Business Intelligence in Competitive Strategy
Lost Boy: "Injuns! Let’s go get em!"
John Darling: "Hold on a minute. First we must have a strategy."
Lost Boy: "Uhh? What’s a strategy?"
John Darling: "It’s er It’s a plan of attack."
Walt Disney’s Peter Pan
It is clear that the fundamental goal of the firm is to earn a return on investment on its capital that exceeds the cost of its capital. There are two basic ways a firm can accomplish this core goal:
- Exist in an industry where the economic conditions are favorable, where the rate of return is above the competitive level.
- Defeat the competition and earn a return greater than the industry average.
These two points define corporate strategy vs. business strategy. Corporate strategy decisions include mergers and acquisitions, new ventures, allocation of corporate resources, etc. Business strategy is concerned with how the firm competes within a particular industry. In other words, it is what defines the competitive advantage a firm must attain in order to win or to survive in an industry. Therefore, business strategy is also referred to as competitive strategy. The definition of corporate and business strategy is not a separation but rather a hierarchy. If a firm is successful in executing its business strategy, it will be successful in the overall corporate strategy. In this hierarchy, the next level is functional strategy, which identifies functional decisions for R&D, personnel, finance, production, and sales and marketing. As the firm gets larger, the distinction between functional and business strategy grows. For small, entrepreneurial businesses, the two are virtually the same.
Figure 1: Strategy Overview
Know the other and know yourself:
Triumph without peril.
Know Nature and know the Situation:
There are two factors that impact the success of any organization: internal environment (resources, processes, capabilities) and external environment. Understanding these factors is key at any point in the strategy hierarchy. It is important to know the capital spending in R&D, development life cycles of the products, production efficiencies, turnover rates in the organization and effectiveness of the sales and marketing force. Several key performance factors can be identified to monitor what’s taking place internally. The majority of the business intelligence solutions today are built around understanding the internal environment. It is clear that this is only half of the equation since in order to achieve strategic advantage, a firm must understand both the internal and the external environment.
Figure 2: Business Intelligence Overview
Information need grows as we move toward the top of the strategy hierarchy in a firm. Traditionally, data warehousing solutions are built to answer business decisions with the maximum impact on the functional strategy. That’s because there’s limited emphasis on external data at this time. For instance, an HR data mart tries to calculate metrics and key performance indicators regarding the HR processes. It should also capture or acquire industry information such as unemployment rates, average compensation, average turnover, etc. In other words, information need is exponential rather than cumulative. The sum of all the data collected at the functional level is less than all the data needed at the business level because at the business level, there is a need for external data. Same principal applies to the corporate level. At the functional level, the decision support is focused on the internal environment. The managers are expected to understand their business units and are evaluated based on this criterion. Senior managers, however, are expected to understand both the internal and external environments. Often times the directors and the executive team focus mostly on the external environment without losing grip on the firm’s internal processes. Since the information need is exponential, the business intelligence system must be created with a strategic focus that captures the data needed for corporate, business (competitive) and functional strategy.
If understanding internal and external environments is what’s crucial to a firm’s ability to execute its strategy, then the business intelligence solutions must capture internal and external data. In functional data marts, internal data is being collected every day. The combination of the functional data marts, which follow the rules of conformity, results in the enterprise data warehouse. What’s missing is the collection of external data at a central location, which can be visualized along with the functional data. The external data can be grouped in two categories: industry data and competition data. For government organizations, or for organizations where government policy is significant, a third group may be added or the government policy data can be grouped in the industry category since only the data that’s relevant to the industry would be collected.
The simplest form of industry data that is relevant to any business is industry averages. This piece of information is easy to find and can easily be incorporated in the corporate data warehouse. Organizations constantly monitor their progress against their budgets and previous years’ performances. With the introduction of industry averages in the scope of analysis, organizations get a better picture of where they are in terms of strategy and how effective their execution is with respect to their corporate and competitive strategies.
Data about the competition is more difficult to gather. Most of the data is simply not publicly available. Nevertheless, a careful examination of the competition yields data. For instance, organizations that offer their products and services on the web immediately make their pricing information available to everyone. That is a crucial piece of information when making pricing decisions. The challenge here is that the data about the competition is not collected as directly as the industry and internal data. Still, when collected, this data should be part of the corporate data warehouse.
From a technology perspective, there are several components of a business intelligence solution in a firm. Data marts, ETL processes, OLAP processes, expert systems, artificial intelligence and fuzzy logic are all parts of the business intelligence solution. Therefore, all these components must work well together. Since data is at the core of all these components, it becomes very confusing when different software solutions tell different stories about the same business. Although the vendors might be different, and they most likely will be, the source of the data, which the tools use for analysis and reporting, must be the same. Data must be central to all of these applications. Since the scope of analysis is not constant, one should be able to maneuver from one data or summary point to another in an effort to find the answers to the business decisions.
In summary, business intelligence is a broader concept than data warehousing since it is an essential component of the overall strategy of the firm. Implementing data marts and data warehouses increases the decision-making capabilities. But in order to achieve the objectives set forth within the scope of the corporate, business and functional strategy, data must be gathered from internal and external sources and a comprehensive business intelligence system must be in place. With that, business intelligence becomes an essential part of any organization from a strategic standpoint.