Let's get the buzzwords out of the way: With the imminent explosion in the number of inexpensive, often wireless sensors and devices of all kinds connected to the internet (the Internet of Things, or IoT), we will be tasked (and challenged by our competitors) to make use of a tsunami of data to improve plant operations. "Big Data" is defined as data coming in such large volumes, or so fast, or in such unusual forms (images, sounds) that we can't deal with it using conventional means.
So how will we handle it? I was given a glimpse of the answer to that question at the recent Inforum meeting for users of Infor software in New Orleans. Infor has spent the past decade or so acquiring leading industrial ERP, HR, CRM, PLM, CMMS—pretty much any software function you might need outside of automation—companies and integrating their packages and clients into a software as a service (SaaS) model, whose latest version is called Infor Xi.
Judging by the cheering during the CEO's presentation about new features and upgrades, the company has enthusiastic clients, especially for its asset management offering. But what impressed me the most is its focus on meeting big data head on and its dedication to building a consumer-style (read Apple-like) affinity among its industrial end users.
Infor has taken similar approaches to both tasks: Gather a group of the most highly talented individuals with the right kind of expertise, put them in an environment designed to foster creativity, and turn them loose on the problems.
A new group called Dynamic Science Labs has been assembled to focus on infusing machine learning and big data analytics into the company's applications, "bringing data analytics to companies that aren't large enough to have the capabilities to take advantage of their vast amount of data," say the PR folks. Who wouldn't see themselves in that mirror?
Early examples of the group's success are rather prosaic. One is to optimize hospital nurse scheduling by balancing workload against factors including expertise, continuity of care, language and room proximity. Another is helping distributors optimize prices to maximize both customer loyalty and business margins, using what-if analysis and extrapolating results for individual customers over customer groups based on industry types and real-time, product-specific, financial performance, seasonality and price-response data.
These early examples don't mean much if you're working in a chemical plant, but they do show the company is taking on detailed, application-specific tasks, and the chemical industry is on the list.
A second Infor think tank called Hook & Loop is dedicated to raising the joy of using its software. Founded in 2012, this group of more than 80 "talented creatives" including designers, writers, developers and filmmakers is based in New York City's Silicon Alley.
Imagine a hierarchy of software functionality starting at the bottom with "useful" (it works) and rising through "reliable" (available and accurate), "usable" (can be used without difficulty) and "convenient" (easy to use, works like we think it should). Most companies—especially ones that make software you have to use to do your job—would be happy to reach that level, and many users just wish they would.
But through Hook & Loop, Infor strives to reach higher levels of "pleasurable" (memorable experience worth sharing) and ultimately, "meaningful" (has personal significance). A demo showed me they're well on the way.
It remains to be seen what Infor—and other software companies—will be able to do to help our process industries take advantage of Big Data, but it's good to know they're working on it and also striving to make it beautiful.