May 15, 2000, Volume 3 - Number 8

Opportunity Detector

Enterprise commerce management enables fast decision making at every stage of the supply chain

By Thomas Yoder

Two global forces are reshaping retail energy markets and the companies that serve them: the rapid advance in electronic technology and the deregulation of electric and gas utility monopolies. The former is enabling changes in energy supply, transmission, distribution, and whole- sale marketing processes, while the latter is changing the retail marketing process for energy. These two energy sector forces, combined with the broader technology innovation of integrated decision processing evolving from enterprise resource planning (ERP) and customer relationship management (CRM) systems, clearly imply that business pro-cesses and systems in the retail energy industry are due for massive changes.

Retail energy is just one of many industries in which such changes are imminent. Furthermore, in retail energy and other industries such as banking and insurance, supply opportunities depend in part on the demand portfolio, and vice versa: They are interdependent. These interdependencies, along with realtime changes in financial and physical supply markets, geophysical distribution networks, and customer decisions, create tremendous opportunities for optimizing the enterprise. The problem is that these opportunities are far from transparent, especially because the dynamic nature of supply and consumption (especially in retail energy) requires a business process that focuses deeply and exclusively on specific slices of market activity. This narrowly focused process is precisely what obscures the view of the full breadth and depth of the total market. Without an integrated supply-and-demand decision-processing system to uncover opportunities and instruct and execute decisions in real time, fleeting opportunities pass by.

If these forces are present in your industry, you have an opportunity to implement enterprise commerce management (ECM) in your organization. An ECM system optimizes the business enterprise by integrating all interdependent supply-and-demand business components. Unlike ERP and CRM, which concentrate on separate portions of the enterprise-optimization problem, an ECM system enables simultaneous decisions for both sides of the market. For example, in response to physical or financial supply market price changes, managers can reevaluate the current product, pricing, targeting, sales deployment, and supply configurations in light of these price changes and adjust all parameters simultaneously to capitalize on competitive opportunities.

Both Sides of the Coin

The need to execute business transactions effectively and efficiently led to the development of ERP and CRM systems. These execution systems are now evolving to incorporate decision models. However, you should view with caution the development of decision models that require one side of the equation to remain unchanged. These models can be poor choices, especially when they operate in conditions where exogenous market factors and endogenous supply-and-demand portfolios change in real time (which these days is virtually everywhere).

ECM decision models help you make supply and marketing decisions simultaneously to maximize profits. This integration of supply-and-demand results, in mathematical terms, in a globally optimal solution for the enterprise. In contrast, optimizing supply given a customer portfolio (or conversely, optimizing marketing given the supply portfolio) yields a locally optimal solution that may move the enterprise farther away from the path of higher earnings. In other words, constrained models developed within CRM or ERP systems will not, when combined, yield decisions that globally optimize the enterprise, whereas ECM decision models will.

Speed is another advantage. Successful product development links the needs of customers with the delivery and supply of products and services that meet those needs. So does ECM; it compresses the traditional product development process into realtime decisions made on the front lines and executed at the “speed of now.” With ECM, organizations develop new products on the front lines—rather than in the corporate offices—to respond to dynamic internal and external changes. Thus, the new strategic function for corporate product development becomes inventing and developing new capabilities.

When ECM?

The most knowledgeable companies think of their transactions as “controlled experiments” and have healthy analytic data structures that they mine continually. Just as scientists use carefully controlled experiments to explain phenomena, so can you. To explain the effects that marketing decisions have on the likelihood of making a sale, for example, you can evaluate the different communication, channel, product, or pricing tactics (holding constant other factors that determine sales). Statistical analysis can do the job of isolating and quantifying the effects that marketing decisions have on sales, provided that the values of all determining factors for each transaction are captured in the data store. Far more often, however, companies view transactions as costs rather than experiments, and thus have limited, incomplete transaction data.

Again, retail energy is a good example. The transaction data situation in retail energy is very immature given that the market is just now forming because of deregulation. As a result, those companies recording each transaction as an experiment in their data stores may gain a huge advantage in knowledge over their competitors that have yet to enter the market, or those that do not appreciate the value in systematically recording them.

Many enterprises with experience in data warehousing may be ready to advance to integrated decision processing within the ECM framework. Among other things, the development of ECM systems is an analytic exercise in developing quantitative decision models. The status of the technology platforms managing supply and marketing information in your organization will determine whether you can successfully develop such models. For example, the success of airline revenue-management systems was due in large part to the extensive transaction data available for modeling demand elasticity in different market segments. The same will hold true for ECM models.

The overall message is: Before you can take the step to ECM to gain competitive advantage, you need to understand your analytic and decision modeling needs and get your data in order.

ECM From the Ground Up

An ECM system is made up of three key components:

• Decision models that analyze all relevant variables, identify opportunities, and recommend decision options. These models are the heart of ECM.

• A data store that receives and directs data streams through the decision components to business applications. These data streams contain historical and realtime data for variables that affect demand-and-supply opportunities.

• An analyst interface and integration with back-, mid-, and front-office business applications.

The decision models drive the requirements for the data store, and the data and business process requirements drive the development of the linkages to the business applications.

The three main development efforts are specifying and programming the decision models and parameters, designing and developing the data store, and creating the interface and integration with the business applications that execute marketing and supply decisions and track transactions.

In ECM systems, decisions stream to business applications, and the business applications return relevant transaction data to the ECM store. Interactive risk management reporting flows from the system because it provides a total view of the entire supply-and-demand portfolio position. (See Figure 1.)

FIGURE 1 The enterprise commerce management system.

The role of the decision model in ECM. ECM decision models derive from your organization’s optimization challenge: maximizing profits subject to your current supply portfolio, customer portfolio, and risk-management position. Profits are a function of ever-changing market supply-and-demand conditions, supply flexibility costs, and demand flexibility costs. Given these data inputs and the current portfolio and risk position constraints, your enterprise makes supply and marketing decisions to maximize profits. These decisions include physical supply transactions, financial market transactions, scheduling and logistics, product configuration and pricing, and targeting.

The optimization challenge is hardly static because decisions made today can affect options in the future. This dynamic component is captured by the value of decision flexibility for your enterprise and the value of decision flexibility for customers and suppliers. There is value in uncertainty and flexibility, because uncertain events offer opportunities to gain competitive advantages that yield extra-normal profits. But enterprises need the flexibility, or options, to capitalize on these uncertain events. Flexibility is defined by product and supplier features, terms, and prices, the core tactical business decisions for the enterprise. Thus, “measuring” flexibility means capturing the option values of customers and suppliers for different terms and prices.

The ECM decision model combines the product marketing methods of database marketing, product segmentation, and product engineering with those of operations and supply management. The model must account for all internal and external changes in the supply portfolio, the customer portfolio, and market-supply, demand, and competitive forces. The exact specifications of all model structures and parameters are unique to each industry, and even to each company. But all ECM systems must take into account all relationships that flow from market supply conditions to suppliers, through the product, to the customer and the market-demand conditions.

Creating the decision model. Deploying this decision technology is a matter of turning the marketing and supply circuits you use in your business into one “circuit.” The marketing circuit comprises product attributes, customer needs, and prospect characteristics tables. The supply circuit comprises product attributes, supply portfolio characteristics, and customer portfolio characteristics tables. The logical relationships, which extend across the marketing and supply circuits, include customer portfolio characteristics-to-supply characteristics, supply characteristics-to-product attributes, pro-duct attributes-to-customer attributes, and customer attributes-to-customer characteristics.

In addition to the relationships among tables, ECM decision technology also takes into account relationships within each table. For example, in the product attributes component, a price attribute (such as price structure) may highly correlate with a risk attribute (level of price risk for customer, for example). It is important to quantify these intrarelationships so that when a logical change is made to one attribute in response to a change in another, the effects of that change on the product as a whole and the associated target market are well understood.

Every ECM system must have these tables and sets of relationships; you must carefully specify the decision models to achieve profit maximization. This goal requires that the decision models measure the values of expected revenue, expected costs, and net expected flexibility penalties, as well as quantify risk positions. Product-feature elasticities — which measure the percentage change in expected revenue and costs from a percentage change in the value of that feature — are efficient and convenient parameters for decision modeling, but unit-based parameters may also be appropriate depending on the functional form of the relationship.

Figure 2 shows the relationships among all decision tables in a manner similar to a house of quality chart. A house of quality chart is the principal analysis tool used in quality function deployment (QFD) for product development. This chart is an excellent device for depicting interdependent components and their logical inter- and intrarelationships.

FIGURE 2 Decision technology circuitry.

ECM models, however, have different analytic structures and parameters than those depicted in standard house of quality charts. The marketing circuit comprises the familiar product development matrix showing the customer’s needs and the product’s attributes. The parameters indicating the interrelationship among customer and product attributes are developed from product segmentation research, while correlations among product attributes are specified by product engineering. The circuit also comprises customer characteristics and customer attributes components, the interrelationships between the two components, and relationships within each component. Forming the interrelationship is the process of targeted marketing, and the key to developing identifiable prospect lists. Forming the intrarelationships is the process of product segmentation based on customer needs and characteristics.

The supply circuit includes the mapping between the product attribute and supply characteristics tables, and the intrarelationships within the supply component itself. The interrelationship captures the supply-chain management to produce product attributes. The circuit also includes the relationship between the customer portfolio and the supply portfolio, which is the customer scheduling, delivery, and service process.

The circular ECM diagram in the center of Figure 2 represents the joining of two circuits into one. By incorporating all business decisions in an integrated, logical system, ECM decision technology can give front-line analysts options to optimize the enterprise and then execute commerce.

Data Store Story

Understanding whether your enterprise’s data structures are “analytic-ready” is usually the first step in ECM deployment. The data store is the fuel circulating in the engine of the models, the part of the system creating motion in the information delivered by the models. Data must satisfy the format of the variables required by the models, so the data store actually contains components that handle null data and data that falls outside of quality control ranges, as well as data transformation routines.

The data warehouse should include market time-series data and a time series of transactions with customers and suppliers. The transaction times series derive from business applications and the experiment data from which you will develop the models.

The data store receives feeds from markets, usually directly from vendors, and from suppliers and customers — either directly through a data stream or a linked business application. The other business applications that are either standalone or part of integrated ERP and CRM systems provide current portfolio and transaction data to the ECM store.

The requirements for query and data update frequencies are dictated by the definition of “real time” in the business model. In retail energy, for example, market-price fluctuations, interruptions of customer services, and financial transaction times are measured in seconds and minutes, so “real time” implies only trivial delay. Furthermore, transaction time requirements differ from decision time requirements, although these two time measurements are converging because of the speed at which information spreads across the enterprise and the economy.

The Integration Angle

The interface and integration of ECM decision technology and data stores with business applications facilitates the coordinated, front-line execution of decisions at the speed of now.

For example, you can make the CRM system reflect new product configuration and pricing immediately, including the sales-automation system for sales-force execution, the e-channel for sales agents and other channels to act on, and to the e-sales system to market to Internet prospects.

The development of this component of ECM is very specific to each company. The current business applications in use at your company, the degree to which the applications are already integrated, and the specifics of the business process determine the specifications of the analyst interface and the linkages among ECM components and business applications.

When the Levee Breaks

Developing and deploying an ECM system is a tractable proposition, especially because your company can use existing business applications to execute business, and then add only the data store, decision models, and linkages that form the ECM system.

ECM processes and systems may eventually become competitive requirements. Continuing advances in computing technology—along with competitive pressures—will dictate movement toward integrated decision-making, just as the combination of technological forces and competitive pressures have made ERP and CRM requirements for business survival today. The ability to see opportunities that are visible only if looking at both sides of the market simultaneously is the competitive advantage that will drive ECM system deployment.

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Thomas N. Yoder (tnyoder@energyspine.net) is a consultant specializing in marketing processes, systems, analytics, and strategy. He has worked in consumer and business-to-business markets with INC 500 companies, Fortune 100 enterprises, and federal agencies. He is currently developing marketing processes, analytics, and strategy for deregulating retail energy markets.