Contract manufacturers have a unique challenge: we are expected to provide a fixed fee bid on building a product, even though we might not have any prior experience with building it.
The price you charge may turn out to be favorable, and the product is very simple to build. But it is also possible that the risk swings the other direction: there are unanticipated processes, resource requirements, and risks that cause you to spend much more than anticipated on the product. And as you discover each of these surprises, you can see your profit margins slipping. So how can you avoid these surprises?
One way is to do a much more detailed analysis at the time of quoting. Dig into the BOM and drawings with enough detail that you know exactly what will be required to build the product. Involve your engineering team, supply chain manager, and production supervisors so they can give more accurate estimates of what will be required to build it. But, there’s a problem with that: most companies don’t have a quote to purchase order conversion rate that justifies investing this kind of time into providing a quote to the customer.
To address this dilemma, let’s take a look at another industry that has faced this for centuries. Automobile insurance companies get lots of requests for quotes, have very limited information about your driving plans for the next couple of months (road trip?), and have to give you a fixed monthly premium. So what do they do?
As it turns out, for a long time, insurance companies purposely LOST money on automobile insurance. This was because they used it as a way to pull customers into the more predictable and profitable products like homeowners insurance. But there was an exception to this: Progressive Insurance (PGR) was making record-breaking profits in the automobile industry while all of the other big insurance companies were losing money. And it wasn’t because they had a low-cost model like Geico or USAA. So what did they do differently?
They used data. Since the 1950s, Progressive had been investing far more than its competitors to collect data points about their customers. With their data, they could predict with significantly better accuracy the probability and magnitude of loss for a particular driver. With this unique ability to predict a driver’s risk profile, Progressive could confidently underbid or turn away customers that they were not interested in. They did this so confidently, that they started even referring customers to their competitors when their competitor could beat their price. The reasoning was that if a competitor wants to lose money on this customer by underbidding me, then let them. I will hold out for a profitable customer and then eat the costs if it turns out that we miscalculated the resources or risks of building it.
So what can we learn from Progressive for the EMS industry? Having an efficient and accurate method of providing a fixed fee quote can give you competitive access to profitable opportunities. By being efficient, you can pursue more opportunities and provide faster service than your competitors. By having confidence in the accuracy of your quote model, you can also have confidence in your walk-away position during price negotiations. If a price-sensitive customer is trying to move you below your acceptable point, you can feel comfortable knowing that you dodged a bullet. On the other hand, you can also come in below the price point of your competitors who are erring in the other direction to win the business at an acceptable profit margin.
What other industries do you see that parallel the EMS industry’s quoting challenges?
Porter, Michael E., and Nicolaj Siggelkow. “Progressive Corporation.” Harvard Business School Case 797-109, May 1997. (Revised May 1998.)