Lies, Damn Lies – and Forecasts

DartVBoardDartVBoardDartVBoardSales ReportsTo repurpose an old joke, sometimes the only difference between a lie and a forecast is that the person who’s lying knows for sure it’s a lie. If you run a B2B company with a direct sales strategy you rely on accurate sales forecasting to plan and staff. It’s frustrating (to say the least) to be told you will have $X in new orders and end up with a lesser $Y. It may sometimes seem that forecasting is a dice roll, subject to almost random winds of fortune.

In this post, I’ll talk about three of the big factors that affect the accuracy of a forecast: Qualification, Sales Stage and Baseline. A nice side benefit is if you focus on doing better with these three things you’ll not only improve forecasting accuracy, you’ll win more deals.

Thorough Qualification

Two very smart entrepreneurs who were very capable coders headed a software company. Any software pro will tell you that the mark of a great coder is using the fewest lines possible to get results. Their method of qualifying a deal was answering the question: “Is someone there going to buy something like our thing from someone?”

If you think about it, it’s a brilliantly simple question that gets to heart of the matter: Is there a deal in play for which our stuff is suitable?

What you get from this simplicity is a snapshot, gut read of a situation that only includes the buyers in the room at that particular time. Using the “Someone Buying Something From Someone” question as the primary qualifier, the software company’s sales percentage win rate was in the low teens. Worse, the biggest reason for a loss was “No decision”. Which is perhaps the most frustrating conclusion possible, because it means you are chasing deals that never really existed.

A change came by focusing on and tracking deals they could win by using a thorough qualification system. This includes data points you can easily get from (properly) questioning the prospect. (BTW, a sales professional’s job is not to GIVE information – it’s to GET information.)

A sample Qualification Checklist is below. Rate each answer by strength 1-5 highest:

  • Funding – If they don’t have specific funding right now, can your prospect explain the process by which he’ll get it?
  • Product Fit – Based on what you know, is your product/service a perfect fit for the requirements?
  • Purchase Process Identified – Ask your prospect if they’ve bought something similar, and what steps she went through to generate a signed deal.
  • Executive Involvement – Does the signing authorities know this project is happening? Are they attending your meetings or have you seen evidence in email streams that they are involved?
  • Customer Competency – If you’re working with someone who is obviously not a competent businessperson, your chances of getting a deal are lower until you get to someone who’s competent.
  • Intensity/Momentum – How urgent is the buying process? Does the prospect want a proposal ASAP and a demo or meeting in 2 days? Ask when they want to reconnect or get your follow up. If they say “oh, anytime in the next couple weeks. No hurry”. That’s a bad sign and a low rating.
  • Impending Event – Everyone know this one. What is causing the prospect to buy a product/service and are there firm dates by which it has to be bought, installed or implemented? If there is no date, how can you accurately forecast it?
  • Consequence of No Action – Here’s a big one that many people miss. For example, if someone replies that they want to have a decision by October 1, and implement by November 30, your next question needs to be along the lines of “What happens if you don’t make those dates?” Good answers are things like the end of the world, people will be physically at risk, or someone is getting fired. “My boss just told me to have it done by then” is a horrible answer. The boss might change her mind tomorrow and you’re looking at a huge hole in your forecast.

Tally up all your weighted ratings and you’ll find a wide range across your pipeline. Pursue deals with qualification ratings of less than 20 at your own risk. Better: Only pursue deals with ratings above 30 and if you don’t have enough those, spend any the time you’d waste on <20 scored deals in finding better deals.

Important: You must re-qualify your deals frequently. Even if you’re waiting in the lobby to pick up the signed order keep checking to find what has changed and what it means to your probability of winning.

Meaningful Sales Stages/Process

Many CRM systems force you into a forecast that mirrors your sales stages, e.g. 60% probability when a proposal is sent, or 20% when the prospect is “qualified”. You need to override the standard model with very strong, well-defined and pertinent and MEANINGFUL sales stages that reflect buyer actions – not yours.

For instance, using generic sales stages you send a proposal to a prospect and it’s put into your forecast as a 60% probability. This is just because someone sent a proposal – even though you might have NO CHANCE of getting a deal. Why would it make sense to assign a probability of 60% on a $100K deal and have that show up in your forecast as $60K of predicted orders value? If you have 10 deals rated at 60% probability at an average of $100K each would you go on a hiring jag because you’re sure you’ll be getting $600K in new orders next month?

A better method is assigning percentages of probability based on PROSPECT behaviors, combined with qualification scores, along with your previous experiential data. Don’t use a sales-activity based scorecard, use a prospect-behavior scoring system, including the score from the qualification factors above. Combined with a formula in your CRM you can easily see more meaningful forecast data.

Just a few examples of what might go into my formula:

  • My total win ratio after a qualification factor above 35 points is 40%
  • My total win ratio after a qualification factor below 15 points is 5%
  • My ratio of wins to total proposals is 20%
  • My ratio of wins after being told I am a finalist of three competitors is 40%
  • My ratio of actually closing a deal when given a verbal award notification is 90%
  • My ratio of receiving a signed contract back after I’ve countersigned it is 98%

I might even throw in a number/stage for having dinner with the President/decision maker at my prospect’s company. Seriously. To calculate a forecasted amount, I weigh these numbers and come up with formula that produces a consistently better forecast.

Tracking Against a Baseline

When your qualification criteria are zeroed-in, and your sales stages match predictability of an order (versus tracking simply activity) you’re getting close to a predictable truth. Of course, there will always be variability. It’s important to establish and track a baseline of your forecasts compared to actuals over time. If your forecasts are coming in consistently within 5% of your number, you may want to use a 95% number as a planning basis – and not use best case to plan or report. (Note: Some CRM systems do this for you, some can but it’s not simple to set up, and others just can’t without manually exporting.)

This is in line with sales managers traditionally “giving a haircut” to each level in the forecast chain. If I’m a second level manager and I see a forecast for $1M, I may know from experience that a safer number is $950K. No sandbagging, though. Consistently coming in above forecast can be as bad as coming up short to a growing business.

Summary

By thoroughly qualifying your prospects, along with having a well-defined sales process and meaningful stages based on prospect behavior, you can immediately improve forecasting accuracy – and order volume. Understand the right “haircut” value and you can consistently come up with a number that inspires confidence in your CFO!

The smaller the business, or the larger the average order size the more wildly the gap can swing between forecast and actual. (If you have two deals in the pipe for third quarter and one falls out – or both – that’s a huge change. If you have hundreds of deals and push five, not so bad.)

Obviously, there’s a lot more to this topic, but these are definitely important concepts in building and operating your direct sales machine. The sooner you understand and use the data the sooner you can depend on the forecast number for every month/quarter/year.

What are some other important factors in a reliable forecasting strategy for B2B direct sales? Comments always appreciated!

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