Cashing in on the monetization opportunities of edge data
The recent release of GE Digital’s Industrial Evolution Index provides a unique and revealing reality-check into the state of the Industrial Internet of Things.
While IT and operational technology leaders continue to understand conceptually that the IIoT represents a significant potential source of business growth and increased competitiveness, most companies are still not actioning the technology in ways that would make a material impact on their bottom lines.
A slightly deeper dive into the data reveals that, while connectivity is viewed by most executives as the most critical component for IIoT success, investment cost remains the largest barrier to IIoT expansion. From that data alone, we can infer that shortcomings in connectivity, along with cost and complexities of associated new infrastructure, are the main culprits for IIoT hitting a wall. If the market had solved for connectivity already, it would probably not be singled out by respondents as a requirement for IIoT success. One does not pine for what one already has.
On a more visceral level, the story is much simpler. IIoT has yet to make its case as a strong fiscal sell. If these same executives were seeing a clear path from the IIoT to revenue creation, they would not be citing cost and complexity barriers, and the IIoT would not stand out as such a largely unactioned innovation.
To flip this dynamic, the conversation needs to change. Benefits need to be framed less around the implications of data collection and downstream analysis, and more about direct actions made possible by a straighter line from employee to action.
Once people understand what happens when more data -- the right data, already processed for consumption -- can be put in the hands of personnel at the point of use without the data ever having to leave the point of use, a whole new horizon opens up for the IIoT. Suddenly, the technology can be seen as an agent of change, going well beyond what’s become a perceived rut of efficiency and optimization. The IIoT’s primary job has to be to let companies monetize their data in new and intriguing ways.
The next logical question, of course, is “How?”
What if, instead thinking of IIoT devices as passive data generators and data ‘flingers,’ we think instead of any asset in the value chain becoming a data carrier and processor. In this context, the act of placing data upon, and processing capabilities in very close proximity to, edge assets may just be the necessary catalyst in helping organizations take action on IIoT value.
Here are three clear paths to monetizing edge asset data.
An unexpected cog in workforce development
Much has been made about the growing skills gaps in manufacturing. Deloitte cites a looming discrepancy between incoming manufacturing talent and the skills required to do the job. Site selection advisory firm WDG Consulting calls qualified labor the “number one concern” across every industry. “The shortage is pervasive and extends to all positions,” the firm says.
The trend, however, does not portend bad news for all. When seen through the lens of edge asset data, an entirely new business model may open up for equipment manufacturers, whereby their products can be enlisted to deliver meaningful, on-the-job learning to close these skills gaps.
For example, let us say an asset with which a newly hired employee regularly works has been embedded with information such as its operating or maintenance instructions. Now, at the precise moment this new worker is called upon to interact with the asset, the asset is able to effectively dictate what needs to be done. The asset literally becomes an informed trainer.
Taking the concept even further, such a mode of data transfer also allows experienced workers to broadcast the “tribal knowledge” they’ve accumulated over the years across the organization quite efficiently. They in fact become empowered to show people just how smart they are by embedding their personal tricks of the trade into the assets they work with every day, to then be absorbed by the next colleague down the line.
Edge data allows these workers to understand that technology is not here to replace them; it’s here to increase their current and future value to the organization.
For companies that manufacture assets that must be maintained, think of the upcharge possibilities that can be justified by selling products that now double as a bridge to workforce training. It’s an entirely new, and unexpected, line of business.
The value of validation
Similar to the skills gap example above, the idea of granting passive edge assets with a capability to carry and distribute data holds tremendous intrigue in industries where a product’s authenticity or handling history are critical to the product’s value. Examples include pharmaceutical, chemical and food manufacturing.
For producers in these industries, there is distinct competitive advantage to be gained by offering a “validated version” of products. These differentiated SKUs would come pre-loaded with a detailed, progressively updatable digital record about the product’s pedigree, handling and storage details, usage record and chain-of-custody. In an age where counterfeit pharmaceuticals have grown to epidemic levels, you can visualize a medicine that proves its authenticity to the aftermarket caregiver at the point-of-use through an embedded, detailed digital record.
Not only does this open the possibility to upcharge, but the opportunity to expand trust for a brand comes into play, as well.
“Found money” from better asset management and utilization
Seen largely in the commercial aerospace industry, the act of making asset data updatable and readable by personnel as they interact with assets has driven benefits of sizable scope and breadth. Airlines have seen reduction in labor costs when their maintenance technicians no longer have to guess or spend time hunting down handwritten part histories, find an asset’s most recent test results, or locate an asset’s compliance status record. It’s all right there.
Meanwhile, ground crews can be enlisted to reduce time on the tarmac by conducting digital, automated checks for part airworthiness; this improves an individual airframes’ overall profitability, and when you extrapolate the numbers across an airline’s entire fleet, the impact is staggering.
At the same time, because each flyable part carries with it its own digital history, airlines are able to increase asset utilization metrics by reducing instances of parts being rendered unusable because of missing historical information. To be sure, even if a part is brand new aerospace regulations require the part be discarded and replaced whenever an operator cannot validate its history. Unfortunately, this source of waste plagues the airline industry, but when the history is attached to every asset, there can be no case of missing information.
For ubiquitous investment in the IIoT to occur, it has to ‘show us the money.’ Pushing the data lifecycle closer to the point of action may just become the IIoT’s greatest contribution to industry, yet.