I spent years working closely with engineers at DEC, Sun and other companies – and I always felt a bit sorry for them.

They’d get flayed for every decommit and slip. They’d sweat blood figuring out solutions to hundreds of subtle problems.

Then, after 2 to 3 years of effort, they’d deliver the product to marketing and, all too often, watch their hard work go for naught.

Maybe marketing missed some key features. Didn’t position the product properly. Training failed to equip the field. Mis-pricing. Tougher competition than expected.

Whatever the reason, the problem was often marketing’s. In the midst of a 7-day-a-week slog to ship a product engineers can be forgiven for wondering if their marketing is any good.

There’s a simple, numerical tool for judging how good marketing is.

It’s the forecast, when compared to actuals. If the forecast is accurate to ±3%, you’ve got great marketing. If ±10% you’ve got good marketing. If they’re ±25% or worse and march on the CEO’s office with torches and pitchforks. If the CEO won’t listen, update your resume.

Why forecasts?
Forecasts are the numerical embodiment of the marketing model. Forecast results prove whether or not marketing understands the market.

Despite using a numerical measure, marketing isn’t like engineering. Imagine if you had to use social media to gate electrons, or sales training to control an I/O rate. Marketing tools aren’t precise. But used well, with a deep understanding of market dynamics, great marketing can nail forecasts time after time.

Elements of successful forecasts
Good market forecasts are both top-down and bottom-up, with an emphasis on the latter. Top-down forecasts look at the macro trends of the economy, IT budgets, secular trends in business and technology. Substitute technologies, those that can replace ≈70% or more of a given technology’s benefits, are especially important to understand.

The most reliable bottom-up forecasts come from taking the existing product’s sales and extrapolating from that to the new and improved product. Obviously, if you’re a startup with no shipping products then forecasting becomes much more difficult.

But if your marketing team has prior startup experience, there are elements of the marketing plan and forecast that should be present.

  • Clear delineation of top 2 target markets and their demand (few startups can handle more than 2 target markets, and most are better off with just one.
  • Expected sales cycle: duration; ASP; resource requirements.
  • Deep competitive analysis: incumbents; substitute products; likely competitive responses; competitive strategy; pricing.
  • Sales incentives & training. Make selling easy and profitable.
  • Distribution, marketing & sales strategy congruence.

The biggest weakness I’ve observed in most tech firms – EMC a big exception! – is sales. For example, at its peak as the #2 computer firm, DEC had only penetrated a third of the F1000. Why? They’d never focused on it, and by the time they did it was too late to move the needle.

It’s important to treat sales as a customer, not a channel. If you can’t sell your sales people – whose livelihood depends on believing in your product – forget about selling customers.

The StorageMojo take
This post came partly as a result of reading Superforecasting by Philip Tetlock and Dan Gardner. I hope to review it soon.

The book reminded me of the many forecasts I’ve made over the decades. Short review: a great read and an excellent primer on the statistical and psychological basis of excellent forecasting.

Engineers are measured, and marketing should be too. Forecast accuracy is the best single test of marketing competence.

Courteous comments welcome, of course.