Pricing and revenue optimization

Citation

(2002), "Pricing and revenue optimization", Work Study, Vol. 51 No. 7. https://doi.org/10.1108/ws.2002.07951gaf.007

Pricing and revenue optimization

Pricing and revenue optimization

In simple terms, pricing and revenue optimization (PRO) is the scientific analysis of pricing decisions. PRO manages prices dynamically based on costs, the competitive position, and on the readiness of customers to pay.

For many companies, better management of pricing may be the fastest and most cost effective way to enhance profitability. As long ago as 1992, after examining the economics of more than 2,400 companies, the McKinsey consultancy concluded that a 1 per cent improvement in price creates an improvement in operating profit of more than 11 per cent. This compares with a 1 per cent improvement in variable cost, volume or fixed cost, producing profit improvements, respectively, of 7.8 per cent, 3.3 per cent, and 2.3 per cent.

Given such an average significant gain in profit from even a small improvement in pricing, it is likely that any company can find some opportunity for improvement.

The aim is to apply disciplined analysis and appropriate tools, so that a company can co-ordinate decisions to optimise profitability consistent with strategic goals. As a discipline, PRO is predicated on two fundamental principles:

1. 1.

   All pricing decisions within a company should be managed consistently, utilizing the best information available, in order to enhance corporate profit and meet strategic goals.

2. 2.

   In most cases, pricing decisions can be improved by the application of forecasting and optimisation techniques.

Demand forecasting – an essential component of PRO – has improved dramatically in recent years. Modern statistical analysis techniques enable stable and predictable demand patterns and trends to be extracted from large volumes of data more effectively than ever before. At the same time, dynamic e-commerce applications have brought new flexibility to pricing.

Given these two factors, the application of statistical analysis to demand forecasting – and hence to an understanding of customer behaviour, combined with advanced techniques used to calculate and update optimal prices, provides a powerful tool for helping to ensure that the right price is always offered to the right customer.

Thus, PRO and the underlying preparatory work and analysis help answer questions such as:

• •

  What is the underlying demand for the product?

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  What will be the effects of a price change for this product through different channels?

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  What are the variable costs of selling this product through a specific channel?

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  What are the opportunity costs of selling this product?

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  What is the life cycle value associated with this product?

PRO complements customer relationship management (CRM) and enterprise resource planning (ERP) systems. These provide the data needed to support pricing and revenue optimization.

PRO should lead to directly measurable, improved decisions with rapid bottom line results through real impact on top line revenue.

The basic steps in the pricing optimisation process are:

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  Segment the market. Statistical clustering and categorisation techniques are employed to determine stable and predictable market segments. For example, it may be that large corporate customers in one part of the country are less price sensitive than small corporate customers in another. This information can be useful in guiding the direct sales force or in planning and executing promotional activity.

• •

  Estimate customer price response. For each of these segments and each product, analytic techniques are used to estimate how that segment will respond to price changes for that product. It may that, for example, a 5 per cent increase in price for a product is predicted to cause a 2.5 per cent decrease in sales.

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  Optimise prices.Using these predicted customer responses, an established set of system rules determines which prices to offer to which customers for each product through each channel, in order to achieve the identified goals. These are not necessarily the lowest prices!

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  Improve the system. An effective system will track customer responses to the price changes and "learn" from the results. Effective PRO systems are dynamic and adaptive; their continued success is based on continuous improvement.