Manufacturing

Pricing Challenges and Opportunities

For all manufacturing companies (automotive, computers, electronics, semi-conductors, metals, industrial equipment, pharmaceuticals), pricing is a key profitability lever and Pricing & Revenue Management technology can generate millions in USD/EUR in extra profits. Applications in the automotive industry provide an important case study.

The manufacturing model has moved from BTS (build-to-stock) to BTF (build-to-forecast) and more recently to BTO (build-to-order). In this last model, cars are built to meet customers' individual orders. Many car makers' objective is to build and deliver a car within 15 days. The prize to be won in the form of lower supply chain costs is enormous. A recent study by Mc Kinsey estimates that the amount that is lost by producing cars to meet a demand that never materializes could be worth up to $80 billion a year for the entire car industry.

However, BTO, with its peaks and troughs, has its own costs and limits. Indeed, most car factories do not start to make profits until they are working at 80% capacity. On the other hand, there are some bottlenecks in the factory. A good example is the paint shop. Changing from one color to another causes losses in production time and efficiency that car makers tend to run large batches of vehicles in one color at a time. For these reasons, even if BTO is considered the ideal production standard of the industry, it will never be the exclusive manufacturing model and will continue to coexist with other models like BTF (build-to-forecast).

At this stage in the manufacturing process, Pricing & Revenue Management Technology allows car manufacturers to better match supply and demand.

• On the supply side A factory building different types of cars is somewhat similar to an aircraft flying different types of passengers paying different fares. Like the airline applying yield management techniques, the car maker must allocate its capacity on a monthly, weekly and daily basis to different types of cars and then, needs to allocate these cars to different markets or dealers. These allocation processes receive as input the orders on hand, a forecast of future demand, the levels of inventory, the manufacturing and delivery standards and constraints, including sourcing agreements with part suppliers. The result is an optimum production and delivery plan, as well as the incremental and opportunity costs of each resource and product. These marginal costs determine the starting price at which a sale generates a positive contribution margin. For example, a car built-to-order with a special "blue" colour and delivered within 15 days to a customer may generate additional incremental and opportunity costs of 1.000 EUR.  
• On the demand side By systematically analyzing how the customer and the distribution network react to different levels of price for different product attributes, such as including delivery time, car makers can acquire a knowledge of their preferences and trade-offs. For example, the preceding 'blue" car delivered within 15 days could be worth more at the time of sale if the customer is willing to pay an extra 1.000 EUR for having his preferred color delivered in 15 days instead of waiting 45 days or buying the same model in "black" from stock. This introduces a price differentiation depending on time of delivery and product features. Demand response models estimate on a continuous basis the perceived value of the customer for different product attributes including time of delivery.

Benefits of Open Pricer technology

In the manufacturing industry, Open Pricer Intelligent pricing solutions are integrated on the supply side with SCM (supply chain management) systems and on the demand side with CRM (customer relationship management) and e-business systems. The following are some of the advantages provided by our intelligent pricing technology to manufacturers :

• optimize the negotiation of distribution contracts with distributors and dealers
• evaluate the optimal price to quote for a special order depending on different product attributes and time of delivery
• define how price can be differentiated depending on time of delivery
• calculate the precise incremental and opportunity costs of each order when it is planned or scheduled for production and delivery
• segment customers depending on their price sensitivity
• estimate the perceived value of different products features, including time of delivery
• evaluate the return and define the optimal allocation of promotional budgets (promotions, incentives, advertising campaign)