Real-time Analytics Best Practices

Transcription

1 Best Practices

2 Many organizations are looking to make their business systems smarter through the addition of integrated analytics capabilities. One of the driving forces is a desire to improve decision making by undoing the usual decoupling of business intelligence and analytics systems from business applications. In this E-Guide, readers can learn tips on gaining a competitive advantage by driving operational decision making in real or near real time. In an interview published on TechTarget's ebizq website in 2011, Gartner analyst Roy Schulte discussed efforts by a growing number of the consulting company's clients to make their business systems "smarter" through the addition of integrated analytics capabilities. One of the driving forces Schulte cited was a desire to improve decision making -- on the fly -- by undoing the usual decoupling of business intelligence and advanced analytics systems from business applications. "There's a gap between what the business intelligence department knows and what the people running the business know," he said in the interview. Schulte still sees lots of value in closing that gap: Interviewed again for a recent series of stories on real-time data analytics, he told SearchBusinessAnalytics.com contributor Beth Stackpole that every company has operational processes requiring immediate decisions, and that having access to real-time business intelligence (BI) and analytics data can help business users make more effective decisions in such situations. Real-time -- or, more commonly, near-real-time -- analytics is particularly popular with Wall Street trading firms and managers of corporate call centers. But it also has uses in transportation, health care and other industries. If your organization is looking to go down the real-time analysis road, you'll find practical advice on evaluating, planning and managing Page 2 of 6

3 deployments in our series. In one story, we examine the business case for real-time analytics. We also look at the benefits and challenges of combining big data and real-time BI systems. And we detail real-time data analysis best practices -- as well as some steps that are best to avoid in real-time rollouts. By Beth Stackpole Looking to generate immediate improvements in business performance and gain a competitive edge on rivals, companies increasingly are trying to take advantage of business intelligence and analytics tools not just to garner strategic insights, but also to drive operational decision making in real or near real time. -- or operational intelligence, as many prefer to call it -- has been heralded as the next logical progression for BI deployments. Nevertheless, consultants say real-time tools are still in the early stages of technology maturity and that implementations are far more prevalent in larger companies with sizeable IT budgets and deep benches of BI and analytics professionals. "Simple kinds of real-time or near-real-time analytics are within the budget of virtually every company," said Roy Schulte, an analyst at Gartner Inc. in Stamford, Conn. As an example, he cited a business dashboard that gets refreshed every five minutes to monitor the volume of incoming customer calls received at a corporate contact center. But, Schulte added, more powerful real-time analysis systems "can require hundreds of thousands of dollars in software license fees and several times that in staff costs to develop and deploy." Schulte said real-time BI technology gives business users or automated systems immediate access to operational data. The goal is to enable analytics applications to be applied to business processes that have limited time windows or require rapid reactions to events and changing conditions. Page 3 of 6

4 Sales offers on the spot with real-time tools In that scenario, a real-time BI system might help a customer service representative make a cross-selling or up-selling offer to a customer based on his recent activity on the company's website or something said during the phone call. "Any large company has a number of applications in which their business processes would be smarter and more effective if they were using real-time analytics," Schulte contended. In fact, with the cost of processing power coming down and more tools becoming available, it's going to become easier to make a business case for real-time analytics beyond the traditional use cases in call centers and financial and trading applications, said John Myers, senior BI and data warehousing analyst at Enterprise Management Associates Inc., a research and consulting company in Boulder, Colo. "With the barrier to entry lowering, it starts to open up a whole new realm of things people can do," he said. For example, a retailer could push real-time data analytics to the cash register level, according to Myers. In such an application, the analytics system could serve up a simple alert that would direct the cashier to make specific offers to customers based on what they were buying as well as their previous purchases and risk scores assessing their payment and credit histories. Being able to make BI-driven decisions as events unfold can be especially important when customer satisfaction is at stake. "Companies used to be able to look at [key performance indicators] every three months to see how they were doing," said John Crupi, chief technology officer at JackBe Corp., a vendor of real-time analytics software in Chevy Chase, Md. "Now, if there's a problem impacting customers and you don't find out about it for a few weeks, you won't have your customers for too long." Real-time not always the right BI fit Even with all its potential, real-time business intelligence and analytics is certainly not a match for every company or every BI business case. Organizations need to think through whether providing end users access to Page 4 of 6

5 the most current data will actually change business outcomes and results -- or just flood them with more data to no great effect. "Not every instance requires real-time data," said Lyndsay Wise, president and founder of WiseAnalytics, a Toronto-based consultancy that focuses on BI and data visualization deployments in midmarket companies. "It depends not on how quickly you need the data, but what are you going to do with the data and where are the action points." An online retailer might benefit from using real-time analytics to help it better service customers or manage product inventories more effectively, Wise said. But giving business executives updated views of sales data in real or near real time isn't so useful if that information doesn't precipitate any immediate actions on their part. To properly assess the need for real-time capabilities, she added, organizations need to look closely "at the cause and effect" of proposed deployments. Page 5 of 6

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