Many end users have been through it more than once. The executive suite announces a new industrial internet of things (IIoT) investment to the tune of millions of dollars. Instead of sharing the enthusiasm, operators cringe. What represents promise to the C-suite often smells of chaos to operators.
Tired of experiments and prototypes that interrupt critical workflows, operators on the ground level often ignore IIoT investments. This resistance—understandable in the face of alert fatigue—defines the next phase of what was previously defined as the DevOps dilemma. In tech companies, development teams (programmers) and operations teams (the folks responsible for keeping systems up and running) suddenly found worlds collided by disruptions of the cloud and big data analytics. Conflicting interests and confused responsibilities meant the teams did not work together naturally and new protocols were needed.
The same is true for executives, the information technology (IT) team and end users in industrial companies. The IIoT is here to stay, but its implementation often plateaus at the end user level. No data innovation, however powerful or robust, can function successfully unless it positively and reliably makes operators’ day-to-day lives more efficient and more expedient. End users have a powerful voice to add to the IT and chief information officer (CIO) decision-making process, and it is time to use it.
How Chaos Happens
In many environments, the process to address technology solutions typically follows a precarious path. At the start, someone recognizes there is a problem and wants a technology solution. Not everyone is convinced it is the correct path to take, so a consultant is hired to analyze the solution and provide recommendations (as well as validate the original assessment). Many meetings, slideshows and discussions later, an investment is made in minimally viable products and point solutions that work well on laptops. The executive committee is amazed and greenlights a plan to implement the solution companywide, launching an ongoing investment in research and development.
The final result? The engineers build a growing infrastructure that aims to address every problem while creating the tools to resolve those problems and gather all necessary data. But no one can say exactly when the project will be finished, and leadership continues to fund an ongoing technology initiative. In the meantime, the solution put in place is so complex and cumbersome that no one really knows how to use it. The team must monitor, manage and respond to the chaos that ensues.
IIoT Has a People Problem
While executives see IIoT investments—the bigger, the better—as competitive promises, end users too often experience them as complications. Their days (and often, evenings and weekends) are spent in reactive mode, brainstorming solutions and addressing safety hazards. Many struggle with “alert fatigue,” constantly moving from one issue to the next and forever solving one problem only to identify two others.
The end result is that unworkable—and sometimes unwanted and uninformed—solutions are thrown at teams. A cycle of implementations ensues, as does endemic frustration and finger-pointing. But there can be empowerment in the role of technology, if operators can persuade organizations to put it to use.
End Users Are the Keys to the IIoT Kingdom
In the age of machine learning and big data, companies need a better way forward, and end users on the floor should be integral to the solution.
Rather than run around fire-fighting every pitfall in an implemented tech solution, users should push to be invited to the party during the development process. They are, after all, on the ground floor of enhanced intelligence—the subject matter experts who can add context and experience to machine learning. Users witness firsthand how infrastructure investments can become overly complex, can fail to serve internal or external customers and can ultimately become a cost center rather than a profit-maker.
The involvement of the operations team can quickly remedy some of the most fundamental obstacles that arise in IIoT development—namely the urge to rely on existing systems to solve every problem and the failure to recognize the limitations of those systems. Because they are intimately familiar with how things actually run, industrial users can provide detailed context, and therefore are invaluable to identifying which data points are most important to consider.
Operators are also more easily apt to recognize the cause-and-effect relation between suggested tech approaches and potential outcomes. Putting this knowledge to use should become a key part of any end user’s job in the future.
Bring Operations Into the Strategic Fold
Today, it is no longer necessary to build a complete solution only to later recognize it falls short of expectations. And there is no guarantee that “if you build it, productivity will come.”
The old way no longer works, and users can help lead the way to smarter IIoT solutions. End users understand how to problem solve and are accustomed to trying different approaches. The capabilities of the cloud and ability to create application programming interfaces (APIs) for problem-solving recommendations enable experimentation without impacting the bigger system and with fewer complexities.
Smart companies place the data science and analytics teams, IT or information sciences (IS) workers, operators and business leaders in the same room—often with dedicated experts in solution architecture, business process management and data science deployment—to discuss solutions, practical limitations on those solutions and the interdependence between functions throughout the company. By breaking down the silos of departments and perspectives, a solution that focuses on identifying the right data is required to solve the right problems.
No data innovation will ever have the desired impact unless it positively and reliably makes end users’ day-to-day lives more convenient and more time-efficient. Innovation must enable techs to spend more time doing the work they were hired to do, so that they can optimize the equipment and plant production processes. Only when end users help lead the innovation process, rather than merely be required to implement uninformed solutions, will the IIoT finally realize its return on investment promise.