your experiences of trying this approach are.