Capitalizing on Capital Goods Replacement Cycles


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How much should capital goods should sellers invest in acquiring and updating identifying which companies have what capital equipment—and even more importantly, when companies will likely begin contemplating replacement? I will unequivocally say, “It depends.”

First, deciding whether locating capital equipment and accurately estimating its lifespan will deliver a positive ROI can be: a.) a no-brainer; b.) a flat out guess; c.) a poker game; or d.) worthy of complex EMV (expected monetary value) diagramming. And it’s not that simple.

Using replacement cycle data is harder than commonly assumed

For example, maintaining lease-end data on automobiles clearly pays off—or clearly should. However, graphing out the ROI, which requires but a simple EMV exercise, would show almost no return for most automakers and most dealer networks. Why? Because with few exceptions, players in the auto industry at all levels can barely spell “nurture marketing.” They confuse bugging customers with meaningless e-mail, postal mail and telemarketing calls positive, value-adding touches. So by lease end, most customers don’t give a rip where they lease their next car. Thus, what should be a “free lunch” winds up “going hungry.”

Hey, even guessing at the return in other product sectors is an improvement. At least there’s an upside.

Replacement cycle data can become a sales impediment

Now, playing the odds as a shrewd card player would seem a better bet. But is it? Only if you know the odds. And in the B2B sector, correctly calculating the odds involves much more than projecting whether or not a company is ready to replace equipment. Equally important to accurately anticipating payback on maintaining a “projected replacement” database is accurately forecasting the likelihood of closing sales, assuming certain companies actually will be replacing equipment as projected. In fact, notifying field sales people that certain companies are projected to replace capital equipment closely resembles sending out non-qualified sales inquiries—which sales people will routinely trash once they discover they’re hardly reliable leads. So the “accurate projection” sales leads get flushed away with the inaccurate projection ones. Along with the potential ROI from building and maintaining the replacement database.

EMV mapping is a dying art

But we still have the EMV approach left for forecasting a positive ROI from this database, don’t we? Well, not exactly. First, changing the forecasting method does nothing for improving outcomes. For sellers that lack the marketing/sales expertise to convert knowledge of equipment replacement likelihood into sales, no return is still no return. Second, in business’s rush to adopt all manner of higher-level statistical analysis it barely understands, calculating EMV has become a lost art. To my knowledge, most business grad programs no longer teach “qualitative analysis,” the discipline centered on EMV. So good thing EMV ROI forecasting isn’t much good to most companies, because they can’t do the EMV part anyway.

So, is maintaining a capital equipment replacement database a lost cause? Despite all my preceding cynicism, not hardly.
Used in the right context, projected replacement date data can create value
With certain pre-conditions met, these database can turn into major revenue generators.

  • The data has to start off reasonably accurate and be meticulously maintained and updated—as in sales flushes untrustworthy data right down the bowl.
  • The data should be incorporated into a CRM system with broad accessibility that creates process triggers and tracks sales follow-up—as in forget about using Excel.
  • Sales people should use projected replacement dates for screen out purposes—as in don’t chase customers in the early years of equipment lifespan.
  • Ideally, replacement projections should trigger tele-qualification calls before ever going to sales—as in never, ever pass on non-qualified sales inquiries to field sales.
  • Marketing and sales have to be capable of converting opportunities into sales—as in good data doesn’t paper over marketing and sales flaws, but makes them more evident instead.

One exception to the rules

But after all that, allow me to make one exception. We’re currently working with a developer/manufacturer of very high-priced instrumentation—as in their lowest grade units start at $500K. And these instruments last and last and last. But “lasting” isn’t the replacement criteria. Disruptive technology drives instrument lifecycle. Periodically, an instrument-maker will achieve quantum performance improvements. At which point, lots of scientists and academic researchers driving these puppies just have to have the latest and greatest, which defines and focuses the replacement cycle. If all companies need do is: a.) know which customers own what; and b.) stay out front technology-wise—this stuff gets lot easier. Still, I didn’t say “easy.” Companies still need to market and sell effectively.

And by the way, be careful what you regard as disruptive technology. Windows Vista is not disruptive. Okay it is, but not in the sense we’re using “disruptive.”


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