The previous note, The Case for Price Management, dealt with explaining the inadequacy of glorified price and discount list capabilities coming from traditional enterprise resource planning (ERP) and accounting back-office systems.
Given the prospective upsurge of pricing solutions demand, and the fact that an increased focus on change management often leads to better results, many professional services firms have begun to focus on price management. For example, Deloitte Consulting, anticipating a pertinent need, relatively recently launched the Pricing Center of Excellence, which is based on several years of experience delivering price and profit management projects. To that end, the practice has developed a detailed price management implementation methodology; created tools to streamline implementations; and included many vertical industry teams from across the company (from such sectors as the automotive, retail/consumer products, financial services, process manufacturing, and high-tech/electronics industries).
Depending on the pricing problem the company is trying to solve, there might be different pricing processes and software categories, such as:
* price execution
* price enforcement
* price visibility
* price optimization
* pricing management
For example, according to AMR Research, the price execution category is designed to control (or altogether curb) maverick selling practices, and to obtain insight and feedback from the field. This is the process used to capture pricing, most often in tables and spreadsheets, and then distribute that information as predetermined pricing to salespeople, for deal structuring support. In other words, price execution is the process through which prices are delivered and communicated to salespeople and buyers, whereas price enforcement involves the adequacy of the processes and tools (such as workflow management) supporting deal negotiation and contract compliance. Another related term on the execution side is price visibility: once users set a better price and understand how it performs, they want to put this into action and enforce it in the downstream components of the value chain. This execution and enforcement aspect of pricing has been particularly embraced by chemical producers.
Price optimization is the process through which the best prices are determined, based on multiple demand-side variables and market factors. Some of these factors are quantifiable (such as the inventory situation) and some are not (such as competitor moves or seasonality), which makes building pricing models a difficult process. Optimization looks at the profit-critical variables of the business, and advises management on how these variables can be changed to achieve greater total profitability.
In every business, many variables control or impact profitability. Some variables are obvious (such as selling prices), while others are not so obvious (for example, queue time in a production facility). Since these variables are interrelated, the best solution considers the variables within a holistic view of the business, so that over-adjusting some variables does not negatively impact others. As in the aairline industry, the best price solutions monitor the situation in real time, to get the information necessary for making quick decisions. These applications are typically a set of equations and parameters, and are used to decide what is (or is not) an acceptable price, given the customer and the circumstances.
This comes in handy typically when the product is being rushed to the market (such as in the high-tech industry, with its ever shorter product life spans; or in retail, where seasonality changes pricing). If customers are very price-sensitive, then an optimization strategy may be quite effective, and will support improved forecasting and price setting. In the retail and high-tech industries in particular, this can enable user enterprises to pursue a proactive demand management strategy, by linking demand and pricing more closely. However, consumer price tracking is fairly easy, compared to the severe challenge of compiling data across production lines, or of tracking multiple channels and a diverse customer base.
Thus, vendor approaches vary both in the types of information they consider, and in how they use that information. There are vendors who concentrate on high fixed-cost and asset-intensive industries (the chemical, paper, and metals industries, for example), and who focus on asset utilization and constraint variables such as product changeovers and maintenance breaks. There are also vendors who focus on enabling retail to do more with merchandizing variables such as product mix, discounting and promotions, seasonal issues, and so on. Specifically, a retailer might need to understand the impact of markdowns; or a consumer packaged goods (CPG) company typically might need to understand the impact of promotion and new product introduction on demand, in order to optimize profits.
Finally, pricing management provides logic to help with pricing negotiations, in the cases where prices are negotiated rather than set. This provides an opportunity to drive margins based on real-time information from the field rather than on guesses.
But to further cloud the realm of pricing, a complete business-to-business (B2B) pricing system poses large-scale strategic, tactical, and execution level questions that should eventually be answere�. Strategic, or industry price level questions, should help managers understand how supply, demand, costs, regulations, and other high-level factors interact to affect overall prices. Companies that excel at this level avoid unnecessary downward pressure on prices, and often emerge as industry price leaders and market share leaders.
The tactical, or product/market strategy level questions, entail determining the right price for the right customer of a product or service, relative to the competition. With the knowledge of how customers perceive all market offerings, and of which product and service attributes drive purchase decisions, companies can set visible list prices that accurately reflect the competitive strengths and weaknesses of their offering.
The execution, or transaction level questions, described in part one of this series, aim at deciding the exact price of each transaction, starting with the list price, and ending by determining which price waterfall factors are applicable. For most businesses, determining how to process these questions through billing and payment systems, and how to perform order management tasks related to that, is the most detailed, time-consuming, systems-intensive task involved in gaining a price advantage.
Price Management Now a Priority:Price management has landed at the top of the agenda in executives' drive to improve profit margins. More and more companies are pursuing profitable growth strategies, and pricing is one of the last untapped levers for bringing these strategies to life. Having emerged from several years of low growth (and even decline), and facing intense pressure from both competitors and customers, many companies have realized that profitable growth requires a different approach to pricing.
First, as seen earlier in this series, one has to move beyond a mere list price to the price waterfall (a detailed picture of every element of pricing and terms of sale), in order to determine the ultimate profitability of every product, customer, and transaction. Only then can enterprises set prices and policies that meet their profit objectives. Secondly, and perhaps more importantly, the sales force should be equipped with the information and flexibility necessary for negotiating savvy, tailored, personalized proposals that meet the needs and targets of both parties.
In addition to price execution and enforcement capabilities (in the short term), and pricing optimization capabilities (in the long term), all based on customer segmentation, chemical companies have a complex set of price management requirements, such as the ability to manage pricing decisions for both commodity and specialty products and services. Often the customer who pays the highest price per product unit is not necessarily the most profitable for the chemical supplier (for instance, they might not pay for specific services, or might be receiving generous rebates). Specialist producers might want some algorithmic help in creating price strategies that support the commoditization of their specialty products. Both commodity and specialist chemical producers need decision support and negotiation abilities for contracts and spot deals, in light of the challenges and opportunities presented by raw material price volatility. Thus, asset optimization often has to be based on profitability, rather than on traditional plant utilization only.
As hinted earlier, pricing and profit optimization in retail are analytic applications which analyze demand patterns and optimize pricing for each stock-keeping unit (SKU) by selling location, in order to optimize revenue and gross margins. The goal is to adjust prices downward in areas where consumers are price sensitive, in order to increase volume, while raising or maintaining prices where consumers are not price-sensitive, in order to maximize margin. Yet, deciding which SKU in which store location is in which category is not a small exercise, and it is certainly not very intuitive. In the past, such decisions were made by experienced retail buyers, who would scrutinize volumes sales data and rely on their "sixth sense." Furthermore, with a typical large retailer managing thousands of SKUs over several dozens of stores, an expert buyer can only deal with a fraction of the pricing decisions that need to be made in order to maximize revenue. The imperative to respond more efficiently to constantly evolving customer requirements is driving retailers away from clairvoyant human buyers, or investment in expensive in-house development, towards standardized software. Flexible and integrated demand intelligence will thus be a key element of a broad retail offering which supports an efficient response to customer demand.
In general, almost every company could benefit from pricing solutions and improved pricing practices, and should approach the management of selling prices and price increase with the same rigor they use to curb upstream supply chain and manufacturing costs. As mentioned earlier, price management on its own might improve revenue (by a few percent) and gross margin (by umpteen percentage points), but truly amazing benefits generally come only when price management is integrated with appropriate cost information and demand management.
Companies that can shape demand through price changes should focus on a combination of price optimization and price enforcement, whereas other companies might want to start first with price enforcement. Thus, avant-garde companies are turning their focus toward price management, and their direct competitors are feeling the pressure to embark on their own pricing management deployments. To show whether such a solution is needed, the litmus test would be to ascertain how long it takes to process a special pricing request (to determine how convoluted a pricing approval workflow is), to see how long it takes for salespeople to inquire about, look up, and communicate prices.
As price management is an emerging and highly fragmented space, selecting vendors based on their viability is not currently possible, since the space will experience consolidation. Thus, projects which appeal by virtue of proven payback and proof of concept are advised, with on-demand deployment where possible. Since price execution functionality (price list management, discount management, price configuration, etc.) is delivered through ERP functions and data, it is essential that the selected price management product be easily integrated with tools such as master data management (MDM), so as to achieve immaculate order-to-cash execution processes.
In reality, not all businesses are ready to benefit from profit/pricing optimization, but all these optimization products and services are driven by information coming from the users' existing systems, or by information that can be generated economically. Pricing/profit optimization is not magic; it starts with concrete information, and if users do not have the right information, they will not get the right results. Typically, a few years of data history is needed to "prime" the system (meaning lots of data capturing, quality testing, and interaction with the vendor). But some companies will still suffer from the data they do not have, which brings us back to the need to balance pricing with demand management and consumer research (to determine, for example, whether the consumers already feel cheated and resentful about the last price hike).
Given the prospective upsurge of pricing solutions demand, and the fact that an increased focus on change management often leads to better results, many professional services firms have begun to focus on price management. For example, Deloitte Consulting, anticipating a pertinent need, relatively recently launched the Pricing Center of Excellence, which is based on several years of experience delivering price and profit management projects. To that end, the practice has developed a detailed price management implementation methodology; created tools to streamline implementations; and included many vertical industry teams from across the company (from such sectors as the automotive, retail/consumer products, financial services, process manufacturing, and high-tech/electronics industries).
Depending on the pricing problem the company is trying to solve, there might be different pricing processes and software categories, such as:
* price execution
* price enforcement
* price visibility
* price optimization
* pricing management
For example, according to AMR Research, the price execution category is designed to control (or altogether curb) maverick selling practices, and to obtain insight and feedback from the field. This is the process used to capture pricing, most often in tables and spreadsheets, and then distribute that information as predetermined pricing to salespeople, for deal structuring support. In other words, price execution is the process through which prices are delivered and communicated to salespeople and buyers, whereas price enforcement involves the adequacy of the processes and tools (such as workflow management) supporting deal negotiation and contract compliance. Another related term on the execution side is price visibility: once users set a better price and understand how it performs, they want to put this into action and enforce it in the downstream components of the value chain. This execution and enforcement aspect of pricing has been particularly embraced by chemical producers.
Price optimization is the process through which the best prices are determined, based on multiple demand-side variables and market factors. Some of these factors are quantifiable (such as the inventory situation) and some are not (such as competitor moves or seasonality), which makes building pricing models a difficult process. Optimization looks at the profit-critical variables of the business, and advises management on how these variables can be changed to achieve greater total profitability.
In every business, many variables control or impact profitability. Some variables are obvious (such as selling prices), while others are not so obvious (for example, queue time in a production facility). Since these variables are interrelated, the best solution considers the variables within a holistic view of the business, so that over-adjusting some variables does not negatively impact others. As in the aairline industry, the best price solutions monitor the situation in real time, to get the information necessary for making quick decisions. These applications are typically a set of equations and parameters, and are used to decide what is (or is not) an acceptable price, given the customer and the circumstances.
This comes in handy typically when the product is being rushed to the market (such as in the high-tech industry, with its ever shorter product life spans; or in retail, where seasonality changes pricing). If customers are very price-sensitive, then an optimization strategy may be quite effective, and will support improved forecasting and price setting. In the retail and high-tech industries in particular, this can enable user enterprises to pursue a proactive demand management strategy, by linking demand and pricing more closely. However, consumer price tracking is fairly easy, compared to the severe challenge of compiling data across production lines, or of tracking multiple channels and a diverse customer base.
Thus, vendor approaches vary both in the types of information they consider, and in how they use that information. There are vendors who concentrate on high fixed-cost and asset-intensive industries (the chemical, paper, and metals industries, for example), and who focus on asset utilization and constraint variables such as product changeovers and maintenance breaks. There are also vendors who focus on enabling retail to do more with merchandizing variables such as product mix, discounting and promotions, seasonal issues, and so on. Specifically, a retailer might need to understand the impact of markdowns; or a consumer packaged goods (CPG) company typically might need to understand the impact of promotion and new product introduction on demand, in order to optimize profits.
Finally, pricing management provides logic to help with pricing negotiations, in the cases where prices are negotiated rather than set. This provides an opportunity to drive margins based on real-time information from the field rather than on guesses.
But to further cloud the realm of pricing, a complete business-to-business (B2B) pricing system poses large-scale strategic, tactical, and execution level questions that should eventually be answere�. Strategic, or industry price level questions, should help managers understand how supply, demand, costs, regulations, and other high-level factors interact to affect overall prices. Companies that excel at this level avoid unnecessary downward pressure on prices, and often emerge as industry price leaders and market share leaders.
The tactical, or product/market strategy level questions, entail determining the right price for the right customer of a product or service, relative to the competition. With the knowledge of how customers perceive all market offerings, and of which product and service attributes drive purchase decisions, companies can set visible list prices that accurately reflect the competitive strengths and weaknesses of their offering.
The execution, or transaction level questions, described in part one of this series, aim at deciding the exact price of each transaction, starting with the list price, and ending by determining which price waterfall factors are applicable. For most businesses, determining how to process these questions through billing and payment systems, and how to perform order management tasks related to that, is the most detailed, time-consuming, systems-intensive task involved in gaining a price advantage.
Price Management Now a Priority:Price management has landed at the top of the agenda in executives' drive to improve profit margins. More and more companies are pursuing profitable growth strategies, and pricing is one of the last untapped levers for bringing these strategies to life. Having emerged from several years of low growth (and even decline), and facing intense pressure from both competitors and customers, many companies have realized that profitable growth requires a different approach to pricing.
First, as seen earlier in this series, one has to move beyond a mere list price to the price waterfall (a detailed picture of every element of pricing and terms of sale), in order to determine the ultimate profitability of every product, customer, and transaction. Only then can enterprises set prices and policies that meet their profit objectives. Secondly, and perhaps more importantly, the sales force should be equipped with the information and flexibility necessary for negotiating savvy, tailored, personalized proposals that meet the needs and targets of both parties.
In addition to price execution and enforcement capabilities (in the short term), and pricing optimization capabilities (in the long term), all based on customer segmentation, chemical companies have a complex set of price management requirements, such as the ability to manage pricing decisions for both commodity and specialty products and services. Often the customer who pays the highest price per product unit is not necessarily the most profitable for the chemical supplier (for instance, they might not pay for specific services, or might be receiving generous rebates). Specialist producers might want some algorithmic help in creating price strategies that support the commoditization of their specialty products. Both commodity and specialist chemical producers need decision support and negotiation abilities for contracts and spot deals, in light of the challenges and opportunities presented by raw material price volatility. Thus, asset optimization often has to be based on profitability, rather than on traditional plant utilization only.
As hinted earlier, pricing and profit optimization in retail are analytic applications which analyze demand patterns and optimize pricing for each stock-keeping unit (SKU) by selling location, in order to optimize revenue and gross margins. The goal is to adjust prices downward in areas where consumers are price sensitive, in order to increase volume, while raising or maintaining prices where consumers are not price-sensitive, in order to maximize margin. Yet, deciding which SKU in which store location is in which category is not a small exercise, and it is certainly not very intuitive. In the past, such decisions were made by experienced retail buyers, who would scrutinize volumes sales data and rely on their "sixth sense." Furthermore, with a typical large retailer managing thousands of SKUs over several dozens of stores, an expert buyer can only deal with a fraction of the pricing decisions that need to be made in order to maximize revenue. The imperative to respond more efficiently to constantly evolving customer requirements is driving retailers away from clairvoyant human buyers, or investment in expensive in-house development, towards standardized software. Flexible and integrated demand intelligence will thus be a key element of a broad retail offering which supports an efficient response to customer demand.
In general, almost every company could benefit from pricing solutions and improved pricing practices, and should approach the management of selling prices and price increase with the same rigor they use to curb upstream supply chain and manufacturing costs. As mentioned earlier, price management on its own might improve revenue (by a few percent) and gross margin (by umpteen percentage points), but truly amazing benefits generally come only when price management is integrated with appropriate cost information and demand management.
Companies that can shape demand through price changes should focus on a combination of price optimization and price enforcement, whereas other companies might want to start first with price enforcement. Thus, avant-garde companies are turning their focus toward price management, and their direct competitors are feeling the pressure to embark on their own pricing management deployments. To show whether such a solution is needed, the litmus test would be to ascertain how long it takes to process a special pricing request (to determine how convoluted a pricing approval workflow is), to see how long it takes for salespeople to inquire about, look up, and communicate prices.
As price management is an emerging and highly fragmented space, selecting vendors based on their viability is not currently possible, since the space will experience consolidation. Thus, projects which appeal by virtue of proven payback and proof of concept are advised, with on-demand deployment where possible. Since price execution functionality (price list management, discount management, price configuration, etc.) is delivered through ERP functions and data, it is essential that the selected price management product be easily integrated with tools such as master data management (MDM), so as to achieve immaculate order-to-cash execution processes.
In reality, not all businesses are ready to benefit from profit/pricing optimization, but all these optimization products and services are driven by information coming from the users' existing systems, or by information that can be generated economically. Pricing/profit optimization is not magic; it starts with concrete information, and if users do not have the right information, they will not get the right results. Typically, a few years of data history is needed to "prime" the system (meaning lots of data capturing, quality testing, and interaction with the vendor). But some companies will still suffer from the data they do not have, which brings us back to the need to balance pricing with demand management and consumer research (to determine, for example, whether the consumers already feel cheated and resentful about the last price hike).
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