5 Ways to Forecast Sales – Which One is Yours?


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How many methods or techniques are there for sales forecasting? There are 5, in my experience, offering varying accuracy and utility. Here’s the background and a short explanation of each.

We all know forecasting sales is a tricky business. It always involves some element of hope, combines a little fear, and is based on some level of confidence. And it always goes wrong. Accurate forecast is an oxymoron – a combination of words contradicting each other.
Nevertheless forecasting sales, revenue, profit and cash flow is the most fundamental of business processes. Everybody has to do it, so all the other business decisions can get made.
Quite how it gets done varies, depending on who does it, and decisions to be made based on the results. For example, the under performing sales rep is hardly likely to forecast no sales and keep the job for long. Likely response to forecasts results can have as much influence on the numbers as can the facts.
Here are the 5 methods I’ve seen used.

1 – Hope

Of course trying to do anything requires a degree of optimism – some combination of aspiration and hope. If you’re selling stuff, or employing somebody else to do that for you, aspiring to reach a given level and hoping to achieve it is an admiral approach to setting targets. But its no way to set a forecast, on which you or anybody else will base decisions. Aspirations are targets not forecasts.

2 – Fear

Fear of the consequences of forecasting is a powerful incentive to self delusion. The under performing sales rep will keep her job for another quarter if the forecast promises to make up for past failings. The struggling business owner will get an extension to his credit line for another six months if the cash flow is positive in the future. Both will have to face reality one day, but at least not today. Forecasts based on fear only delay the inevitable by making matters worse.

3 – Guesswork

Accurate forecasting is impossible, so the only sensible approach is a simple guess. Will that customer buy? Will the competition do something silly with price? Will the CFO provide the budget. Most sales people don’t know the answers to these questions, so they guess – yes, no, or maybe.

4 – Confidence

Most professional sales operations use Confidence as the basis of sales forecasts. Recognising nobody gets every deal on the prospect list, sales managers will apply a factor to the estimated value of each sale to get to a weighted probability adjustment. For example Customer A has a proposal for $100k. The sales rep is 70% confident of winning so the estimated value is adjusted to $70k. The aggregate of weighted probability adjusted values is more likely to be accurate than the other three methods. But it’s still based on a guess. The adjusting Confidence factor is a guess, so the result must be equally a guess. It just sounds more scientific.

5 – Process

Our Process method adds real science to the preparation of sales forecasts. It can be standardised across all sales opportunities and improved through closed loop feedback. It’s more accurate than any other method, and actually adds value to sales operations, being tightly aligned with the sales strategy and process. It becomes a competitive advantage for teams adopting the concept.
Breaking the sales process down into milestones creates a logical progression from first call to contract. Assigning a percentage value to each milestone, and adjusting the forecast value by that percentage as the milestone is reached, increases the weighted value of the forecast. The only way the sales rep can get an higher forecast is by achieving the milestones, each of which make the successful sale more likely.
In this example the list is ordered by close date – next to close at the top – and colour coded for probability. As deals move up the list they should progress from Red, through Amber to Green. This colour coding draws attention to the at risk deals. Any red at the top of the list tells you to get to work on the deal or get ready to lose it.
sales forecast with weighted probability calculation

Republished with author's permission from original post.

Steven Reeves
Consultant, author, software entrepreneur, business development professional, aspiring saxophonist, busy publishing insight and ideas. Boomer turned Zoomer - thirty year sales professional with experience selling everything from debt collection to outsourcing and milking machines to mainframes. Blogger at Successful Sales Management. Head cook and bottle washer at Front Office Box.


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