The latest implementation best practices and technologies deliver tools for better business decisions.
by Alan Joch, August 2008
When the management team at Equinix wanted to improve how new customers are cultivated and brought into one of the company’s high-tech data centers, it didn’t print reams of marketing brochures or hire more operations staff. Instead, it put an analytics framework in place to study customer interactions as they progressed from new prospect to paying client and then looked for ways to make each of those touchpoints easier to navigate. Almost two years later, the Foster City, California-based company is reaping the rewards of its business intelligence (BI) investment with continued double-digit annual growth rates and reduced workloads for its IT and business staffs.
But before organizations can bank on return on investment (ROI), they need the right technologies and policies to deliver analytics that directly address business requirements. Savvy organizations also realize that analytics aren’t one-size-fits-all—different tools and strategies are essential for the various roles employees serve throughout a company.
Efficiency has always been an important goal for Equinix, which serves more than 2,000 clients throughout the U.S., Europe, and Asia who use its high-tech facilities to house telecommunications and networking equipment. These 40 multitenant centers fill an important industry niche—they provide the physical infrastructure for telecommunications companies, networking firms, and digital content providers to install their equipment and establish data-exchange links for internet traffic. Over the last few years, Equinix’ unique business model has helped it grow at annual rates of more than 40 percent.
But initially, success created challenges. To maintain its service levels, the company had to make the customer onboarding process more efficient. “We wanted to improve that process in an orderly way and ensure that we could measure our improvements and quality levels throughout the process,” says Todd Elsberg, director of business operations at Equinix.
ROI from the new technology and business practices is now coming from a reduction in the time it takes to get the business staff the information it needs to fuel Equinix’ continued growth. “There’s an ROI from the dissemination of accurate and role-specific information on a global basis,” Elsberg says. “No one has to pick up the phone to learn the status of a purchasing requisition or the latest numbers in the departmental budget. They can log in to the BI system and see the actuals.”
A Push for Analytics
Equinix isn’t alone in trying to power its business with better analytics. “Business managers throughout the world are wondering how they can improve the quality of their decisions, while at the same time IT managers are increasing investments in data warehouses and BI solutions,” says Harry Ghuman, Oracle’s group vice president for the Oracle Insight program and industry strategy.
Spending surveys by a number of market researchers this year place BI expenditures at or near the top of CIO priority lists. The desire to boost decision-making quality isn’t the only business driver. A recent poll by the Opinion Research Corp. found that senior executives are grappling with making sense of all the information they’re collecting in their various production systems. 70 percent of the respondents said decision-making is becoming increasingly complex and challenging.
However, companies that successfully learn to use BI to improve and simplify decision-making efforts often see a big payoff. For example, supply chain and financial analytics yield median ROIs of 277 percent and 139 percent, respectively, according to The Financial Impact of Business Analytics: Distribution of Results by ROI Category, a 2003 review of BI investments by IDC. The report indicates that adding predictive intelligence capabilities can deliver ROIs of 145 percent.
Fortunately, best practices and BI frameworks are emerging to ensure that organizations can see BI results quickly. “Historically, it wasn’t easy to integrate data needed for decision-making from multiple systems. Today, we can easily pull together information from the wide variety of sources necessary to provide what decision-makers need,” Ghuman says.