The Internet of Things (IoT) is changing the future of industry. Cloud-connected “things,” including all manner of equipment and devices, are becoming pervasive among consumers and business alike.
Many of these concepts are not new. Some were known by different labels in the past: supervisory control and data acquisition (SCADA) systems, telematics, machine-to-machine (M2M) communications. Another term has been coined: “Industry 4.0,” representing the Fourth Industrial Revolution.
There are many concrete examples of the IoT in action. In oil and gas, industrial equipment is being remotely monitored across vast distances and often in harsh environments. In agriculture, moisture sensors are used to minimize water usage while maximizing crop yields. Commercial buildings are being retrofitted with next-generation, connected heating, ventilation and air conditioning (HVAC) systems that can factor in weather to maintain comfort and save energy.
Pumps and systems can be retrofitted with accelerometers to analyze vibration and temperature as ongoing condition monitoring. The learning and trends, or normative data, can be analyzed to have a true sense of degradation over time and feed into a data-driven preventive maintenance schedule.
Business Drivers for IoT
Along with vision, IoT projects need funding justification with a business case. There are principally four main business drivers for commercial IoT projects.
- Comply with new regulations: An example is the U.S. Department of Transportation’s new rules for commercial drivers around e-logs and hours of service. Electronic compliance is a straightforward way to document these new regulations digitally.
- Reduce or avoid costs: Examples include field service, logistics and supply chain optimization. Industry is moving from scheduled maintenance to a predictive maintenance model. Also, companies are using IoT to prevent inventory losses among valuable, perishable assets like food and pharmaceuticals.
- Differentiate product: Industrial companies are offering connected product features as adjunct offerings to differentiate themselves from competitors, increase revenue, avoid commoditization, enable better reliability and improve uptime. Additionally, manufacturers are using connected product customer usage data to gain insights and improve road maps.
- Generate new revenue streams: Monitoring a product sold to a customer can enable premium service levels, as well as entirely new managed services revenue streams for manufacturers. IoT is also reinventing the concept of equipment leasing: IoT enables managed hardware-as-a-service monitoring—or subscription-type offerings—that bundle the device with connectivity and the application. This is opening up recurring revenue-based business models for traditional manufacturers. Traditionally, original equipment manufacturers (OEM) have created a product and sell direct or through distribution. The service element is handled by OSM or outside service and maintenance organizations. As sensors can be connected, the OEM itself can guarantee uptime as opposed to a standard warranty.
But why is there not faster adoption of IoT technology? Here are the top five barriers to IoT adoption:
1. Too much media attention is on informational technology
For the mid-tier industrial world, it is hard to decipher the big picture on how and where to start. As a result, the IoT industry appears heavily focused on gadgets and not making them relevant to the particular business verticals themselves—so the IoT can appear expensive and intimidating. While one must understand the pieces and costs, focus on the desired outcome and peel back the onion one layer at a time. As a manager, use data and information to influence human behavior. For example, a maintenance technician can preempt a costly pump failure through use of data alerts and trending analysis.
2. Conservative technology culture or too much focus on operational technology
A second major barrier has to do with the expertise and culture of industrial organizations, which focus on operational technology (OT). Industrial organizations as OT companies are at direct odds philosophically with informational technology (IT) organizations. While IT is defined by constant change and innovation, OT is change- and risk-averse. That is why it is not unusual to see industrial automation systems in service for decades with little or no change. In a world where production downtime can devastate revenue, stability is the top priority.
Kodak was a market leader until digital disruption eclipsed film photography with digital photos. Some referred to those who do not innovate during these rapidly changing times as being “Kodaked.” One has to commit through a series of small experiments to learn from these organizational changes. Companies can mitigate risk by having reasonable expectations in small, coordinated “digital test beds” to determine the value and return on investment (ROI).
3. Lack of industrial technologists to lead the IoT program
There is the question of who in a company can lead the digital charge. Companies need a person or team that can bridge the gap between the IT and OT cultures so competing priorities are met. The program needs a combined IT/OT perspective for the organization, all within the confines of achieving IoT goals with increasing operational complexity or burdens that may be already short-staffed.
An organization must consider how lean manufacturers are running, and think of innovative ways to automate insights, but have human “touchpoints” that force change from those insights such as alerts, schedule maintenance to save on costs.
There are several certifications in data science, online courses and conferences nationwide to introduce middle management to these concepts. Look to team with universities and vendors that can assist with this function and educational need. The thirst and quest for knowledge must be an ongoing mandate of the executive team.
4. Misunderstanding the ROI
Industrial technology investments are highly ROI-driven. IoT should be seen as a process improvement over time that yields significant savings and efficiencies, not as a typical 12-month payback cycle type of investment. ROI must be looked at holistically with the bottom line organization-wide and from a cost-savings and efficiency-improvement standpoint.
Data should be considered an asset not only for SCADA or monitoring, but as condition monitoring that leads to predictive/preventative maintenance. Sensors that monitor vibration, temperature, humidity and more can provide a wealth of new insights.
Measuring and seeing trends from various sensors can help predict failures before they occur, minimizing unplanned and costly downtime. This also improves maintenance schedules, replacing the calendar or manual guides as leading indicators of planned downtime.
5. Security concerns
With all the news regarding cyber security and hacking, it is easy to worry about the potential problems that occur. But there are safeguards to protect sensitive industrial information.
Data can be verified and encrypted with a myriad of one-way communications depending on the level of sensitivity. SCADA systems do not need to integrate sensor data and action it—they can be separated digitally.
In addition, the cloud infrastructure could be networked internally as a “private” or corporate cloud with no access to the outside world.
How to Begin
A straightforward and practical approach should be used when embarking on an IoT project. This should not be viewed as a massive, company-changing effort, but rather a series of small projects or digital test beds that have the potential to increase revenue, improve the bottom line or boost customer retention.
Realize that not all IoT initiatives will succeed—some say that about half will fail. A reasonable approach is to pick a few products and services to which adding sensors and connecting them could result in substantial improvement to the organization’s bottom line.
In addition, identify products and services that could possibly lead to additional sources of revenue. Research has shown from a portfolio of six projects, one will be a big success, two will be average hits and three will fail. This approach is manageable and if the pilots are successful, they can be part of the company’s offerings. If they do not succeed, they can be considered learning experiments.
This process should be repeated. In addition, one should consider the organizational culture when implementing IoT: ensure buy-in from the top management, identify digital directors, transform the company culture, etc. Even with all necessary systems and processes in place, a strategy can be crushed by old visions of what the company is or aspires to be.