Anyone familiar with “The Imitation Game,” a 2014 film about famed-mathematician Alan Turing’s work to crack German codes, understands how important data was during World War II.
As Turing wrote shortly before the war in a 1937 article titled “On Computable Numbers, With an Application to Entscheidungsproblem” published in the journal Proceedings of the London Mathematical Society: “According to my definition, a number is computable if its decimal can be written down by a machine. … Although the class of computable numbers is so great, and in many ways similar to the class of real numbers, it is nevertheless enumerable.”
In case you’re wondering, “entscheidungsproblem” is not a typo, and, no, gesundheit is not the proper response. It’s a term meaning “decisions problem” based on a challenge German mathematician David Hilbert posed in 1928 looking for a step-by-step mathematical procedure based on axioms. It’s complicated, but you can read more about it here if you’re interested. Turing and another mathematician named Alonzo Church both deduced the entscheidungsproblem is not possible, but, nevertheless, an interest in algorithms began to take root within the “computable numbers” community.
Data is just as important now as is it was then—and undoubtedly more so. Because of advancements in software applications, there are better ways for people and companies to use data and learn from it than ever before.
With the emergence of Industry 4.0 and the vast amount of data that can be collected from various sensors, mobile devices, wearables and such, it’s not surprising that organizations are looking for a solution for how to tap into that data to help mitigate risk while increasing productivity and being mindful of their return on investment.
Enter the Digital Transformation
“There are likely tons of things you can do to help unlock the potential ROI” through the digital transformation, said Scott Lehmann, Sphera’s vice president of product management for the company’s ORM for Operations solutions. “And given that most organizations cannot do it all at once, there needs to be a way to prioritize their efforts and drive focus.”
As Lehmann explained in a recent SpheraNOW podcast, Sphera’s “2018/19 Operational Excellence & Digital Transformation” report found that almost 70% of companies are starting or implementing a digital transformation project, and about half (53%) are trying to figure out what digital transformation means for them.
A recent article from Datanami explained digital challenges succinctly: “The revolution of Industry 4.0 is not the big data itself. Manufacturers have been generating a lot of real-time production and quality data for quite some time now. However, it is not unusual for these lakes of siloed data to ‘go to waste’ due to the lack of platforms that can truly leverage these diverse data sources and extract overarching insights to improve quality, productivity and so on. In other words, the pain point is not generating and collecting data but being able to effectively extract value from it.”
To borrow a phrase made famous by actor Neil Patrick Harris’ character, Barney Stinson, on “How I Met Your Mother”: “Challenge accepted.”
It starts with focusing on the safety culture, Lehmann said in the podcast. “You need to enable people with technology-supported business processes and the tools to change the operating culture by providing visibility, transparency and the means to do things in a better way,” he said.
Technology can be a great enabler, but it needs to be designed to help people collaborate, work more efficiently, effectively and safely. “Think big, start small, scale fast,” Lehmann said.
To achieve that goal, he explained that it’s important to connect pain points throughout the organization and connect stakeholders, and software designed to capture all that Industry 4.0 risk-related data should include interoperability functionality and open standards.
As Turing once said, “We can only see a short distance ahead, but we can see plenty there that needs to be done.”
That’s some #truth from Turing, and it certainly applies to digital transformation strategies as well.
Achieving Excellence
Lehmann then explained how one large company went into a big digital transformation project with a series of goals: to close the loop between operations, maintenance and engineering to reduce risk, improve productivity and reduce costs; to transform complex data into meaningful information with actionable insight; and to integrate disparate data from various vendors and systems. After the project was completed, the organization was able to receive a “rich, deep and single, shared view of the operational reality to help [their] people proactively manage activity and mitigate risk according to corporate policies and standards.”
In a second case study that Lehmann cited, the company reported that it was able to save $6.5 million in annual frontline efficiencies, achieve a 75% reduction in crew wait time and a 50% drop in supervisor wait time, and realize a 20% decrease in recordable safety incidents. How did they achieve this? By focusing on driving safer, more efficient work practices, ensuring corporate policies were put into operational practice to ensure compliance and that risk assessments were integrated among other things.
“The digital train is leaving the station,” Lehmann said, “but it’s not too late to still get on board.”
And smart organizations will do just that before a big entscheidungsproblem emerges.
To learn how a leading chemical operator is beginning to unlock the potential of digital through its Safe Work 4.Zero program, please click here.
