Chief Pricing Officer

 

pricing and margin in disassembly businesses

 

Back in March, the Chief Pricing Officer wrote about the concept of a pricing waterfall, which was introduced by McKinsey in “The Price Advantage”.  Price waterfall is an important method to determine the pocket price and margin for many businesses, but for disassembly businesses the challenges in calculating margin take a different form. 

 

For disassembly businesses, such as meat processing or lumber, the challenge (which is caused by the nature of the business) is that the organization needs to buy the supply as a whole entity (e.g. animals to process; trees to cut, etc) and then disassemble that entity into sellable parts (e.g. beef primal cut or ground meat for a beef processor; 2×4x12 or 4×4x12 for a lumber company).

 

 

Beef Production

 

 

Lumber Production

 

Part of what makes this even more complicated is the fact that not all the products that are produced have the same value.  For example, in the beef business, consumers will not pay the same price per pound for ground beef as they will for New York Strip steaks. Each cut has its value to the consumer and determining the right prices requires in-depth industry knowledge as well as the appropriate toolset.

 

The lumber industry, encounters similar challenges when pricing the different grades; the price of wood chips is not the same as a 2×4 plank.

 

So why is this such a critical challenge?  Well, at the end of the day, these companies need to ensure that the revenue gained from selling all the finished goods covers their expenses, of which, the raw material often comprises the largest portion.

 

These challenges are the reason that understanding the historical margin at the supply unit level (e.g. live cattle or trees) is crucial to a healthy business.  So what does this have to do with pricing? 

 

In the meat processing business, the overall revenue from a carcass is referred to as the cutout. This represents the total revenue obtained by virtually reassembling the carcass considering each cut’s yield and the price achieved in the marketplace.  Said another way, the cutout calculation takes into consideration the disassembly bill-of-material (BOM) as well as the revenue for the different cuts or pieces. When comparing this overall revenue to the corresponding costs (typically the cost of the whole supply unit – live animal; trees – is adjusted to consider the actual yield of the finished goods), you get a good idea of the gross margin achieved. Historical prices support the calculation of a historical cutout and gross margin picture, enabling disassemblers to understand how their business performed in the past.

 

Even more important however is being able to look forward, by applying the cutout calculation logic to projected costs and selling prices – allowing disassemblers to view forward looking margin.  This is critical to making effective business decisions.

 

To better illustrate the complexity, the following illustrates how carcasses are broken-down into different cuts based on the countries:

 

 

Reassemble Beef Carcasses to Calculate Revenue

 

The lumber industry has a similar challenge as trees are broken down into different finished goods:

 

 

Reassemble Trees to Calculate Revenue

 

And this is what is common between those businesses and the used part dealer – the dealer needs to make sure that when the revenue from the different parts is added up for the tires, windows, body, etc, this revenue exceeds the cost of buying the car and the labor used to disassemble it and market the parts.

 

Managing prices and margin in a disassembly business is different from those portrayed in the previous price waterfall discussion, however mechanisms like cutout help disassemblers better understand historical performance and take proactive, corrective actions going forward just as the margin waterfall helps manufacturers in traditional assembly businesses.

 

 

 

 

Professor Clive Granger, winner of 2003 Nobel Prize in economics, passed away on May 27, 2009. Few will argue that he revolutionized the field of economic time series forecasting. Professor Granger was particularly interested in prices and applied his theoretical ideas of causality and co-integration to financial stock market price time series.

 

He questioned bad econometric practices when he saw them….

 

“Before Dr. Granger’s studies, it was common practice for economists to take methods intended for stationary time series and use them to analyze nonstationary ones. But Dr. Granger — working closely with a colleague at the University of California at San Diego, Robert F. Engle — demonstrated that this approach could produce erroneous results” (http://www.nytimes.com/2009/05/31/business/31granger.html).

 

 

…and determined theoretically-sound concepts to overcome the underlying challenges.

 

“For want of better techniques, economists often applied statistics designed for stationary data to non-stationary data. But in 1974, Granger and his post-doctoral student Paul Newbold, building on the earlier work of the British statistician G Udny Yule, showed that pairs of non-stationary time series could frequently display highly significant correlations when there was no causal connection between them. For example, the US federal debt and the number of deaths due to Aids between 1981 and 2000 are highly correlated but are clearly not causally connected. Such “nonsense correlations” called into question the meaningfulness of many econometric studies.” (http://www.telegraph.co.uk/news/obituaries/finance-obituaries/5407598/Professor-Sir-Clive-Granger.html).

 

Professor Granger was awarded Nobel Prize in 2003 for his foundational work in the area of co-integration.

 

“His innovation has completely changed the way that economists estimate and build dynamic models of the macro economy,” Torsten Persson, an economist at the University of Stockholm who served on the Nobel Prize Committee for Economic Sciences, said at a ceremony honoring Dr. Granger in 2003. “Nowadays co-integration methods are literally used everywhere — by academically minded researchers in universities, as well as more practically minded investigators, be it in central banks or the private sector” (http://www.nytimes.com/2009/05/31/business/31granger.html).

 

As practitioners in the field of pricing, we owe a lot to Professor Granger and his lifetime of dedicated work.