It’s not hard for Andy Jennings to predict what’s coming in 2014 for analytics software company FICO Corp.
The San Jose, Calif., based company has already announced that its Decision Management Platform will be released early in the year. A suite of decision management authoring tools, it will include a rules-based engine, an analytic modeler for building predictive models and machine learning techniques and application development tools.
It will be available in the cloud as a SaaS service from FICO or an on-premise application.
But in an interview Jennings, the company’s chief analytics officer, also forecast an interesting trend: The need in organizations for people with domain skills and insight — also known as intuition — will increasingly be important.
That’s an interesting call coming from a vendor which says it makes predictive analytics products to help make the jobs of lines of business staff easier.
The company makes the FICO [NYSE: FICO] score used by credit bureaus to determine the risk of credit/debit card holders; the Falcon fraud detection software, the Triad account management software and Blaze Advisor rules engine.
In one way or another all take advantage of big data. But Jennings said, some people wrongly believe the more data an organization collects for analysis the better.
“That’s 100 per cent wrong,” he said.
“When you’ve got lots of data its easier to drown in more reports,” he said. “Unless you have domain expertise and intuition, it’s difficult to understand what to believe and how to interpret results” of number crunching.
“The era of the domain expert has by no means gone away.”
Technology solutions can make domain experts more efficient and effective by gathering data quickly, Jennings said. “But it’s still going to come down to someone interpreting those reports and putting them into context.”
That’s why, he added, the need for good data analysts who understand the business domain that needs the decision will continue. However, he noted, they are in short supply.
Some software companies pitch analytic solutions as ways of helping relatively non-technical line of business staffers to make decisions. That’s not necessarily a mistake, Jennings said, but he believes they should more technology-savvy.
Other predictions for IT-related staff in analytics made for 2014 include
–the swallowing of small analytics software companies by bigger competitors, who will market a “big data stack” of solutions to make it easier for customers to wade through piles of data’
–a shift of marketing from big data infrastructure solutions to analytic applications that can help organizations get more value from their investments in Hadoop data warehouses and Storm stream processing;
–more emphasis on “prescriptive analytics,” which Jennings said goes further than predictive analytics to help organizations automate decisions like “what offer should I make to get a customer to buy one of our products?”
–companies pushing what he called “systemic experimentation,” which uses analytics to do comparisons of existing data to get more variety in results. That might, for example, help a financial institution decide a person is approved for a loan, but at X per cent interest.