Are You Ensuring Efficient Manufacturing “Should” Costs?

Michael Doyle March 22, 2017

The whole reason companies have procurement organizations and specialized roles such as Sourcing is because finding market-competitive pricing for goods and services is simply not as straight-forward as one might think.

A 2015 aPriori survey about methods manufacturers use for finding the most competitive pricing indicates the second most common approach is still historical data comparisons:


Methods Manufacturers Use to Negotiate Pricing with Suppliers
Source: aPriori’s 2015 PCM Survey

One of the largest procurement budgets in the world belongs to the United States Department of Defense. In an article he co-wrote and published in 2011, current US Secretary of Defense Ashton Carter (then Undersecretary of Defense for Acquisitions, Technology, & Logistics) suggested the least desirable place to search for efficient cost is with historical data:

“Should cost demolishes the assumption that historical data… represent efficient economical operation. Indeed, in any given program, there are countless processes, technologies, and trade-offs that can increase efficiency, reduce unnecessary overhead, drive down risk, and bring substantial savings over historical ‘norms.’ Program management teams must work diligently to find these opportunities and build them into their program plans and cost estimates to arrive at the program should cost.” – Dr. Ashton Carter & John Mueller


You could probably guess that Dr. Carter’s suggested methodology puts critical importance on establishing an accurate SHOULD-cost estimate, which I’ll define as:

… an estimate of what it should cost to purchase efficiently manufactured goods or efficiently delivered services within a specified market and at an acceptable level of supplier gross profit.

Or, restated as an equation:

SHOULD Cost = (Efficient Supplier’s Cost) + (Efficient Supplier’s Acceptable Gross Profit Level)

Our RFQ Achilles Heel

If we believe in the value of SHOULD-cost estimation, then we must also believe that there are both more and less efficient ways to manufacture custom components.

Let’s say we are sourcing a sheet metal component. Should we focus on suppliers with Progressive Die machines? Turret Press? Laser Cut? Waterjet? Plasma? Oxyfuel? If so, what machine is best for our custom component? What is the most efficient way to manufacture to the tight tolerances we need? Are there more cost-effective materials that still meet spec? Can all manufacturing processes be completed at one factory or will we need to ship partially-completed components between factories?

Relying on the traditional three RFQ samples methodology to find efficiency is a little like determining the biggest fish in a lake from three catches: there are far too many variables for us to believe that three samples found efficiency!

The Power of Two: An Enhanced Sourcing Methodology

What if our procurement methodology included both the RFQ quotes and a SHOULD-cost estimate? Having both would tell us if there are likely manufacturing efficiencies in the market that we’re not seeing from just our three RFQ samples.

Of course, to find manufacturing efficiencies, both our RFQ and our SHOULD-cost estimate must consider the same cost drivers: the same materials, the same feature tolerances, the same annual volumes and batch sizes, and so forth. A methodology considering both might then be:

Such a methodology would let us ask deeper procurement questions: should we negotiate with our preferred RFQ supplier to see if they can be more competitive with our SHOULD-cost estimate? Should we search our supplier database for a more competitive quote? Should we focus on a particular manufacturing process that is best (most efficient) for our custom component? And so forth…

An Enhanced Methodology Means Enhanced Business Intelligence

By collecting our three quotes (with associated suppliers) and our market efficient SHOULD-cost estimate, what might we be able to tell from such combined datapoints?

First, we would have data on our suppliers that told us – on average and over time – how close each supplier is to market efficiency.

Further, we could analyze suppliers (again, over time) to find our most efficient suppliers at the granular level: what suppliers are most competitive in sheet metal manufacturing that involves heat treatments? what suppliers are most competitive in low-volume casting? what Chinese suppliers are most efficient in logistics costs to our Wichita KS headquarters?

Such business intelligence would help ensure our suppliers are only bidding on components where they can truly compete with efficient manufacturing costs, making the entire procurement process more competitive. You get the idea!

Want to Learn More?

Watch this video to learn how aPriori helps sourcing managers quickly and easily generate highly detailed and accurate should cost estimates that enable more productive conversations with your valued supply chain partners.


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