Tag Archives: sales reps

A weighted forecast: all you need from a sales forecast?

Friday, August 14th, 2009

How often have you heard a sales executive commit to a top-line revenue number by handicapping the forecast? It happens in executive meetings around the world. As a quick refresher, handicapping the forecast is usually done by weighting the pipeline revenue number.  Weighting the forecast is the simple process of multiplying the opportunity “probability to close” by the opportunity revenue and aggregating that “weighted revenue” across all opportunities—and “Abracadabra!” you have your final revenue number.

In a large company, it is quite impressive when you can rely on such a simple process to forecast a revenue number 3 months in advance. In my software career, from Siebel to Right90, this simple method has been incredibly accurate at calling the top line revenue number. This isn’t anything new, and many folks have espoused this method.

So, sales forecasting is easy. Call it done, right?

Should I build 55% of the forecasted units?

WRONG! Is the sales forecast used only for calling the top line revenue number? No. It is used across the organization, including by operations teams to determine how many units of which product they need to build.

Example: If Customer A is forecasted to buy 1000 widgets and the probability of that opportunity is 55%, does that mean the factory should build 550 units?

The customer will either buy 1,000 units or 0 units. Building 550 is the worst of both worlds:  if you win the business,  you don’t have enough to fulfill the order (and therefore lower customer satisfaction or lose the business all together).  However, if you don’t get the order you get stuck with 550 units of left over inventory for that product. In this case, a weighted forecast doesn’t work. Instead, a raw, bottoms-up forecast is a better method.

Denis Pombriant, of Beagle Research, explains this issue in great detail in a recent white paper. Let’s take another example of where weighted forecasting is not enough.

Existing business vs new business

For many companies, 80% of revenue comes from ‘run-rate’ or ‘existing’ account business. It goes to reason for these companies, forecasting existing business is more important than forecasting ‘new business.’  In the case of existing business, there is no probability.

Example: We all know HP buys chips from Intel.  Do you think there is an “opportunity” for HP computers in Intel’s CRM system with a probability associated with it?  NO – Intel won that business a long time ago, but Intel still has to forecast the units of each specific chip that HP demands each month. In this case, Intel needs a raw forecast of exactly how many units of which specific chip that HP demands in which month (or week).

This requires a bottoms-up forecasting approach by units, by account and product managers familiar with the HP and Intel relationship. After capturing the raw forecast, Intel likely leverages a statistical forecast and management judgment in arriving at the final unit judged forecast. This is another example of where the weighted forecast method is not sufficient.

There are many other cases where a weighted forecast does not provide all that you need. However, as I stated at the beginning, weighted forecasting is a valuable PART of a sales forecast. This is why we recently added weighted forecasting functionality to the Right90 sales forecasting application, enabling companies to create  a complete sales forecast.  A complete sales forecast in best-in-class companies involves some combination of

  • a bottoms-up raw forecast from direct sales folks
  • a bottoms-up raw forecast from distributors or partners (the channel)
  • A product manager’s forecast
  • A statistical forecast
  • A calculated forecast (based on probability weighting or some sort of historical measure)
  • Management vetting (scrub or review) of the raw forecast
  • Executive judgment

Sales forecasting is part art and part science; best-in-class companies use all information available to them to arrive at a trusted and actionable sales forecast.

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Stick or Carrot for the Sales Reps

Tuesday, June 30th, 2009

In my previous blog, I covered the The Importance of a Sales Forecast and what it is going to take to create an environment that enables, and at the same time forces, sales people to input their sales forecasts with ease, thought, discipline and, above all, with a realistic understanding of the buying and sales cycle.

Beyond (i) getting executive commitment (ii) making it easy for the reps to forecast (iii) enabling the necessary level of analysis (iv) holding the reps accountable to the sales forecast; the sales reps are always going to need some level of motivation to manage and update their sales forecast on a regular basis that goes beyond simply benefiting the company.

Companies have tried a variety of options, all with varying degrees of success. In his How to Take the Fear Out of Making Your Number White Paper, Haresh Patel, most recently senior vice president of sales and marketing at WJ Communications, leveraged different techniques in his sales management roles to drive adoption, better visibility, and, ultimately, better forecast accuracy. His techniques ranged from educating the sales force on the value and impact of better sales forecasting, to forecast accuracy team competitions, to having a compensation plan incorporating an accuracy factor.

Although I am in total agreement with the above approach, it needs to be complemented and preceded by the stick method to ensure that the sales reps manage and update their forecasts on a regular basis to begin with. I am sure my current and former teams have fond memories of the stick!

This is a sales management issue that needs to be addressed by sales managers on a daily basis. There is merit in providing incentives for better and more accurate sales forecast contributions but one has to be careful of the context of what one is trying to achieve through the incentives.

Let me give you an example. In a previous life, we used to have a quarterly “closest to the pin” competition where every single person that had a number, sales reps, managers, VPs, would call their number. The company rewarded the ones closest to the pin within certain boundaries (5-10%). What always amazed me about this process was that, although there may have been some value to the whole exercise, it did not tie back to the weekly sales forecast commitments the same people were making. In fact, there were cases where the variance between the two numbers was as high as +/- 30%.

The question is why would it not tie back? For it to be effective in impacting ongoing behavior, I would apply the closest to the pin concept to the actual forecast commitments that sales reps and managers are making at the beginning of the quarter, in the middle of the quarter and with two weeks to go to the end. My strong belief is that any incentive that is put in place should reward sales people for the accuracy of the sales forecasts that the rest of the organization is relying on to make critical business decisions and not reward a siloed guessing process. Only then can one aspire to become a best in class sales forecasting organization and drive value from their sales forecast.

Next week, I will cover the issue around what can be done to help sales people become better forecasters.

Stay tuned.

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The Importance of a Sales Forecast

Monday, June 22nd, 2009

If there is one thing that reps hate to do, it is to input and submit a forecast. How often have you heard “I should be out selling, not updating a sales forecast for my boss!”

The reality is that sales does itself a disservice by not having a sales forecast that drives value across the organization. To create a valuable sales forecast, you need a formalized process across the organization that is enforced at all levels of the company.

Often companies find themselves in the vicious cycle of sales forecasting without them even knowing it. They get sucked into a process that is tactical, time consuming and which, by the time it is complete, everyone in the organization ignores. It is ignored because no one trusts it, the output is seen to be subjective and cannot be relied upon.

Getting to Trust Your Forecast

The process of getting to a trusted sales forecast does not have to be complex, in fact it starts rather simply with getting the sales reps to input their forecasts. How do you get sales reps to regularly input and update the sales forecast on a regular basis?

First, you have to have an executive management team that is committed to the process (why on earth wouldn’t everyone be committed to it given the impact of a sales forecast?) and that clearly communicates and enforces the value of the process.

Without commitment you cannot expect reps to do it on their own!

Secondly: you have to make it really easy for the sales reps to update their sales forecasts. Many companies have shoehorned Microsoft Excel into being the answer. It is by far the most prevalent tool out there being leveraged for sales forecasting. But it’s not the best answer.

Tying the sales forecasting process to a CRM solution like Salesforce CRM, Oracle CRM-on-Demand or Siebel, does make it considerably easier for them. By doing so, the process of updating an opportunity and inputting a sales forecast becomes seamless to sales reps. You have to use the right application for the job.

Thirdly: you have to understand what is changing in the sales forecast and why — this will focus all your conversations during the sales forecast review process.

Lastly: you have to measure the sales reps’ accuracy over time to enable you to hold your sales reps accountable. If the sales reps know that you are monitoring and tracking their every move they may feel less inclined to play games with their forecasts. When sales reps are confronted with the results of their sales forecast submissions, their behavior changes, immediately!

You may never get sales reps to like updating their sales forecast, but at least you will get them to update it on a regular basis with more fact-based information than ever.

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