Business & Technology Nexus

Dave Stephens on technology and business trends

Linear Performance Pricing – Part 2

with one comment

In my last post I introduced you to Linear Performance Pricing, a sophisticated method sourcing professionals use to analyze and negotiate pricing on direct material components. Using Linear Performance Pricing, you can pinpoint and correlate the relationship between price and attributes of value, then use that correlation to understand different vendors’ offerings. In this way, buyers can strategically contribute to new product design. And negotiating on price based on how the market measures value can prove very powerful with suppliers.

But we were using Linear Performance Pricing on more mundane matters. As I recall, we had a mini Cooper we were trying to get a great deal on. So, after playing around in Excel, I settled on the following formula to represent the inverse of value (let’s call it wear):

Wear = Mileage + (2005 – Model Year) * Constant

After getting all the data into Excel and scrubbed, I used the LINEST function to compute “m” and “b” (y = mx + b). I also paid a lot of attention to something called “r squared,” which gives us an indication of fit. An “r squared” of 1.0 would be a perfect fit, while values closer to zero indicate poor fit.

I experimented with the Constant until I found a maximum “r squared” of 0.55, which, admittedly, is fairly mediocre. My guess is further filtering of data points to eliminate body damage, poor mechanical condition, etc, would increase correlation. The Constant that “won” was 29,000. The meaning behind this is that as mini Cooper model years go by, older mini Coopers pay a penalty the equivalent of 29,000 miles per year of age. This seems pretty steep. The analysis covered 2002, 2003, 2004, and 2005 model years.

Here’s a chart showing the raw data and the best fit line.

So, you can probably guess what my smart friend did next. He looked at the data points as far below the best fit line as possible – those were the cars with the highest value and lowest cost. Next he had to factor in shipping costs. He was now down to a much smaller list. He filtered that list further by his color preferences and other subjective factors. With the handful that remained he negotiated over the phone, eventually settling on one at an even greater discount.

He had earned himself a sweet deal on an even sweeter ride!


Written by Dave Stephens

02/23/06 10:02 PM at 10:02 pm

Posted in Opinion

One Response

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  1. As a follow-up for those interested, my smart friend was actually looking for a mini Cooper model S over the 2002, 2003, 2004, and 2005 model years. His analysis & LPP took into account regional price differences. What did he learn? There is currently a $3000 plus arbitrage opportunity between the East and West Coast for these cars, and slightly smaller between Texas and the West Coast. When he applied Linear Price Performance regionally he achieved an “r squared” of 0.68, which is a lot better than the non-regionally adjusted 0.55 in my post. And yes he bought one! It’s in-transit to Half Moon Bay currently.

    Dave Stephens

    02/28/06 10:11 PM at 10:11 pm

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