With complex statistical models, it can take weeks to produce usable results. Prebuilt, specialized analytic apps promise forward-looking insight that people can act on now.
It's official. The term "analytics" no longer refers only to advanced statistical methods and operational research. It's now shorthand for what people really want from business intelligence: concise, actionable insight that lets them respond to what's happening now and anticipate what will happen in the future rather than just react to the events of last week or last month.
Enter prebuilt analytic applications. As the name suggests, these are off-the-shelf apps, ready-made for specific industries such as banking, insurance, and retail, as well as for disciplines such as finance, marketing, purchasing, and human resources.
A banking analytic app, for instance, might provide predefined (though still customizable) reports, dashboards, and metrics on various types of risk, including credit, operational, or market risks, or on customer satisfaction, loyalty, and share of wallet. A cross-industry sales app would spotlight pipeline, cross-sell, and up-sell opportunities, as well as products and customer segments that generate the most revenue.
Siebel (owned by Oracle) and SAS were among the earliest developers of these applications, which have mushroomed in recent years along with customer interest. Most of the leading enterprise app vendors--Oracle, SAP, Infor, Lawson, and others--and many leading BI and analytic software vendors--IBM, Oracle, SAP, and SAS--are launching products and portfolios.
We're not talking about transactional applications such as ERP, CRM, and supply chain management. Those apps--whether on-premises or on-demand--invariably have built-in analytic features.
Analytic apps are entirely about insight and decision support. They generally include data links to enterprise apps and line-of-business systems, as well as predefined data models, dashboards, metrics, and reports that make them faster and easier to deploy than apps built from scratch. Vendors create them with input from industry experts, drawing on best practices and industry benchmarks. That's reassuring to customers, who otherwise would face the long, risk-fraught process of gathering requirements, building consensus on functionality, developing custom apps using a general-purpose BI/analytic suite, and then hoping--more likely praying--for user acceptance and adoption. (For more on BI development, see 5 Factors In Agile BI.)
Companies considering prebuilt analytic apps should ask these questions: Will the app fit the company's specific needs? Can it be customized or adapted for a better fit? Some products pitched as applications aren't really apps at all because they're not supported and maintained by the vendor. You'll definitely want to know whether the vendor is on the hook if the product doesn't work. And is there a road map for upgrades?
Finally, does choosing a prebuilt app mean sacrificing differentiation for the sake of fast, easy deployment? The answer depends on how tied the apps are to a company's core strategy, but it's highly unlikely they'll make or break your company. Analytic apps are a shortcut to insight, but as with BI, having data at your fingertips doesn't guarantee success. On that score, make sure your company is ready for the shrewd and swift fact-based decision making required to take advantage of analytic apps.
InformationWeek Tech Digest, Nov. 10, 2014Just 30% of respondents to our new survey say their companies are very or extremely effective at identifying critical data and analyzing it to make decisions, down from 42% in 2013. What gives?