To be successful in business, we have to be ready for major new developments that are just out of sight. Right now, what's over the horizon is a veritable mountain of opportunity. We'll call it the intelligent market, or i-market.

The i-market is developing where business intelligence and e-business meet. This convergence is analogous to the intersection point of continental plates. Upon collision, they create powerful eruptions resulting in a vast new landscape in which grand mountains rise from the earth. Those who have the creativity and pioneering spirit to exploit this convergence will be able to deliver both better information and better access to it. Now that's a competitive opportunity worth pursuing.

Before outlining the potential of i-market, it will be helpful to review the trends that preceded it.

The BI/DW Trend

Over the past five to seven years, the data warehouse (DW) has become a standard component of the architecture and strategic direction of most businesses. Whether a company chooses to implement a top-down, enterprise-driven data warehouse strategy or applies a bottom-up, departmental data mart strategy, there is a driving need for businesses to assess and improve their competitive position in the marketplace. This business driver manifests itself in the race to collect information, analyze results, predict future trends and make well-informed tactical and strategic business decisions. These decisions affect a myriad of corporate subjects, from customers to products to suppliers and distributors, for a wide range of industries from retailers and manufacturers to banks, healthcare providers and airlines. We are witnessing an ever-increasing demand to deploy data warehousing structures and business intelligence (BI) tools to operate against them.

The past several years have uncovered an interesting trend in the value proposition of the data warehouse and business intelligence. The value of data warehouses and business intelligence applications has increased significantly. The need for reporting has moved from static reporting to proactive/interactive information discovery, from highly structured data to more unstructured information. The primary purpose of the data warehouse is shifting from a focus on data transformation into information to ­ most recently ­ transformation into intelligence. In order to better understand this trend, it is useful to look at the curve of value over time for data warehousing.

As depicted in the business intelligence value curve (see Figure 1), the context of the data warehouse has changed with time, moving from a focus on static reporting to a focus on the business intelligence value chain. This evolution in data warehousing can best be understood by example.

Figure 1: The Business Intelligence Value Curve

Static Reporting (Information)

The need for information has always been part of business. There are a variety of systems that are designed to get information in (operational systems) to process transactions and manage business operations. Likewise, there are countless systems that are used to get information out (data warehouse) to support business decision making and reporting across the enterprise. Both of these systems can generate static reports, the most memorable of which is the green bar report that was physically printed on green bar paper. These management reports were extremely costly because stacks and stacks of reports were mailed or delivered to desks across the company, country and even the globe. The recipients of the information would have to sift through the reports to find the critical piece (s) of information and try to relate them to other reports containing other critical piece(s) of information. Although these reports provided the information needed, they were not well integrated, easy to use or interactive. These frustrations, and the continuing business need for intelligent information, led to the second phase of the business intelligence value curve.

Subject-Oriented Data Warehouse (Intelligent Information)

In the early days of the data warehousing discipline, the data warehouse was often built as a means to make highly structured reporting results available in a more timely fashion. It was not unusual to see early data warehouse deployments justify their development based on cost avoidance of report generation from transaction systems. Such transaction systems were not optimized for ad hoc reporting or historical trend analysis; therefore, data was moved into the warehouse where it could be more easily manipulated and reported upon. The primary focus of the data warehouse was to provide intelligent information to support reporting and historical trend analysis capability for the sales and marketing departments, such as: Who are the top 10 percent of my customers? What products do they buy? Has the top 10 percent changed over the last year? Who should we direct a product marketing campaign toward? Who is most likely to buy a particular type of product?

With these new questions being asked, the content of the data warehouse became more collaborative in nature; that is, more than just the sales department contributed to, analyzed results of and made decisions based on the data warehouse. Data warehousing efforts began to become multidepartmental as companies began to build customer profiles in the data warehouse. The warehouse began to turn data into integrated information that could be used not only to understand the results of customer behavior, but also to attempt to influence it. Organizations began to demand marketing campaign management applications to both use information from the data warehouse and provide information to the data warehouse in the form of campaign tracking results. The collaborative data warehouse began to impact how marketing investments were made with the objective of improving return on investment for the company's sales and marketing dollar.

Enterprise-Wide BI (Integrated Intelligent Information)

Once the data warehouse becomes a collaborative effort between two or more departments, it does not take long to recognize and exploit enterprise-wide benefits. The sales and marketing department information, for instance, becomes extremely valuable to the customer service department when interacting ­ perhaps the most important touchpoint of the customer relationship management cycle. Customer value and vulnerability models take on greater importance to a company as it begins to understand and, more importantly, predict loyalty of the customer and vulnerability to competition. A company's investments can be directed toward more effective ways to retain valuable customers. The enterprise can focus its efforts on the value proposition for individual customers, discerning customer preferences and providing individualized communications, product marketing, sales experiences and service activities.

The data warehouse is supplemented with third-party demographics as companies begin to extend their customer profile information assets. Information in the data warehouse can be used to discover cross-selling and up-selling opportunities. Information in the data warehouse begins to be used to discover other potential, previously untapped markets. Discovery, definition and refinement of the profiles of customers predisposed to the company's products become a competitive lever of the data warehouse. The ability to define and exploit customer-driven segmentation strategies provides new justification for the data warehouse. The enterprise begins to use the data warehouse to answer: How does this customer want to do business? How can I recognize the value of this customer when I have them on the telephone or in a meeting? Given their previous buying patterns, what other products might interest this customer? Where can I find prospects that fit the same profile as my top customers?

Several important characteristics of the early data warehouse implementation begin to evolve. The data warehouse with an enterprise focus begins to become much more mission critical. Where early data warehouse implementations delivered weekly, monthly and quarterly updates and longer-term strategic decisions, the warehouse with enterprise characteristics demands information be updated with transaction results much more frequently, often daily, in order to provide the most complete information possible. Strategic decision making becomes shorter term as companies may redirect themselves to exploit competitive differentiators several times a year, rather than once every two to three years. Static reporting gives way to multidimensional analytics and data mining activities. Companies recognize the data warehouse as an enabler of their business strategies, and decisions made based on information in the warehouse affect the entire enterprise at its bottom line ­ improving revenue.

Value Chain BI (Individualized Integrated Intelligent Information)

As businesses become more global in nature with mergers, acquisitions and partnerships, the data warehouse and business intelligence it provides take another step forward in the value-added proposition. Emphasis on how to better service existing customers and extend the customer base involves a company's suppliers, distributors, and new sales and marketing channels. The customer profile is extended with psychographic, behavioral and competitive ownership information as companies attempt to go beyond understanding a customer's preferences. The data warehouse is extended with information such as how a customer is likely to feel about a product or purchase, what competitors' products a customer might own and when the customer is likely to make the next purchasing decision. The warehouse has evolved from data through information to intelligence as agents are used to evaluate and act upon information the moment anything changes. The data warehouse is used to automate actions based on business intelligence. Examples include: extend an offer for insurance when a new automobile is purchased, determine with which supplier the order should be placed in order to achieve delivery as promised to the customer ­ and place the order, or send an e-mail product offering to key prospects when the competitor's product they own is nearing the end of its warranty.

Demand for access to the data warehouse evolves to include entities external to the company. Companies may help their customers make new purchasing decisions by displaying previous purchases and marketing complementary products. Companies may determine that suppliers need access to aggregate demand levels for certain products or product companies in order to assist them in making effective manufacturing planning decisions. New distributors can benefit from intelligence in the data warehouse about product sales trends or marketing campaigns. As access to external parties increases, the warehouse evolves yet again to increase a company's competitive position by sharing business intelligence across the value chain.

What's Next?

The data warehousing/business intelligence environment has evolved in business context from single-department content through multidepartmental collaboration, the enterprise view and finally the business value chain. As data has progressed to intelligence, uses of the data warehouse have gone from reporting, parameterized queries and all flavors of OLAP tools to analytic applications and intelligent agents. The data warehouse has moved from reactive to proactive and has taken its place as a mission-critical asset to the business. Where will this trend lead? Before we attempt to answer this question, it's important to analyze a similar trend in an important technological enabler ­ e-business.

The E-Business Trend

Using the Internet as a technological enabler over the past two to six years has resulted in the electronic business trend demonstrating a striking similarity to the data warehouse/business intelligence trend. As the use of the Internet has evolved, the pattern of this evolution is parallel to the evolution in data warehousing. The same change in context ­ from focus on brochureware to focus on integrated value chain ­ is taking place.

Over time, the value of e-business applications has increased significantly. It has moved from static Web pages to dynamic commerce, from highly structured content to unstructured information. In order to understand the e-business trend, we'll examine the curve of value over time for e-business as we did for business intelligence.

As depicted in the e-solutions value curve (Figure 2), the context of e-business has changed with time, moving from a focus on content to a focus on the business value chain. This evolution is again best understood by example.

Figure 2: The E- Solutions Value Curve

Brochureware (Information)

Early adopters of e-business saw the Internet as an enabler of information distribution. These early implementations were static Web sites, typically deployed on a company's intranet, for internal broadcast of important information. From an external perspective, company Web sites (commonly called "brochureware") have been used as a way for customers and business partners to understand an organization's line of business, its history, mission and values. Other examples of these first business uses were online product catalogs, including description and product ID; dissemination of company goals, objectives and policy; and dissemination of corporate phone directories and office locations.

By virtue of the fact that such Web pages were static, content was highly structured and only provided a one-way flow of information. The benefits from undertaking such initiatives included providing widespread access to information, reducing the cost and time associated with delivering paper documents and information, and understanding the potential of this emerging technology.

Collaboration/Communication (Intuitive Information)

Not long after the first internal deployments of Internet Web pages, Web sites became much more intuitive in nature. A true collaboration platform was established, moving beyond the one directional information flow of the initial Web sites. They began to support e-mail capabilities, questions and answers regarding corporate information and forms- based data entry. Navigation became more sophisticated with links to supporting data and more explanation; but, more importantly, they were easy to use. Examples included e-mail capabilities, frequently asked questions (FAQs), requests for additional information and customer profile input.

Many organizations have found that customer service applications are a valuable way to leverage the power of the Web. Through the development of intuitive business- based applications, both customers and businesses have come to see the value of intuitive customer self-service initiatives.

Electronic Commerce (Integrated Intuitive Information)

The evolving maturity of Web tools and techniques has transformed relatively primitive Web sites into the world of e-commerce, focused on developing this new sales channel. By providing an opportunity for continuous interaction between the customer and the enterprise, organizations have discovered a new approach to cultivating and extending relationships with their customers. Business justification for e- commerce rapidly evolved from "Why should we do this?" to "Why we must do this!" The Internet has presented businesses with a new way to reach customers that is no longer dependent upon the physical presence of the traditional brick- and-mortar place of business. In cyberspace, the customer can browse through products, fill a shopping cart, make their purchases and schedule delivery from any place in the world, any time the desire to purchase arises. The primary examples of this enterprise e-business view are online procurement, business-to- consumer commerce and business-to- business commerce.

These applications provide the ability for companies to streamline core business processes within their own organizations, as well as dramatically reduce the costs and inefficiencies within their value chain. The integration and Web-enablement of these core systems has helped companies leverage their investments and evolve into e-businesses.

Integrated Value Chain (Individualized Integrated Intuitive Information)

The focus of e- business today, for the most forward- thinking organizations, is in leveraging Web technology throughout the entire value chain. E-business has evolved from static content and information distribution to dynamic content, displayed to a wide number of customers, suppliers, distributors and even competitors. These environments allow distributors to take advantage of lower pricing and inventory availability, while suppliers provide order fulfillment, shipping and routing information, and take advantage of online invoicing and faster electronic payment cycles. It also provides consumers with unprecedented choice and selection, competitive price searches and a global view of similar, competitive product solutions. Businesses are challenged to develop new ways to respond to the new types of market demand ­ online orders that provide immediate payment but also bring expectations that the product will be delivered almost immediately. Examples include B2B exchanges, supply chain automation, e- commerce and legacy application integration.

In addition to the freedom gained through leveraging the Web as a commerce medium, personalization has become an increasingly important component of these applications. Personalization means providing tailored offerings and information directly to individuals. This component of e-business provides organizations the opportunity to exercise and strengthen their key relationships with suppliers, distributors, business partners and ultimately customers.

The Convergence

Thus far, we've examined the trends in business intelligence/data warehousing and e-business as separate entities. The reality is that these trends have been on a path of convergence for quite some time. Many businesses have come to realize that their business intelligence initiatives can become more valuable and provide a "bigger bang for the buck" by using e-business technology to multiply their beneficial effects. Similarly, many organizations deploying e-business solutions have come to the realization that as the e- business trend evolves, effective use of their business intelligence environments allows them to realize maximum benefit from e- business strategies. Let's take a closer look at the convergence of these two trends.

In the content phase, convergence of the business intelligence and e-business trends is simply the widespread distribution of information. As the data warehouse produces reports, these reporting results are distributed via Web-based technology. The benefit to the data warehouse is that information that is frequently requested is made available to a larger number of end users with browser capability on the desktop. The company investing in fledgling e- business capabilities (static Web pages) provides a benefit to end users by publishing Web pages that reflect updated information from the data warehouse.

The collaboration phase of convergence is best described by the publish-and-subscribe model often associated with business intelligence initiatives. In this model, information in the data warehouse can be subscribed to electronically and delivered via e-mail or an intranet. The data warehouse becomes more proactive, and e-business becomes the enabler of the customized information subscription and delivery service. The resulting convergence provides information tailored to the individualized needs of the end users.

Convergence at the enterprise level provides synergy by combining enterprise intelligence with e-commerce, as in the example of targeted e-marketing. In this example, the business uses information about its customers, coupled with its e-commerce capabilities, to electronically market and sell its products. Offering cross-sell and up-sell opportunities to its customers in electronic fashion on a Web site are also examples of convergence of the business intelligence and e-business trends at the enterprise level. At this point, convergence provides intelligent information for the enterprise.

Finally, convergence at the business value chain level provides customized, information portal technology to deliver information from a number of sources, including the data warehouse, to a company's customers, suppliers, distributors and other entities. These information portal views are tailored to the individual requirements of the end user and the business transaction being facilitated. The company is succeeding in delivering individualized, integrated intelligence information to consumers throughout the business value chain.

This convergence is creating a new marketplace ­ the i-market. The focus is not only transacting, but also leveraging the information assets across the organization. The i-market is Web-enabled enterprise applications for transacting and Web-enabled enterprise business intelligence applications for reporting, analytics and decision support. This new i-market represents a tremendous amount of opportunity and offers limitless ways to market, sell, transact and operate companies.

Figure 3: The i- Market

The i-Market Evolution

We've made many observations about both data warehousing and e-business. As steps have been taken from content through collaboration, the enterprise view and the business value chain, the characteristics of both the data warehouse and e-business have changed from reactive to interactive to proactive, from structured data to unstructured business information and from broad audiences to customized, targeted views. The ultimate convergence of these paths is the formation of the i-market.

Organizations seeking to exploit this emerging mountain of opportunity must adopt a new business model that is based on the following five key elements:

  1. Provide customized, personalized information to each individual consumer. This is accomplished with Web-based portals to present information that is unique to each end-user's needs and interaction style.
  2. Leverage individualized views to provide a meaningful information exchange. This collaboration occurs in an easy-to-use context that is intuitively perceived and instantly acted upon by the user.
  3. Use active agents and triggers to provide automated responses to business information stimuli. Likewise, improve responsiveness to business events and market demands through intelligent analysis and correlation of information.
  4. Use stored and integrated information assets, including data warehouses and marts, to full advantage. This information, combined with external information sources, provides the big picture to business constituencies. Again, the power of the Web is the best technology enabler for efficient distribution of and access to integrated information.
  5. Exploit information. Gain power and market dominance by using complete and timely information to drive all business decisions and processes. Thus, information is the glue that binds business intelligence and e-business, allowing organizations to complete their transformation so there are no gaps in knowledge.

i-Market Preparedness

Business opportunities of seismic proportion are forming in the world of information technology. Enterprises that realize the value of harnessing the power of the emerging i-market ­ the convergence of business intelligence/data warehousing and e-business ­ will be able to reach the summit of market domination and unmatched competitive advantage long before their competitors.

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