5.2. Framing the Problem: Understanding the Current State Pricing Process

Jane has a few key ideas in mind that help her focus her initial efforts. She realizes that she needs to form a team in order to have the relevant expertise available. She also needs data in order to identify the root causes that will direct her to solutions. Jane's initial thinking is to design a data set using historical data.

In a previous project, Jane employed an approach based on a Product Categorization Matrix. This tool is based on the idea that the seller should view the product from the perspective of the buyer. Jane feels strongly that such a tool could put sales representatives in a stronger negotiating position for certain products. Consequently, Jane intends to integrate product categorization data into the team's investigation.

5.2.1. Defining the Process

Quickly, Jane pulls together a small team consisting of two sales representatives, a sales clerk, and a Polymat financial analyst familiar with the IT system who knows how to access invoice and sales data. The team members agree that they should focus on improving the pricing management process, that is, the process that consists of setting price targets, negotiating prices with customers, and invoicing and tracking orders after a successful sale. To define the scope and focus of the initial work, the team starts by drawing a high-level map of this process (see Exhibit 5.2).

Figure 5.2. Process Map of Polymat's Price Management Process

Jane checks this scope with Bill, who confirms that this is the right place to start; his management team is already undertaking a strategic review of the market planning process and is looking to simplify Polymat's product range. Bill makes it clear that he expects Jane to help drive improvement in the operational implementation of the stipulated market plans and pricing strategies. This is where he believes a Six Sigma approach will be most beneficial.

Based on discussions with Bill and other members of the management team, Jane also realizes that recent attempts to renegotiate prices with customers have by and large been unsuccessful. Working with the financial analyst on her team, she uncovers data connected to four separate attempts to increase prices over the last two years. Each of these was directed at achieving a 5 percent price increase across Polymath's customer base. None of the four attempts were successful in meeting this target.

5.2.2. Constructing an Analysis Data Set

In thinking about her analysis data set, Jane decides that her main Y will be a measure of the price increase. For each sale, she defines this as the difference between the price charged for the product after the negotiated increase and the price that would have been charged before the increase, divided by the price before the increase. This measure eliminates any currency exchange rate fluctuations that might otherwise complicate the analysis.

Jane also realizes that prevailing market conditions have a pronounced effect on price. The market for Polymat products is highly volatile and can change from demand exceeding supply (a shortage) to supply exceeding demand (an oversupply) in just 6 to 12 months, depending on a number of factors:

• Cyclical characteristics of end user markets (e.g., packaging, electronics).

• Fluctuating oil prices (a key raw material).

• New polymer supply factories coming online (mainly in China and the Far East).

Based simply on market forces, Jane expects that when demand exceeds supply a higher price should be viable (and vice versa). However, she needs to verify that this expectation is supported by the data. So, to better understand the situation, Jane decides to baseline the capability of the current pricing management process using a detailed assessment of two of the recent attempts to impose a unilateral price increase.

After intensive planning and some brainstorming with the team to identify useful data for this investigation, it becomes clear to Jane that information on the experience of the sales representative and on the sophistication of the buyer involved in each sale will be vital. With this in mind, Jane realizes that it does not make sense simply to use a large set of unstructured and possibly uninformative sales data. Instead, she decides to retroactively design and assemble a data set for her baseline assessment. This will both ensure that she has data on the relevant background variables and minimize the time she spends researching and constructing the values of related variables.

Jane constructs the data set for her baseline assessment as follows:

• Products. Working with a member of the Polymat marketing department, she selects 20 products as the basis for the study. These products represent a range of both commodity and specialty product types as defined in the Polymat marketing plan. The products are sold in volume and have a respectable (> 30 percent) combined market share.

• Customers. Polymat is the market leader in four territories: the United Kingdom, France, Germany, and Italy. Jane wants to ensure that the study includes a range of customers from each of these territories. To that end, for each of the 20 products, 3 customers representing a range of different sizes are chosen from each of the 4 regions. Here, customer size is defined as the annual volume in sales made by Polymat to that customer. This results in a total of 240 customers being represented: 3 customers for each of 20 products for each of 4 regions.

• Supply/Demand Balance. To include the effect of market conditions in the analysis, Jane indentifies two price increase campaigns that were run under different conditions. In the first case, the market was tight, that is, demand was close to exceeding supply and there was a relative shortage of polymer product. In the second case, 12 months later, the market had shifted to a point where, owing to new factories coming online, there was oversupply.

Based on this retroactive design, Jane constructs a data table whose rows are defined by all possible combinations of the 20 products, the 12 customers (3 in each of the 4 regions), and the 2 supply/demand balance periods. This leads to 20 × 12 × 2 = 480 records. For each of the combinations of product, customer, and supply/demand balance period, Jane obtains the following information for a sale:

• Sales Representative Experience. Jane and her team believe that the experience of the sales representative is a factor of interest, because at Polymat there is no fixed price for each product. Sales representatives have the responsibility of negotiating the best price based on general guidelines and pricing targets set by their sales manager. Consequently, the price that a customer pays for a product depends on the outcome of the negotiation with the buyer. Jane works with the sales manager to sort the sales representatives into three categories of experience: high, medium, and low. Their categorization is based on each representative's number of years of general sales experience and industry-specific knowledge. For example, a sales representative designated with high experience has over ten years of sales experience and in excess of five years selling at Polymat or a similar business.

• Buyer Sophistication. Because negotiation is a two-way undertaking, Jane wants to explore the relationship between the experience of the sales representative and the experience of the buyer. She expects that price negotiations will differ based on whether an inexperienced sales representative is selling to an experienced and skilled buyer, or vice versa. Jane sits down with the sales manager to categorize the buyer sophistication for each customer that bought one of the 20 products under consideration. High buyer sophistication is allocated to customers whose buyers are highly professional and highly trained, whereas low buyer sophistication is assigned to customers whose buyers are less highly trained or skilled.

• Product Category. This is a categorization of a product and customer into one of four classes, based on how the buying organization views and uses the product. The Product Categorization Matrix section that follows describes this categorization and Jane's use of it.

• Annual Volume Purchased. This is the total amount spent by each customer for this product over the year in which the supply/demand balance period falls.

• % Price Increase (Y). This is computed by taking the difference between the price charged for the product after the negotiated increase and the price that would have been charged before the increase, and dividing this difference by the price before the increase.

5.2.3. Product Categorization Matrix

Jane is concerned about the simple specialty–commodity split that marketing uses to describe Polymat's products. Luckily, in a previous role, she was responsible for a project in which purchasing operations were redesigned. As part of that project, Jane developed a simple tool to encourage buyers to think differently about what they did, where they spent their time, and where they should focus to reduce the costs of the products they bought.

Jane decides to turn this thinking on its head and apply the same idea to Polymat's pricing process. "After all," she reflects, "if you are selling a product and want to get the best price, it's certainly a good idea to think of the product and its value in the same way that a customer would."

Jane pulls the team members together over lunch for a discussion of her proposed approach. She explains that the Product Categorization Matrix will help them to see the product from the buyer's viewpoint, and so should be more informative than the specialty–commodity split that just sees things from the seller's point of view. Jane goes on to say that each sale of a product to a customer can be placed into a two-by-two grid based on the requirements of the buying organization (Exhibit 5.3).

Figure 5.3. The Product Categorization Matrix

The vertical axis, Alternative Sources of Product, represents the buyer's supply vulnerability relative to the product in question. The axis is scaled from Few to Many, referring to the number of potential suppliers. It represents the buyer's risk, posing the question, "What happens if the current seller cannot provide the product?" For example, if the buyer cannot obtain an equivalent product elsewhere or if the product is specific to the buyer's process, then that sale's value on Alternative Sources of Product is Few.

The horizontal axis, Product Volume Purchased, represents the product's relative cost to the buyer. This axis is scaled from Low to High. If a product represents a high proportion of the buyer's spend, the Product Volume Purchased rating of the sale is High.

The four quadrants of the matrix are:

The buyer will typically expend effort in two areas of the matrix: the Strategic Security products and the Strategic Critical products. The buyer will be sensitive to price in two areas: Strategic Critical and Tactical Profit. The buyer's ultimate strategy is to move all of his products to the Tactical Profit quadrant, where he can play one supplier against another, or at least to make his suppliers believe that their products are in this quadrant!

As Jane emphasizes, this product categorization is based on the use of the product. A particular product may be Strategic Security for customer A because alternative products do not give the same consistency of performance in customer A's manufacturing process, whereas for customer B, that same product may be Non Critical, being one of several alternatives that can deliver the consistency that customer B requires.

As the team quickly realizes, this approach to thinking about price sensitivity is situational—it is quite different from simply setting a list price for each product, and will give Polymat's sales representatives greater insight into the price increase a specific transaction may bear. With the team's support, Jane holds a series of meetings with the appropriate sales and marketing personnel to apply their account knowledge in categorizing the transactions included in the baseline data set. When this work is completed, she is happy to see that all four types of sale are broadly represented in the baseline data.