Your sales forecasts are essential, but are they also a disaster in the making?
They could be.
According to a recent survey from InsightSquared, 68% of companies miss their sales forecasts by 11% or more. Only 15% of leaders are satisfied with their sales forecast process.
Their forecasts aren’t working.
What’s worse, only 25% of sales reps, the people actually responsible for closing these deals, are involved in the forecasting process. The VP of Sales, Sales Managers, and Director of Sales are all more involved than the rep doing the selling. The more we look at the common habits involved with sales forecasting, the worse this gets.
It’s a disaster alright.
Why does sales forecasting fail?
It’s not even like these sales forecasts are failing a little bit. They’re failing consistently for the vast majority of organizations.
Here’s another thing that came up in this survey.
“Less than half of opportunities actually close within their original forecast date.” The forecast date moves an average of five times before a decision is made, placing a significant burden on sales teams to monitor and account for these changes.
This is why forecasts are failing.
- Companies are creating inaccurate sales forecasts
- Sales reps, the people closing these deals, aren’t being included in the forecasting process
- Forecasts aren’t being adjusted as deal circumstances change
- Sales quotas are set too low or too high
- Sales teams have limited or poor data on the deals that are in progress
- The employees creating forecasts aren’t (partially) accountable for meeting them
This is no good.
These are consistent problems for sales teams; these issues negatively impact the effectiveness of your sales forecasts. In fact, the most predictable part about sales forecasts is how often they’re wrong.
Does this mean sales forecasting is bad?
Not at all.
It’s just being done poorly.
What makes sales forecasting unreliable?
It’s the ingredients that make sales forecasts unreliable. The outcome will be terrible if you use poor ingredients to bake bread. Forecasts work the same way. The better you are at addressing the factors that go into an accurate sales forecast, the more precise they will be.
Okay then.
Which factors produce inaccurate sales forecasts?
- A sales process: Each sales rep should be able to walk you through your sales process from A to Z. They should be able to provide you with the step-by-step details you need to work with a prospect or customer. This process should outline who does what from the time the lead hits your manager’s desk to an account manager onboarding a new customer.
- Subjective metrics: Do your sales reps know which factors they should look for? Factors like outcome markers (e.g., repeat customers, long history, big spenders, etc.) tell you whether a customer is moving towards or away from the sale. Behavioral factors (e.g., highly engaged, loves and admires your company, etc.) also play a role in this forecast. Your team should (a.) have a list of the factors to watch for and (b.) a way to weigh or measure the value of each factor.
- Poor data entry: If your team relies on tools like spreadsheets to document forecast data, the risk of error is high. The best system facilitates the following: (a.) it allows sales reps and stakeholders to work together to enter forecast data. (b.) Sales reps are exclusively focused on documenting the data, not manipulating spreadsheet formulas or dealing with administrative busywork.
- No/poor training: Sales reps shouldn’t be going with their gut. They should know what’s expected and be taught how to enter their data into your firm’s CRM systems. For example, ‘every interaction should end with a request for (micro) commitments.’ For example, “Can we schedule a call to discuss the proposal together?” The customer’s answer is something clear and objective salespeople could enter into your CRM.
- Sales optimism: This is a good thing – sales reps need to maintain a steady sense of optimism and positivity, but that shouldn’t come at the expense of realism or transparency. If prospects aren’t doing their part to move the sales process along, it’s important to own that. Entering optimistic data (which needs to be defined) poisons historical data, ruining sales forecasts for the future. A good rule of thumb? Be an optimist while selling and a pessimist while documenting.
These factors create forecasting errors.
What about the factors that impact sales forecasts as a whole? You know, the factors that are outside of our control?
- Your organization’s answer (policies) to specific objections (i.e., no refunds vs. a 5 yr. warranty)
- The economic climate (i.e., recessions, booms, industry busts, etc.)
- The political climate (i.e., climate change vs. traditional industry)
- Company reputations (via online reviews)
- Budget and spending
- HR changes (hires, fires, layoffs, promotions)
- Policy changes that make it harder to sell products and services
- Territory changes
- Competitor moves
- Product or service seasonality
- Legalities (e.g., legislation, compliance requirements, industry changes)
Each of these items needs to be factored into your sales forecasts.
The data you need for accurate sales forecasts
If your stakeholders and sales team knows what’s expected, you can produce accurate sales forecasts. That’s easier said than done, though; most sales teams don’t know what they need to create these accurate forecasts.
So, what do sales teams need?
- A sales process: This needs to be clearly defined; your workflows should outline the various stages (e.g., MQL, Contact, Interview, Demo, Quote, Negotiations, Close, Onboard). It should outline the sales process from A to Z, defining who does what, when, why, and how.
- Clearly defined goals: Your team’s goals, objectives, and KPIs shouldn’t be set in stone. There should be plenty of room to iterate. Are sales reps struggling to meet their quota? Find out why then determine if the goals need to be adjusted down or up depending on what you find.
- Sales metrics: This is a list of both specific (e.g., commitments, sharing contact info) and general (e.g., contacts, MQLs, quotes/proposals sent, conversions, etc.)
- Forecast data: Sales teams should have a complete list of the items that need to be entered into the CRM. These items should be easy and simple to enter. Stakeholders should then use this data to update sales forecasts, clarifying the likelihood of the deals going through.
- Exit criteria: Implement exit criteria at each stage of the sales process. For example, Before moving a prospect from the Interview to the Demo stage, sales reps should collect a prospect’s name, email, phone, and LinkedIn. These are objective metrics that verify your prospect’s commitment.
- Post-mortem analysis: Why did your company lose these deals? Your company can receive more historical data if sales managers or team leaders are willing to take the time to reach out to prospects for a 2 min. exit interview. These managers should explicitly state that they’re not looking to sell; they’re looking to learn more about the deciding factor, why they lost the deal, and how to improve.
- Manager investigation: Sales reps and stakeholders depend on managers. They need managers to investigate the commits made by individual sales reps, watching the team’s day-to-day performance closely. Are sales reps struggling to make contact with the MQLs you’ve sent their way? Find out why. Are sales reps telling white lies about the status of their deals? Sniff that out. Counting poor prospects to boost pipeline volume? Stop it.
- Centralized data: You’re collecting (at least) two types of forecasting data. (a.) historical data – past sales data you can use to make (accurate) predictions about the future. (b.) opportunity forecasting, analyzing your in-progress deals to determine which ones are most likely to close. Your historical data should be stored in a system that’s centralized (e.g., CRM, in the cloud) and has strict version control. This gives stakeholders, managers, and sales reps the confidence they need to make decisions based on the pool of data that’s available.
What’s the takeaway from this?
If your sales forecasts are missing these elements, or you’re making the mistakes I’ve mentioned above, your forecasts are costing you money.
How much money are you losing?
Your CRM should tell you. For example, the Lost Deals by Loss Reason report in Pipeline CRM shows you why individual salespeople and the team are losing deals. If you’ve assigned a dollar value to your deals, the magnitude of the loss should be pretty obvious.
Your sales forecasts are essential, but they have to be accurate
As we’ve seen, 68% of companies miss their sales forecasts by 11% or more. Only 15% of leaders are satisfied with their sales forecast process.
Their forecasts aren’t working.
“Less than half of opportunities actually close within their original forecast date.” The forecast date moves an average of five times before a decision is made, placing a significant burden on sales teams to monitor and account for these changes.
The success is baked in at the start.
It’s the ingredients that make your sales forecasts profitable. The outcome will be amazing if you focus on the factors that make your forecasts accurate. Address these factors, and you’ll find your forecasts point to the wins that are rightfully yours.
