Managing costs in an automated environment
Effective management of cost is often one of the most challenging issues to overcome when designing a product configurator. Costs are influenced by a multitude of factors and are anything but static. Costs are often influenced by quantity, urgency of requirement, choice of supplier and many other factors. Furthermore, costs will change over time as suppliers increase prices, or new competition occasionally drives costs down. How costs are managed in automated systems is a business decision, this article offers one possible strategy.
There are two choices required;
- Market driven pricing or cost-plus pricing
- Actual costs or standard costs
Many configurator variables will be parametric, and these add further complexity to the use of either standard costs or market driven pricing. It will not be possible to define separate part numbers, costs or prices for each incremental change in dimension where the number of variables may approach infinity. It will be necessary to introduce scaling where the cost or price is based upon a reference part of known geometry and a cost factor is calculated to reflect size variations.
Market driven pricing would be difficult to implement in a product configurator because of the need to scale the prices to parametric variables.
Actual costs are highly volatile and would be very difficult to use in a product configurator. The volatility of costs would frustrate customers who may receive two different quotes for the same product. The use of actual costs might hide considerable deviation without recording the reasons for the cost change.
The most practical strategy for a product configurator is to use Standard costs and Cost-plus pricing
Standard costs are entered against each part number in the cost lookup table in the database which are static until changed manually. These costs will be reviewed periodically against “Actual Costs” which have been collected from purchase history. The decision to change a cost will need to be made by a person who is familiar with the purchase history of the part and can make decisions after understanding each variable in the order which could affect the price paid to the supplier.
A variation report is usually run to compare data from the configurator and purchase records in the companies Engineering Resource Planning (ERP system). The scaling parameters for parametric variables will need to be considered.
Material of construction and product finish are further variables which may be calculated without the need for a new part. The decision to manage these types of variables needs to be made when defining the rules used by the product configurator.
In a configured environment, over time and as multiple parts are considered, individual variances will be cancelled out by other parts where the variance occurs in the opposite direction. Overall it should be possible to achieve average cost variations of below 3%. The goal should not be to achieve zero deviation unless the parts are very consistent, but to achieve an acceptable deviation to minimise risk. Considerable efficiency will be gained from automating the estimating and design processes where the aggregate cost deviation will be insignificant.
The purpose of the product configurator is to generate accurate information quickly and dynamically for potentially millions of product permutations. A well-managed cost base will ensure that these costs are available to reflect the configured product at all stages of the configuration process.
To summarise, standard costs should be used, which are compared regularly with actual costs and a variance report generated. This will allow the product configurator to calculate consistent information quickly and dynamically. Where necessary scaling parameters should be incorporated to reduce the number of standard costs managed. Furthermore, prices should be calculated on a cost-plus basis but regularly maintained. Regardless, individual cost variances will occur, but with a well-maintained system the overall cost variance should be managed to a value below 3%.
Written by Peter Slee Smith, Editted by Jason Spencer – 22/03/2018