Last week a friend told me that her sister’s business had overpaid their taxes and without justification the government would not refund the overpayment. I was skeptical of the story and responded that there is a very clear process for requesting refunds of overpaid taxes or applying them to the subsequent year, and the IRS would not just ignore that. My friend was adamant that her sister would not make something up and she believed her. Not long after that conversation, I read an an article Misleading Statistics, by Thomas Sowell. In the post, Sowell focused primarliy on statistics that might be accurate in and of themselves, but are then used incorrectly to support something that is not true. Although these situations are very different, they are good reminders that people will believe statements, anecdotes, and plausible-sounding statistics that support their ingrained beliefs. It is therefore important to be skeptical of sound bite statistics, and require your team to provide the whole truth and nothing but the truth.
Pricing strategies and individual pricing decisions are areas where incomplete or misleading data are often presented. There is a general perception that higher prices will reduce sales, and management teams will often hear that a firm’s prices are an obstacle to greater success. While in a macro sense, there is some truth that prices will affect volume, prices are usually not the number one factor in a customer’s decision of whether and where to buy something. So simple statements that pricing was the reason business was either won or lost are usually not the whole truth. For example, these statements could be heard in businesses all over the world:
- We are not hitting our sales targets because competitor X is undercutting our prices
- We raised our prices this year and we are losing sales because of that
- We are losing sales because our approval process takes too long
- We are losing bids (or we lost those bids) because our prices are too high
All of these statements could be true, but could also be misleading. They all need more details to determine if they are the whole truth. Some additional information I would want to know include:
- Is competitor X’s market share growing while our share is shrinking?
- Are our existing customers switching from us to X, or is X simply serving a faster-growing segment?
- Are we losing business to X in multiple geographies or is it limited?
- Is there any correlation between the magnitude of our price increase and the volume we have lost?
- Have we actually measured the elasticity of our sales?
- Is that elasticity consistent within segments and customers, or does it appear random?
- Is that elasticity consistent within a product category?
- Have the number of prices requiring approval increased or have we deteriorated in our approval times?
- Do we measure how long it takes us to approve prices?
- Is there any correlation between our win/loss rate and our approval time?
- Which steps in our process are taking longer than they used to?
- Are the price levels (not just margins) on deals we won lower than on those we lost?
- What is the correlation between price levels and win rate?
- Have our win/ loss rates changed among incumbent customers?
- Have our win/ loss rates changed when trying to win business from competitors’ existing customers?
- How do our prices compare on bids for existing business versus new business?
- Are our win/ loss rates consistent across customer segments?
You get the idea. There are many more questions that can and should be asked to get to the whole truth. If you don’t obtain the whole truth, you could make pricing decisions which actually make results worse than if you had done nothing. If you lower prices in an attempt to win more business, you could destroy the margins on business you are already winning, but capture little upside in return.
When a data point or statistic fits an employee’s preconceived view, they often do not dig for more facts. They simply present the data and their conclusion, and they want you to agree. But remember, that statistic could be misleading and needs context. Although it takes organizational effort, insist on getting the whole truth and nothing but the truth.
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