Bruno Aziza, former Business Intelligence leader at Microsoft, opened his Predictive Analytics World keynote speech with the classic Saturday Night Live “Bad Idea Jeans” sketch. This feature shows men who, believing they know what they’re talking about, actually share some bad ideas like Mike Meyers stating: “Now that I have kids, I feel a lot better having a gun in the house.” Aziza aimed to show that there were a lot of bad ideas circulating around predictive analytics that did not translate into added value for users and clients. The presentation was in line with the overall spirit of Predictive Analytics world – practical advice from industry thought leaders and Fortune 500 experts as well as hands-on workshops that would produce results. The JMP sponsored June 25th – June 26th conference in Chicago highlighted a variety of topics relevant to diverse groups including academics, executives and data scientists and has generated ongoing buzz online.
A range of topics were discussed across the conferences wide range of exhibitions, workshops and talks including advanced predictive modeling methods, cloud analytics, customer retention, crowdsourcing, predictive analytics, data visualization, financial services, forecasting, fraud detection, text analytics, uplift (net lift) modeling just to name a few.
Highlights included Aziza’s take on analysis and John Hassman, director of Marketing Analytics for wholesaler United Stationers, on forecasting. According to Information Management’s live coverage of day two, Aziza suggests: “Nobody cares about data volumes and speed; they only care about the final number. You must think about your data as a service … You need applications that are mature enough for users to drill down to that one number they need, that they’re looking for. The ability to map that semantic layer and create a direct service is where there will be ‘wins’.” When it comes to predicting about a firm’s financial future, Hassman, in a similar vein, suggests the popular notions are off: “No one knows, but it’s better to look at the data you have and make informed decisions.” Based on his experience with United Stationers, he recommended quick modeling with in-house and publicly available data using Ycharts.com, citing his company improved accuracy of internal forecasts by 30 percent (and now consistently within 5 percent of forecasts) and fewer budget revisions. Other interesting talks included Bob Grossman’s well-attended presentation on analytic maturity in which he discussed how to speed up analytic maturity and the role organizational culture plays in doing so.
Popular workshops included Matt Flynn of Travelers’ half-day Sunday session on JMP, SAS and R, which attracted R, JMP and SAS users. According to Ann Miley of the JMP blog, Flynn suggested “using scripting as the glue that holds things together [and] lets you take the best of what you like from different tools,” which allows users to “then run longer processes in a more automated way and create more analytic bandwidth.”
Of the many exhibitors present, the Central Intelligence Agency purchased a booth to recruit data scientists. The analytics company, Latent View, earned attention with catchy t-shirts that reflect their strategy stating: “We torture data until it confesses.”
Dan Abbott of Abbot Analytics, who gave a talk on HR Analytics, lauded the event’s practicality suggesting that while predictive analytics may be something difficult to understand, and even harder to explain, “attendees don’t just get a bunch of algorithms and techno-jargon,” but guidance that will benefit their projects and organizations.
For more highlights view our Storify collection featuring notable insights and links to further reflections.