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Video Q&A | Predictive Analytics Tutorial
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Video Tutor Jeff Jonas
Jeff Jonas is Chief Scientist, IBM Entity Analytics Group and an IBM Distinguished Engineer. The IBM Entity Analytics Group was formed based on technologies developed by Systems Research & Development (SRD), founded by Jonas in 1984, and acquired by IBM in January, 2005. Jeff Jonas blogs at: www.jeffjonas.typepad.com.
Questions, and Answers from the Tutor
Question: Human resource organizations often use a screening test that they say accurately predicts how an applicant would do if hired and rules out those who don’t fit a particular pattern. I always find this amazing because they could be passing on employees who may be revolutionaries because of this test.
How do we keep predictive analytics real? Basically, it should be one part of an analysis, not the centerpiece. How do we keep this as a tool but not as a crutch for a department or employee who doesn’t match insight with the tool, which potentially could lead to a series of false positives?
Answer: This worries me, too. If organizations stop hiring with some diversity, where is the creativity going to come from? One solution is to always introduce some randomness. Having built a slew of HR-related systems for Las Vegas over the years, including scoring systems used in the initial screening process, one of the things they developed was a process to hire ex-felons! That was innovative!
You've got to match forecast to actual in my opinion. Otherwise, you start drinking your own Kool-Aid!
Question: I'm a small business owner with a company specializing in video production, editing, motion/still graphics, logos, and branding. We're a "two-man band" with a Rolodex of associates we contract on a project basis as needed. I'm curious how I can apply predictive analytics to my goals of:
Retaining current clients
Gaining new clients
Increasing my profit each quarter
Answer: Predictive analytics for small companies is a bit tricky to do in-house. I think what we will see is more and more services you (as a small business owner) can latch onto -- without having to make a capital commitment yourself. One example might be uberVU; another one coming up quick to handle geospatial analytics is SimpleGeo.
And while these are more analytical than predictive, I'd say predictive analytics "as a service" will come, and as such, will help startups, small companies, and probably even big companies, too.
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Further Educational Materials
Q1: What exactly is predictive analytics?
Q2: What types of data are used in predictive analysis?
Q3: Why do businesses use predictive analytics?
Q4: Which industry sectors will benefit most from predictive analytics?
Q5: Do predictive analytics tend to be more IT- or department/division-driven?
Q6: Do you see companies moving in this direction? Thinking about their data in this cross-departmental way?
Q7: What are the most common challenges associated with predictive analysis projects?
Q8: Where should an enterprise that’s new to predictive analytics begin the deployment process?
Q9: Do users of predictive analytics need to change how they create, manage, or store data?
Q10: What does the future of analytics look like?
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