Digital transformation projects often seek to gain insights from operational data, understand how to keep it secure, and figure out how to benefit from advancing artificial intelligence (AI) technology like machine learning and cognitive computing. Since early 2014, we’ve continuously enabled co-innovation projects working against use cases from multiple industries like oil and gas, mining, manufacturing, healthcare, and retail. They all investigate and deploy solutions that extract information from data available from a world in which everything is now connected.
Extracting value from operational data
In this article, I will draw from material derived from one of our current co-innovation projects, zeroing in on the aforementioned challenges. To get more specific, let’s consider what is required to identify data of interest, aggregate this data, process it at the edge, and then get it flowing into data stores. Then, drawing from these data stores, analytic tools can be used to further ingest, explore, hypothesize, correlate, analyze, predict, and visualize it.
This specific project’s focus was to integrate two standalone offerings in the market today that would bring an Internet of Things (IoT) gateway appliance, fused to a multi-tenant cloud capability for managing the collection of machine data, for direct consumption by a suite of predictive analytics applications. Such a capability, once deployed, can become game-changing for a company. Something as straightforward as being able to provide insight into fryer-oil usage and filtration compliance, for instance, can have real implications on cost and quality.
The two partners entered the SAP Co-Innovation Lab where they could actively test and validate, in a very granular way, how to integrate the two systems to create a more unified bundle of capabilities. The project team confronted early bottlenecks and identified sound configuration parameters. What they learned contributed directly to the overall efficacy of the target solution to accelerate implementation and deployment time. And in this instance, the collaboration has produced results highly applicable to the same problem in other industries.
Taking advantage of multiple strengths
Tackling such challenges can be easier said than done, largely because (for many companies) machine data generated by sensors is highly segmented. Much of this data is tucked away in silos and often categorized based on the device manufacturers. If you lead an IT team asked to spearhead an effort to make this data accessible and of value for the company, you invariably work with those in operations technology (OT) who will understand the electromechanical and physical dimensions of managing machine assets and their maintenance. IT and OT are different worlds, and a co-innovated effort means taking advantage of multiple strengths. In our example, one partner brings a hands-on understanding of OT requirements and operating environments and could offer deep knowledge on how to intelligently communicate, store, and forward machine data to the broader team and project effort.
Bridging OT and IT teams
A team working to form an IoT–based solution could benefit from including a partner with both industry and co-innovation experience, as it can aid in bridging communications among the IT and OT participants in the project. In this way, an IT team and its OT colleagues can stay focused on making sure the co-innovated capabilities integrate with and support existing business systems and process. Here, the other partner is adding value through applying its technology and know-how to simplify and optimize consumption, and supporting business decisions by having collected the right data that is rich in useful information. An IT and OT co-innovation team working with co-innovating vendors can accelerate progress as well as mitigate risk. Together, they can leverage proven capabilities, avoiding the riskier trial-and-error time when attempting something, new, complex, and with constraints from limited expertise.
Discovering the future
I’m continuously reminded of the quote from science fiction writer William Gibson: “The future is already here, it’s just unevenly distributed.” From my Co-Innovation Lab observation deck, I regularly encounter discussions with customers who are seriously grappling with issues that I’ve seen addressed in other industries. Co-innovated solutions often emerge adjacent to what is delivered by vendors directly, and do not necessarily get immediate and widespread visibility through some broad go-to-market initiative. An oil and gas IT/OT team that is heads down facing its own discrete challenges may be unaware of some IoT-based solutions deployed by an existing vendor in utilities or mining that can be readily replicated and applied to fit their needs.
In my next blog, I’ll look forward to sharing some co-innovation IoT problem-solving featuring the unique capabilities of sensors not at rest and the immediate value to business.
Learn more about how data can drive innovation in Data – The Hidden Treasure Inside Your Business.