Tuesday, July 6, 2010

Best Practice: Pricing Optimization

By Pradip Krishnadevarajan, Texas A&M University

Senthil Gunasekaran, Texas A&M University

and Dr. Barry Lawrence, Texas A&M University

Companies have been facing gross margin pressure for many years. The real issue is profitability threatened by customer price pressure (the upper boundary of the gross margin) and a declining ability to reduce cost of goods sold further (the lower boundary of the gross margin). Companies have addressed the problem through attempts to decrease the cost–to-serve, thereby increasing the percentage of profit contained within the gross margin. As the gross margin shrinks, the increased profit percentage can “hold the line” on net profits. Unfortunately, the customer has anticipated increased efficiencies and is requiring higher service levels. The result is a constant battle to protect shrinking net profits. In light of these difficulties, many firms have turned to more scientific pricing methods. Pricing is typically market-based, but pricing decisions are very complex and, when made in an information vacuum, will suboptimize gross margins for the firm. The pricing/discounting decision is an information exercise and determines at least half of the firm’s profitability equation.

Most firms have been experiencing a constant gross margin percentage decline during the last four years. The median gross margin percentage for various publicly traded distributors in the distribution space has dropped from 27.2% to 26.5% from 2006 to early 2010 based on data (aggregated by the authors) from a series of reports published by Modern Distribution Magazine (Baird & Co, 2006-2010).

The current No. 1 best-selling NAW Institute for Distribution Excellence book, Optimizing Distributor Profitability: Best Practices to a Stronger Bottom Line (available at http://www.naw.org/optimizdistprof), details best practices, their implementation, and ROI. These practices are valid in any economy, but the significance of one best practice versus another may change under different market conditions. Each month in this blog, we have introduced a best practice and how it can improve earnings and/or ROI under current economic conditions. We encourage you as you participate in this blog to ask questions, debate results, and offer your own experiences with such practices, so that we may further the knowledge of the community and the understanding of the science of distribution.

The book breaks business processes into seven groups (SOURCE, STOCK, STORE, SELL, SHIP, SUPPLY CHAIN PLANNING and SUPPORT SERVICES) based on various distributor asset categories. This month, we focus on SELL as shown in exhibit 1.

Best Practice: Pricing Optimization

Pricing is the gross margin inverse of asset management and procurement procedures. Pricing decisions are very complex. Pricing is typically market-based and, when made in an information vacuum, gross margins can be suboptimized. Since pricing requires basing decisions on a large amount of information, it requires system support. Wholesale distribution pricing has traditionally been approached as an art and not considered a science. Pricing/discounting decisions represent at least half of a distributor’s profitability equation. Pricing decisions on products and services are critical to increasing revenue, profitability, and market share. Applying scientific decision making to pricing is a potential focus area for profitable revenue management.

The practice levels for Pricing Optimization are as follows:

COMMON practice: 1) Cost-plus pricing (2) Cost-plus driven matrix pricing (3) List price or list-less pricing.

GOOD practice: 1) Value-based pricing (2) Pricing matrix based on customer stratification and seller’s item visibility (item stratification).

BEST practice: 1) Pricing optimization models (2) Pricing matrix based on customer stratification, seller’s item visibility, customer’s item visibility, unit cost, and historical gross margins (3) Pricing rules/heuristics.

The most common forms of pricing methods are cost plus, value based, and market-based pricing. In most cases, all three methods are based on a single dimension, which could be cost, value, or competition. The following are characteristics of best practice models:

  • They are easy to understand and apply when compared to a complex mathematical environment.
  • The core of the model should be based on variables that are typically readily available and/or easily quantifiable.
  • They should address data availability and quality issues.
  • They should leverage and integrate with existing system processes (for example, inventory stratification).
  • You should be able to implement them quickly with minimal IT resources.
  • They help achieve incremental business impact (ROI) by using simple pricing models before moving to complex pricing models.

Poor pricing polices and guidelines, a lack of data-driven information, too much speculative information, and the lack of a structured pricing framework will result in margin erosion and pricing inconsistencies. All of these result in the inability to price using item, customer, geography and time combinations. Failure to price effectively results in the following ways:

  • Paying customers in services to take products
  • Falling into a price lock once companies set an initial price; it is very difficult to increase later
  • Losing the opportunity to take advantage of low-visibility and low-sensitivity items that the customer buys infrequently
  • Leaving money on the table and maximizing revenue at the expense of profitability.

Distributors often try to increase revenue through discounting to attract more customers. This strategy often backfires and ends up generating lower margins. The pricing optimization framework developed by Texas A&M University’s Supply Chain Systems Laboratory is shown in exhibit 2.

Exhibit 2: Pricing Optimization Framework.

This model is designed for implementation in most IT systems. The model is in no way designed to replace a salesperson or pricing analyst. Instead, the process is designed to provide, in a concise manner, relevant information formatted for use without looking through several different screens in the system and conducting significant offline deduction. The system is the science, and the salesperson brings in the art to make an effective pricing decision. The sales force may feel that they are familiar with whether a customer is profitable or not. However, when you have thousands of products and hundreds of customers, no human being can process that much data. A computer can calculate it in a split second.

Pricing in Action

Weather Supply Company (WSC) is a regional heating, ventilation, and air conditioning (HVAC) distributor that sells in three states with 25 stocking locations in the Southwest. Established in the late 1960s, this company is one of the largest independent wholesaler-distributors in the region. The company sells a full line of HVAC equipment, controls, pipes, valves, and industrial supplies for both commercial and residential construction. WSC provides in-depth industry knowledge to help customers develop comprehensive solutions in a fast-moving, rapidly changing business environment. The 25 branches are grouped under five regions.

WSC was growing rapidly, with multiple acquisitions in the past couple of years. Not only had the distributor’s product lines been growing rapidly, but its customer base has been expanding quickly as well. The growth caused the company to expand its service offerings. The distributor had a high cost-to-serve, and it relied on many suppliers. Management wanted to perform a customer stratification process to determine which customers it could grow with and still stay profitable. They wanted to perform the stratification for the following reasons:

  • Pricing decisions. Different customers require different levels of service. Some customers purchase higher quantities, while others purchase lower quantities. These factors contributed to different costs for different customers. The customer stratification process would help WSC understand where each customer stood with respect to cost-to-serve. This stratification would also help in contract bidding processes.
  • Negotiations. If a salesperson had information about the characteristics of the customer with respect to other customers, he or she would be better positioned to make the right decisions.

  • Resource allocation. Sales force and logistics deployment decisions could be made based on customer stratification. For instance, WSC could assign the top salesperson to the most promising customer. The company was performing a great deal of research in lean sales processes. Eliminating nonvalue-added activities from the sales process is the critical success factor to a lean activity. The customer stratification process laid the groundwork for these initiatives.

  • Areas of opportunity for future growth. There were areas of opportunity to grow in both customer and product market share. A pricing process driven by the customer stratification process would guide WSC in developing strategies for identifying and capturing those opportunities. It could also provide a roadmap for the marketing department to focus its efforts on these prospects.

WSC decided to apply Texas A&M’s pricing optimization framework. WSC’s analysis was done using a Microsoft Access-Excel custom tool developed especially for this project. The tool was used to demonstrate the methodology and identify pricing opportunities. WSC’s management was ready to implement the practice in their ERP system, but the system could not accommodate certain features of pricing rules and final price calculations. They were able to change the configuration for customer and item analyses, but WSC asked its ERP provider for help in implementing pricing rules. As part of the negotiation, they came up with a creative and collaborative approach to implement the best practice and share the resulting costs. The ERP provider programmed the best practice and the distributor served as a knowledge pilot base for programming and development.

WSC brought its 250 key personnel (branch managers, sales managers, sales executives, and customer service associates) for three one-day education sessions to discuss the methodology and its results using WSC’s data. WSC also unveiled a performance plan that explained how the project’s outcome would be linked to employees’ performance. The plan set the stage for stakeholders to apply what they learned in their day-to-day jobs and provided momentum for sustaining best practices in the future. WSC’s pricing implementation was completed in three months, and the ERP provider’s implementation was completed three months later. WSC’s sales reps applied the pricing tool in their pricing decisions. The six-month journey resulted in improvements to shareholder value. Exhibit 3 shows the margin improvements in a few select locations. There was no drop in sales, since the price increases were conservative. The average GM% increased by 4.3% points.

Exhibit 3: Pricing results.

The following conclusions are drawn from the Pricing Optimization research consortium findings and our experience with hundreds of best practice implementations and educational sessions—which provided the opportunity to observe, interact, and learn from thousands of distribution professionals—over the last 10 years:

  • The potential for pricing improvements exists.
  • Incorporating both quantitative and qualitative information is a must for successful pricing decisions, but the process should be defined unambiguously.
  • Involvement of information technology personnel in pricing implementation (from day one) is paramount.
  • Educating the tactical pricing team (inside and outside salespeople, sales and marketing manager, and branch manager) on pricing methodology and getting their buy-in is the single-most important factor in any successful pricing implementation.
  • Defining and detailing the roles and responsibilities of various stakeholders involved in the pricing process is a key factor (Who does what and who is accountable for what?).
  • Finally, defining quantitative metrics and connecting them to incentive or compensation structure is a vital link in sustaining successful best-practice implementations.

About this Blog

“Managing in an Uncertain Economy” is a blog created by the Council for Research on Distributor Best Practices (CRDBP). The mission of the CRDBP, created by the NAW Institute for Distribution Excellence and the Supply Chain Systems Laboratory at Texas A&M University, is to create competitive advantage for wholesaler-distributors through development of research, tools, and education. CRDBP encourages readers of this blog to send in comments and e-mail this blog to other interested parties.

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