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Your Best Pricing Solution Might Not Be Ideal

Most of the pricing people I know are bit like engineers. They tend to be a lot more analytical than the average person. They’re accustomed to dealing with complex problems that involve more than one variable. And they’re pretty good at devising the ideal solutions to the problems they encounter.

But like many engineers, pricing people…myself included…will sometimes overlook the “user environment” in our solution designs.

(Personally, I prefer think that we’re just overly optimistic about the user environment. It’s not so much an oversight on our part, but more a matter of having higher expectations. That perspective makes me feel better. But you can make up your own mind on this point. Ha!)

As we discussed in the “Better” Practices for Pricing Improvement webinar, the “best” pricing solutions are the ones you can actually execute.

Now, these solutions may not be “ideal” from a technical perspective. But they’re the ones you can actually get through the gauntlet of the status quo and over the wall of resistance to change.

And no, these solutions probably won’t rise to the lofty level of “best practice.” But they’re a big step in the right direction and they are certainly “better” than having no solutions at all.

Simply put, a relatively basic pricing solution with 90% adoption and utilization will always…and without exception…outperform the most technically-sophisticated and robust pricing solution that no one uses!

In the webinar, we explored a number of “better” pricing solutions and practices that others have employed. These approaches were all based on best practices, but simplified and deprecated to suit the particular environment. And relative to the status quo, each of these “better” solutions still managed to produce significant gains and performance improvements.

In some conversations after the live session, however, I sensed a bit of discomfort with employing anything less than the ideal. For these practitioners, the notion of devising the ideal solution on paper and then implementing something lesser just seemed like settling…or maybe even giving up.

But after I pointed out that their formula for what actually constituted ideal was missing an important variable—i.e. an “adoption and utilization” factor—they felt a lot better about it. You see, when you include adoption and utilization into the equation, the supposedly lesser solution often becomes the ideal…and the formerly ideal solution often proves to be unworkable.

Did I mention that pricing people are a bit like engineers? 🙂

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