The 9 Fatal Flaws of Business Intelligence
By focusing too much on systems and software, and not enough on how to accurately interpret information, a large percentage of business intelligence (BI) implementations suffer from one or more of nine "fatal flaws," according to Bill Hostmann, Gartner research vice president and distinguished analyst.
"The main reason [for the flaws] is that companies tend to view business intelligence as a bunch of technology; but you have to have insight into what that technology is supposed to provide," Hostmann says. "You have to have people trained [to] ask the right kinds of questions and who have the skills to use that [BI-generated] information intelligently."
For example, a BI application might provide plenty of customer information that a firm can use for CRM purposes, but realizing truly value requires the ability to filter the information to identify patterns, trends, and indications. If sales increase, is it due to your loyalty program, new products, a shuffled product mix, word-of-mouth marketing, or some other factor?
It's also important that the company have enough data points to offer statistically significant information, Hostmann adds. Some companies base their CRM strategies on too little information. If the results seem far out of what's expected, Hostmann recommends conducting additional queries or supplementing the existing data in some other way.
But, just as important, firms can collect so much information that they don't have the ability to analyze it all, Hostmann says.
If firms can keep the above factors in mind, they should be able to avoid Hostmann's "nine fatal flaws:"
- Believing that if you build it, they will come. When firms develop their BI initiatives from a data-centric perspective, the value isn't obvious to the business, so there is low adoption across the enterprise. This can be avoided if there is involvement from the business side from the beginning.
- Managers dancing with the numbers. Many companies are locked into an "Excel culture" in which users extract data from internal systems, load it to spreadsheets such as Microsoft Excel, and perform their own calculations without sharing those results across the enterprise. Marketing, sales, and other departments need access to this information for comprehensive CRM.
- Data-quality problem? What data-quality problem? Data quality issues are almost ubiquitous and the impact on BI is significant -- people won't use BI applications that are founded on irrelevant, incomplete, or questionable data.
- Evaluate other BI platforms? Why bother? One-stop shopping, or buying a BI platform from the standard enterprise-software vendor doesn't necessarily lower the total cost of ownership or deliver the best fit for an organization's needs.
- It's perfect as it is. Don't ever change. Many firms treat BI as a series of discrete projects, focused on delivering a fixed set of requirements. However, BI is a moving target: Requested changes in the first year of deployment can affect 35 percent to 50 percent of the application's functions.
- BI? Bye-bye—let's just outsource the whole darn thing. Some companies expect to cut costs via outsourcing. But focusing too much on costs and development time often results in inflexible, poorly built systems.
- Just give me a dashboard. Now! Many companies press their technology staff to buy or build dashboards quickly and with a tiny budget. But dashboards delivered under those circumstances are of very little value because they are silo-specific and not founded on a connection to corporate objectives, such as improving customer retention.
- X + Y = Z, doesn't it? A BI initiative aims to create a "single version of the truth," but many organizations haven't even agreed on the definition of fundamentals, such as "revenue." Achieving one version of the truth requires cross-departmental agreement on how business entities (customers, products, key performance indicators, metrics, and so on) are defined.
- BI strategy? No thanks, we'll just follow our noses. The final and biggest flaw is the lack of a documented BI strategy, or the use of a poorly developed or implemented one. Hostmann recommends creating a team tasked with writing or revising a BI strategy document, with members drawn from both the technology and the business sides.
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