October 1, 2012
This is the first post in a series about the evolution of pricing and the renewed focus on profitability.
If you take a step back and look at the evolution of the pricing space, it’s easy to see it as an outgrowth of BI tools. In other words, pricing was simply a very specialized application of enterprise data mining. The idea is that an analyst mines your ERP master data in search of holes in your pricing based on past transactions.
So then the origins of pricing software were rooted in analytics. And many of today’s vendors are still stuck there. But even for those that have expanded the scope of their solutions beyond analytics, this BI pedigree has shaped the approach to solving this problem. More on that in a bit…
But first, what indeed is the problem that these vendors are trying to solve?
The Problem with Pricing
Religious doctrine in the pricing space has long held that the problem pricing vendors are trying to solve is a pricing problem.
Makes sense right? And this is where things go wrong.
Pricing is never the problem. Poor pricing is a symptom of an unprofitable company. Companies must set prices in order to collect revenue for the value they deliver. But if a company could be profitable without ever worrying about price, it would gladly drop this word from its vocabulary. Listing fees aside, does eBay have to concern itself with pricing? No!
So the real problem that pricing vendors solve is profitability. How do you use price (and other means) to improve a company’s profits, so you can grow, invest in R&D, and return value to your shareholders.
It’s Hard to Shake Your Past
Pricing’s origins in analytics has meant that every pricing vendor has approached the profitability problem with an analytics first motto. “First we need to get our hands on all your master data.”
The traditional pricing project has always started with ETL (Extract, Transfer, Load), not to mention transformation and normalization. Once this is done, the traditional project has looked like this:
Your pricing analyst begins parsing through the data in search of valuable opportunities. (Most pricing projects stop here.)
The pricing team works with product management to set better pricing policies and target price guidance. (A few companies make it here.)
Lastly, you deliver this guidance in the form of deal-specific analytics through a quoting solution. Unfortunately, user adoption tends to scrape bottom because this solution wasn’t built with Sales in mind; instead, reps call the Deal Desk after each meeting. (Very few companies make it this far.)
When you have a pricing hammer, everything looks like a nail.
Next week’s post will look at how you can turn this current approach to pricing on its head.