Years ago, I remember consulting to a small printing firm.
As is often the case in job shops (make-to-order manufacturers), estimation was the system constraint.
Obviously, this wasn’t a good thing. It meant that customers wanted to buy printing; that production had the capacity to fulfill their orders; but that estimating was limiting the flow of Throughput (contribution margin).
Increasing the flow of estimates would provide two benefits:
- It would release a bunch of work into production (where it could be converted into Throughput)
- It would increase the conversion rate (in a high-volume job shop like this, estimation lead-time is a major influencer of conversion rate)
The temptation was to add another estimator. But before we did this, we took some time to observe the estimation function in the context of the wider sales process.
Here’s what was happening:
- Customers would provide salespeople with a request for quote (RFQ)
- The RFQ would sit in a queue for days, and then the estimator would spend a disturbing amount of time costing the job (on a cost-plus basis)
- Salespeople would provide the estimate to clients and then negotiate the price quoted down to market value!
We realized that it simply didn’t make sense to dedicate all that time to the generation of estimates. The firm had production capacity. Within reasonable limits, any work that would generate Throughput was good work!
For that reason, we changed the estimation priorities to:
- Cover raw-material costs
- Win the work
- Generate as much Throughput as possible
Then, to jump-start the process, we got the CEO to make a simple commitment. Each day, before leaving work, the CEO promised to check the estimator’s in-tray. If it contained any RFQ’s that had been received after 3:00 pm, the CEO would *guess* the market value of the job and scribble it on the estimate! These guesses would be transcribed and dispatched first thing the next morning. (The CEO agreed that, with his experience, the guesses would be ‘good enough’.)
The result was that estimates were turned-around in hours, instead of days. The conversion rate increased. Production became busy. And the firm developed a reputation for speed (which, in that industry, is a valuable reputation to have).
Obviously, this approach conflicts with estimators’ cost-plus view of the universe. But the reality is that prices are not determined by estimators; they are determined by the market. It’s better, in most cases, to design a quick-and-dirty estimation process and then have your salespeople negotiate the final price.
In a job-shop environment, we tend to encourage clients to quote a couple of prices, each with different lead times. That way clients can pick their own price (more often than not they’ll elect to pay a premium for a shorter lead-times).
So, how do you calculate the price?
First, you need to accept that accuracy is a mirage. The market sets prices; you don’t. You just need to arrive at a number that:
- Covers your raw material costs, and
- Provides a return on your constraint (capacity-constrained resource) that is comparable to (or greater than) other jobs that you have the opportunity to run in place of this one, and
- Represents good value to your prospective customer
You need a method for estimating that is designed around these requirements. Not a method that’s designed for accuracy.
Often the best approach is to start with a representative set of jobs that you believe have been priced sensibly in the past and then devise a means to adjust the price of these representative jobs to allow for variations.
Fortunately, if you do an analysis of the relationship between the attributes of your set of jobs and the impact each attribute has on the price, you’ll discover that Pareto is at work here. There is only a small number of attributes that impact meaningfully on the price, meaning the rest can be ignored when you create your pricing model.
This approach is a little more structured than the let the CEO guess the price method. And it will enable you to immediately eliminate your estimating bottleneck, win more jobs, and get those jobs into production.
