big-ideas-features
 

Managing in a Global Economy

Continued

Model Behavior

The Oracle Insight program offers one such framework for making more-effective BI possible. The program’s methodology for BI engagements consists of a maturity model for assessing BI capabilities, assessment tools to gauge a company’s existing analytics infrastructure, Oracle’s portfolio of BI-related technologies, and an ROI modeler. “The Oracle Insight team works with customers to transform their companies by identifying new sources of value and then helping them capture that value,” Ghuman says. “We have many different mechanisms for how we can accelerate their decision-making goals.”

At the core of this approach is Oracle’s maturity model (see infographic, “Enterprise Decision Maturity Diagnostic,” below). The model helps an organization evaluate its decision-making potential according to four success factors: intent; governance; employee, partner, and customer adoption of information-driven decision-making; and execution. “Most organizations demonstrate different capability levels across these four factors, so once the current state is known, the organization can use the model to determine what additional capabilities are required to improve its decision-making maturity,” Ghuman explains.

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For example, a company that demonstrates marginal decision-making capabilities in the areas of governance, people, and execution might yield improvements by providing real-time performance data and key performance indicators (KPIs) via interactive dashboards, Ghuman says. Thus, if in the “people” success factor only select senior executives and data-analysis experts currently see BI reports, a rollout of role-based dashboards for all the staff can help them do their jobs more effectively, resulting in gains in customer service and productivity. Ghuman adds that the model is valuable not only for evaluating enterprise BI capabilities but also for improving business decisions for individual departments and business processes.

The Oracle Insight methodology also helps organizations choose the right analytical tools for each of three types of decisions businesses make. Strategic decisions take a big-picture look at questions such as what new markets to enter, what acquisitions will have the biggest payoff, and where best to increase capital investments. Tactical decisions would, for example, look for ways to implement strategies by determining what products to manufacture, where to make them, and how to price them. Operational decisions would involve outlining promotional campaigns, identifying the best customers for up-sell opportunities, or optimizing shipping routes.

A Tactical Approach

Equinix’ Elsberg used the Oracle Insight methods and expertise to focus on tactical decision-making in the early phases of the company’s BI expansion. “Our workflows are heavily customized, so we had to customize the reporting as well. I had an incredible relationship with the Oracle team, where we shared information back and forth to do that tailoring quickly,” Elsberg recalls. “The Oracle team really worked to get our needs addressed.”

One strategy that emerged from this collaboration was the decision to not “boil the ocean” with a reporting strategy that would initially encompass the entire enterprise. “For a company that’s growing as fast as we are, that would have been too much to bite off,” he says. “It would have distracted too many people from further growing the business.”

Instead, the team focused on two areas—the first phase involved customer onboarding and, four months later, the second phase focused on the company’s financial applications. When deciding on what areas to focus on during these two initial phases, Equinix looked for processes where BI could deliver quick returns so managers would clearly understand the platform and have an incentive to get behind the program, Elsberg explains. “In phase one, we wanted to better respond to our customers’ onboarding needs. The business driver for the financial reporting in phase two was the benefit in the overall dissemination of information down to the business units,” he adds.

To improve customer onboarding, Equinix used analytics to determine how long the process was taking and which groups within the company customers were interacting with from start to finish. In short, “How many times were customers bouncing from one department to another?” Elsberg says. “Then we looked at why that happened.” For example, they discovered that some delays had resulted from incomplete information about physical space and network connections available for new customers in Equinix data centers. Better inventory summaries helped Equinix streamline subsequent implementations.

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