The Streetlight Effect & the Price Waterfall

By Christine Carragee
August 14, 2013

“A policeman sees a drunk man searching for something under a streetlight and asks what the drunk has lost. He says he lost his keys and they both look under the streetlight together. After a few minutes the policeman asks if he is sure he lost them here, and the drunk replies, no, that he lost them in the park. The policeman asks why he is searching here, and the drunk replies, “this is where the light is.”* 

An analogous and similarly ridiculous task, is to search for margin leakage in only the most obvious places, instead of the most likely places.

Every company has a slightly different set of data easily available. Before a pricing software project kicks off, this data is usually already in use in ad hoc reports and sales tools.  Shuttling this existing data into a new software package can have some benefits, but a sustainable profitability lift comes from identifying data gaps and building out a roadmap for obtaining the right data to improve decision making going forward.

Go figure, the pricing department can often provide a detailed and complete set of List Price data which can be benchmarked against transaction prices, so the right side of the waterfall related to price setting is often a quick win to fill out.  Sometimes variable costs, even as basic as getting accurate (updated) unit prices on Cost of Goods Sold (COGS), can be a challenge, but at least in public companies there is legal obligation to maintain this information for accounting purposes.  Fixed costs are usually easy to quantify and measure, but aren’t very useful in short term pricing decisions.  Cost to Serve (CTS) elements related to individual customers are challenging to accurately estimate because they usually come from a shared cost center, like salaries for a National Accounts Support team, which have to be allocated back to the transaction level.

Basic waterfall sections

Poking around in our internal training materials I found this quote:

“The single most important outcome from a requirements gathering phase for a new pricing project is a well-defined waterfall.”

If you’ve ever worked with Vendavo you know that we’re fanatical about price waterfalls.  It’s our go-to chart because it’s a means of visualizing profitability levers (adjustments) and quickly establishing their relative importance.  Defining the waterfall framework takes in-depth business process knowledge and a vision for a brighter future.

Known Unknowns**

A successful first phase in your pricing competency journey is to define the waterfall in detail, but leave placeholders for adjustments that can’t currently be quantified. Defining the waterfall frame work is like acknowledging the need to search places other than under the lamppost; it will help to limit your observational bias. There are two types of approaches:

Option 1:  One adjustment can be used to show multiple related sources of leakage until discrete causes can be teased apart.  This may require the development of a means to capture more granular data at the time of sale or during the negotiation process.

Option 2: The unquantifiable leakage source can be fed in as a zero, overstating existing profitability in the short run, but when its zero for everything, you at least know you have that inaccuracy built in; it’s a known unknown.

Option 3: You are limited only by your own ingenuity.  What other creative approaches have you used, or planned to use to put place-holders into you price waterfall to highlight data needs?  How did you or will you add a flash-light to your key search to get out from under the streetlight?


 *David H. Freedman (2010). Wrong: Why Experts Keep Failing Us. Little, Brown and Company. ISBN 0-316-02378-7.

**Known Unknowns: The Poetry of D. H. Rumsfeld by Hart Seely

  • known unknown , price , streetlight , waterfall

    Christine Carragee

    Christine has a diverse background in pricing analysis and implementation across industries. As a pricing practitioner, she has worked in both B2B and B2C environments and collaborated across functional areas to improve margin performance. Applying her passion for data analysis, Christine has helped Vendavo customers to anticipate their data and reporting needs during requirements gathering in anticipation of the on-going the value realization process. Another component of her work has focused on corporate education and training; ensuring strong project ROI through user adoption and increased pricing understanding.