The best Formula One drivers rarely blink. Cornering a turn at 155 mph (250 km/h), their eyes dart from one edge of the track to the mirror. But what happens if they’re not seeing clearly?
What if their windshield was 90% obscured?
As a business owner or sales leader, the beginning of each quarter is the starting line of a race — everyone’s scouting for risks and opportunities ahead, eyes darting from the target to the pipeline.
A quick look in the rearview mirror of recent performance could look like the chart on the left.
At first glance, the signs look good. Pipeline coverage — the ratio between what’s forecasted and closed — has floated consistently around 3x. With 3x coverage for the upcoming quarter, everything looks good and predictable.
Or does it?
What we need is to see more clearly. To see the underlying data that show increasing or decreasing predictability.
The chart on the right shows a different reality. The real reality.
In the chart on the right, a smaller percentage of what is forecasted is actually closing over time. When you look at the underlying data and begin to break it down, the picture gets clearer.
“Gravy” is a common sales term. You might have heard something like this before: “Well, we don’t mind that the reps are cautious, it just provides us with upside or gravy.”
We can break gravy down into a few categories. First, there are the deals forecasted to close at certain amounts that actually close at higher amounts. Those higher amounts are “appreciated” gravy. Second, there are the deals that are in the pipeline but not in the forecast due to close dates that are pushed too far out — in pipeline but not forecasted gravy. Third, there’s the gravy that never makes it into your Salesforce data but closes anyway — not in pipeline data.
The problem is that the more gravy you have as a percentage of closed deals, the less predictable your quarters become.
In addition, gravy is invisible to all but the sales rep working on that deal in secret. It can’t be managed or maximized, and a growing reliance on gravy puts attainment in future quarters at risk. Gravy is the antithesis of sales discipline.
The problem with gravy is that it distorts the numbers, making sales harder and harder to manage and predict.
Chasing coverage ratios
Misforecast or unexpected deals are often symptoms of noisy, bad data — incorrect estimates, incomplete entries, or information entered at the wrong time.
Most companies today have this type of bad data, making coverage ratios an illusion. To compensate for bad data in sales, companies put pressure on marketing teams to drive for ever higher coverage ratios — 4x, 5x, 6x.
But inefficient marketing spend defocuses companies and comes at a cost to the business, damaging capital efficiency and margins.
Even bigger risks
Bad data affects more than coverage ratios.
It makes it harder for a team to focus on the right deals. How do you allocate your best resources — your executives, sales engineers, professional services personnel, etc. — to your most important deals, if you’re looking at the wrong data?
To solve these problems, we’ve created a software as a service platform called BadData that analyzes your sales pipeline in Salesforce.com to identify actionable improvements, alert you to where bad data exists, and identify opportunities for coaching and management.
BadData takes a persona-based approach to rank and categorise every region, team, and sales rep in your business by what they achieved and how they attained it. By identifying reps who have a pattern of contributing bad data, we can spot reps who may be stuck, making it easier for you to coach them to success.
It only takes fifteen minutes to see more clearly.