Research paper

4 BUSINESS INTELLIGENCE Journal • vol. 12, no. 3

Enterprise Agility and Mature BI Capabilities Hugh J. Watson and Barbara H. Wixom

Much is being written about enterprise agility, and it is easy to see why there is interest. The current business environment is turbulent because of heated competition, economic shifts, demands from customers, regulatory changes, mergers and acquisitions, and technological advancements. An agile organization can adapt to and perform well in changing environments. Companies that can’t adapt aren’t likely to survive for long.

Enterprise agility has two components. The first is being able to sense changes in the environment. The second is being able to respond to these changes. For example, an agile organization is able to quickly detect when a competitor’s new product is gaining market share and to respond by introducing a competing product. An agile organization senses the effects of a downturn in the economy and responds by adjusting its budgets.

Every department in the enterprise needs to be agile. The research and development department needs to be vigi- lant about new technological developments. Production needs to be able to easily switch schedules in response to new business opportunities. Human resources needs to be able to adapt to new hiring requirements.

BI and data warehousing have critical roles in ensuring the agility of the entire organization. BI can be used to sense when changes are occurring, such as changes in the demand for products or difficulties in the supply chain. BI can also help the enterprise respond to changing environments by meeting reporting requirements on new government regulations or alerting the sales force about products that are temporarily out of stock.

M AT uRE BI

Dr. Hugh J. Watson holds a C. Herman and Mary virginia Terry Chair of Business administration in the

Terry College of Business at the university of Georgia.

He is a Fellow of TDWI and the senior editor of the

Business Intelligence Journal.

[email protected]

Barbara H. Wixom is an associate professor at the McIntire School of Commerce at the university of

virginia. She is a Fellow of TDWI and an associate

editor of the Business Intelligence Journal.

[email protected]

5BUSINESS INTELLIGENCE Journal • vol. 12, no. 3

Mature BI Capabilities Organizations differ in the extent to which their BI capabilities support agility. Firms with nonintegrated data, high data latency, Excel-based analytics, and little appreciation for information-based decision making are unlikely to be agile. Companies that are more mature in their BI capabilities can respond successfully to turbulent environments.

The literature provides several models that describe BI and data warehousing maturity. Wayne Eckerson (2004) suggests a six-stage model that includes prenatal, infant, child, teenager, adult, and sage stages. Watson, Ari- yachanandra, and Matyska (2001) present a three-stage model: initiation, growth, and maturity. Based on these and other models, the following characteristics are associ- ated with high levels of BI maturity:

n Senior management perceives and treats BI as a strategic resource. Senior management believes that BI is important to organizational success and funds it accordingly.

n There is alignment between the business and BI. BI is an important enabler of the business strategy. Senior management has a vision that it communicates about how BI can support the business.

n BI delivers high business value. The returns on the investment in BI are much greater than the costs.

n A culture of information-based decision making exists. Decisions are driven by the numbers. This approach is in contrast to intuitive decision making or decision making based on gut feelings.

n BI governance is effective. There are people, com- mittees, and processes in place to ensure that all aspects of BI, ranging from strategic alignment with the business strategy to the establishment of common data definitions, are handled effectively.

n The enterprisewide data infrastructure is effective. The enterprise data warehouse contains most of the data needed to support decision making throughout

the organization. Data structures support ad hoc analyses and the rapid development of new applica- tions. This is in contrast to Excel-based spreadmarts.

n Data quality is high. There is a single version of the truth, and people and processes are in place to ensure and enhance the quality of the data.

n The production and development environment is stable. There are people and processes in place both for operating the existing warehouse and for develop- ing it.

n There is widespread use of BI. BI is pervasive throughout the organization. This does not mean that everyone is performing analyses, but that BI is involved or integrated (perhaps seamlessly) into most people’s jobs.

n The BI staff and users work together closely. The BI staff works hand-in-hand with users and under- stands their information needs. Users are able to access and use the BI and data resources that are available. There may be BI centers of excellence.

n People, tools, data, and methodologies are available to support rapid application develop- ment. This includes SWAT teams and tools, rapid prototyping tools, agile development methodologies, configurable packaged applications, and flexible, intui- tive query and reporting tools.

n A strong portfolio of business-driven BI applica- tions exists. Rather than simply reporting or trying to understand what has already occurred, data is

M AT uRE BI

Companies that are more

mature in their BI capabilities

can respond successfully to

turbulent environments.

6 BUSINESS INTELLIGENCE Journal • vol. 12, no. 3

work to get the plane off the ground or back to a gate, avoiding unpleasant customer experiences.

The airline industry as a whole is in cost-cutting mode. In fact, some airlines are beginning to eliminate customer care service over the telephone. Instead, customers must complain using letters or e-mail, which are less expensive channels. Continental is trying a different approach. The company is creating a process that reduces the overhead associated with the telephone channel.

When a customer calls a reservation agent and files a com- plaint, the agent now has access to that customer’s history via the data warehouse. The agent enters data into a rules engine that analyzes the customer complaint within the context of the actual event details and the customer’s value to Continental, and then receives a proposed resolu- tion. The agent can satisfy the customer in real time and record the resolution before the call ends. The company has been able to improve overall customer service yet still reduce costs—the businessperson’s ideal situation. n

Conclusion You are likely to hear your company’s senior manage- ment talk about the need to be more agile. Much of the opportunity and responsibility for being agile is in your domain. Where possible, seize this opportunity and push your company’s BI and data warehousing capabilities to a higher maturity level.

References Eckerson, Wayne W. [2004]. “Gauge Your Data Ware-

house Maturity,” DM Review, November, pp. 34–37, 51. Also available at http://www.tdwi.org/publications/ display.aspx?ID=7199

Watson, Hugh J., Thilini Ariyachandra, and Robert J. Matyska, Jr. [2001]. “Data Warehousing Stages of Growth,” Information Systems Management, Summer. www.ism-journal.com/ITToday/datawarehouse.pdf

analyzed to predict what will happen in the future. Real-time data and analytics are used to influence cur- rent decision making and operations, often through rules and event-driven triggers and alerts. Business performance management systems are in place.

What’s Possible with Mature BI Harrah’s Entertainment and Continental Airlines have mature data warehouses that have helped support company agility. Consider the following examples, which illustrate how these organizations have been able to sense or respond to changes in the environment.

Right after the terrorist attacks of September 11, 2001, Harrah’s and other Las Vegas hotels and casinos did not need BI to recognize that business had dropped precipi- tously. Most customers were unwilling to board planes to fly to these destination resorts. Business had to be generated from customers within driving distance, such as from San Francisco or Los Angeles.

Fortunately, Harrah’s had a mature customer-centric data warehouse and had analyzed the data to understand what offers (e.g., complimentary rooms, show tickets) have the greatest appeal to market segments. Using this informa- tion, Harrah’s targeted customers within driving distance with offers that had to be used quickly. The company’s investment in BI was rewarded. Whereas other hotels and casinos suffered significant revenue declines post– September 11, Harrah’s actually had revenue growth.

Within the past year, Jet Blue and American Airlines both received negative press for stranding customers in planes on the ground for long periods of time. Continental Airlines wanted to develop a process that would proactively prevent similar kinds of situations from happening on their flights.

Continental’s Flight Operations department was using the data warehouse to feed a real-time application that provided up-to-the-minute airline performance statistics. Flight Operations was able to add an alert that identified any airplanes that had been sitting on the ground away from a gate for at least two hours. Now these flights appear on the screen immediately so that technicians can

M AT uRE BI

Where does your BI program fall on Wayne Eckerson’s Maturity Model? receive a personalized BI maturity score using TDWI’s free BI Maturity assessment Tool available at www.tdwi.org/benchmark.