Moving the Sales Needle

Apttus and Adobe Echosign earlier this year conducted a survey of more than 100 Fortune 1000 sales leaders, focusing on perennial blind spots for sales managers.

Here’s the big picture view of their just-released findings:

• One in four companies don’t have sufficient KPI insights for average pipeline multiple, deal size, quote-to-cash cycle time and win rate;
• Four out of 10 companies require three days or longer to generate a quote;
• Fifty percent of companies have experienced costly mistakes on quotes;
• One in three companies are not managing renewals effectively and are missing opportunities to capture value; and
• One in five report that forecasts are chronically inaccurate and have a material impact on business planning and spending.

No Winging It

This is reminiscent of the fog of war. Everything looks so logical in the plans, so pregnant with success. Once we get started, though, random events quickly consign the plans to the waste bin. That’s not to say that we’re helpless in the face of reality — and frankly, I am surprised that some of these numbers look so good. The assumption that only one in five companies report chronically inaccurate forecasts, for instance, should not be made beyond the Fortune 1000.

We can reliably assume that in getting to that lofty perch, companies have gone through multiple iterations of sales modeling, planning and training — and that few, if any, of their reps just wing it.

Compare these findings to CSO Insights’ survey of a broader population, and you can see that the numbers are higher for mistakes, and that the blame mainly can be laid at the feet of the 50 percent of companies that don’t have a sales process and therefore don’t enforce one. As I say, that ain’t the F1000.

So take this, if you dare, as a best-case scenario in which most of the right things are being done the right way most of the time in the F1000. This leaves literally millions of companies worse off, and it suggests to me that the sales profession is way late in adopting newer and better approaches to business.

Accurate Modeling

I’ve been doing a lot of work lately with analytics companies like Scout Analytics and Aviso, and I have past experience with C9, Mintigo and many others. In all of this experience, the thing that always rings true is the false security too many people get from using spreadsheets to run forecasts.

A spreadsheet is merely a list of deals and our hunches about how they’re going to turn out. However, because spreadsheets work with numbers, we tend to give them greater value than they should command. Consider this: If your forecast were in a Word document rather than a spreadsheet, would you regard it as highly? Methinks not.

Getting beyond spreadsheets and simplistic forecasting will improve results — but that means developing real statistical models that offer accurate probabilities of deal closure. It also means tracking more deals than we currently do, because the tendency today is to winnow down the list as the quarter winds up so you can focus your energies on what’s really important. Unfortunately, what’s important is usually based on a spreadsheet containing someone’s hunch represented as a number. See the problem?

A better approach — or at least, the one I favor — involves machine learning and treating the forecast as a portfolio rather than as individual deals. When you have a portfolio, you might be more reluctant about winnowing, because every deal has some value. The key is accurately assigning how much value, and using modeling and statistics to figure out not only what’s closeable, but also what could be closeable given appropriate inputs of time and effort.

For instance, maybe a deal is likely to close if you do a second and more detailed demo. Do you have the bandwidth to do that? What else shifts if you do? Most importantly, what combination of tradeoffs like this produces the greatest yield from the portfolio?

Way Past 1.0

While we’re at it, we also need to include renewals and other installed-base revenue in the real forecast. Too often, they’re kept separate, and maybe the chief sales officer has an understanding of their impact — but not always. If you’re segregating hunting and harvesting, you might want to take a new look at that. I know all the arguments about not wanting the sales force hunters to spend their time harvesting the easy revenue, but that’s an idea past its prime.

Reps should be responsible for all the revenue from an account, because accounts are becoming more complex — we’re not just selling version 1.0 any more. Tools like Xactly, which manages compensation processes, make it easy to assign multiple or multi-part quotas to reps, so that each may have an installed-base goal as well as a new revenue goal, as well as any other goal that makes sense, such as new product introductions.

Selling hasn’t changed much in the last couple of decades. It’s gotten faster, thanks to technology, but as I have said before, we’ve gotten just about all the acceleration we can get at this point. Finding ways to work smarter is what will fuel the next performance increase.

In my experience, sales people are notoriously conservative and don’t like change. Fair enough. The route to further growth has to start with businesses forming win-win coalitions with sales teams to evolve their practices through advanced technologies. For me, the message of the Apttus Adobe Echosign report is that mistakes are rather costly, and it’s time to take well-considered actions.