Is your organization thinking of embracing a digital business model supported by IoT-connected devices? If so, this article outlines a clear and cost-effective strategy for incorporating IoT into your organization.
Originally published in H1 2019 AXUG Magazine
Over the last decade, we have seen the internet of things (IoT) go from being relatively unknown to one of the most talked-about technology innovations. In 2009, IoT accounted for $18 billion in sales; in 2017, those numbers surpassed $1 trillion.
It is not difficult to understand why IoT has seen such rapid growth. Connectivity has become pervasive. Hardware devices are cheaper, smaller, and more powerful. And the rise of cloud computing has enabled all companies, not just large enterprises, to collect massive amounts of data, store it in a centralized location, and turn it into actionable insights.
Despite this progress, many companies today have yet to move to digital business models supported by IoT-connected devices. While there are many reasons cited for not committing to IoT, we most often encounter a belief that IoT initiatives are too complex, extensive, and costly to be relevant to companies with realistic budgetary and resource constraints.
The primary goal of this article is to correct that misconception through this phrase: Think Big, Start Small, Reinvest Fast. At the end of this article, I provide examples for IoT projects that companies of any size can implement or learn from on their IoT journey.
Think Big
The quick-win strategy for jumping into IoT is to buy cheap sensors, throw them on/in machines, and begin gathering data. While it is very tempting to start small and fast, it is more important to first lay out a vision for your operations. In a study of IoT’s early adopters by HPE’s Al Madden, respondents cited insufficient planning in their early IoT projects as the main cause for late stage rework and even project failures.
You may be wondering, “If these small projects are less disruptive and focused on solving a single problem, how can they lead to broader failure?” That is because what you build today—including the infrastructure, architecture, security, data standards, and hardware—will influence your future IoT projects. Remember, the goal of IoT is to connect your people, processes, and assets via one unified location. We are not building the internets of things.
In order to Think Big, your team must first identify your primary goal. Most IoT initiatives are meant to do one of two things: optimize operations or improve Customer experiences. Once the vision is documented, it is important to gain an understanding of what is required to reach that goal. What hardware is needed to capture data? Where will data be stored, who needs access to it, and how will it be secured? How will numerous data sources be integrated into a single location? What tools will be used to analyze the data and turn it into actionable insights? And what underlying technology has the power to process these massive new data sources?
Start Small
Once all of the above is understood, it may seem natural to create a “big bang” solution that will solve all problems impacting operations. However, a 2017 Cisco survey found that 75 percent of IoT projects are failing to achieve their objectives. While those failure rates are not slowing adoption—in fact, 73 percent of participants in the same survey noted they are using data from their IoT initiatives to improve business performance—it is important to balance risks and rewards when beginning an IoT journey.
How do you start small? The best way is to identify one problem area within your larger vision to solve. Then, drill down into detail and identify the questions you would need to answer in order to resolve or improve the process. Once these questions are defined, you can gain a better understanding of the type and structure of the data needed to answer those questions.
Your initial return on investment can be increased by choosing an area that can be scaled or used as a template for future IoT initiatives. Therefore, when building your initial IoT solution, it is important to leverage a platform that is extensible and scalable, enabling you to add on capabilities and grow your solution footprint. Security should also be built in—into all microcontroller (MCU) devices, operating systems, and cloud infrastructure—to prevent breaches and respond to emerging threats. And with technology changing so quickly, be sure to build a solution that is capable of swapping in newer technology as it becomes available.
Always remember that starting small is not thinking small. Rather, it means iterating with small wins that align to the larger vision and business objectives. This approach limits up-front risk and can fund future IoT projects.
Reinvest Fast
As stated earlier, we believe it doesn’t take massive investment to dip your toes into the IoT waters. By implementing a few sensors, integrating data sources, building in simple alerts, and automating manual processes, IoT has the potential to provide a positive ROI beginning day one, even if in a limited scope. Be prepared to learn from any failures—or surprises. Then reinvest into future IoT initiatives that can provide a multiplication on your return. If the initial IoT project is implemented correctly, it should be able to be scaled up and out with less incremental investment. By leveraging previous architectures, integrations, and learnings, new IoT projects can be launched faster and with less risk. The more connected you become, the bigger impact IoT has on optimizing your operations. And it takes less time to achieve your ultimate vision.
IoT Entry-Point Examples
Now that we have discussed how to Think Big, Start Small, and Reinvest Fast, how do you know where to begin? Below are a few IoT entry points we have seen manufacturers implement as their first step toward optimizing operations with connected factories. Hopefully you can implement some of these “quick wins”—or use them to help you brainstorm additional use cases relevant to your business.
Do you have materials or products that must be weighed for formulas, pricing, packaging, shipping, etc.?
If so, you likely have people responsible for manually reading weights from scales and entering that data into your system(s). Leveraging IoT scales and integration, you can automatically capture weights and populate all appropriate forms and fields without any manual data entry. In our experience, this can speed up weighing cycle times by 91 percent and enable the reallocation of resources. As you build toward your larger vision, the data from these scales can be integrated with data from other machines to learn and monitor product quality trends while predicting and preventing unplanned downtime.
Do you have equipment that needs to be serviced or fixed based on utilization?
If so, you may be recording utilization manually or using production averages. This could lead to equipment being used too long—or costly repairs before machines actually need them. You could go purchase new “smart” machinery that connects to the cloud, but that often requires a large capital expense. Another option could be as simple as adding vibration sensors to the outside of current machines. These sensors would monitor when the machine is on and vibrating. That data can be tracked in real time, at both the machine and component level, and used to proactively schedule maintenance and prevent unplanned downtime. Scaling up, these sensors could track all of your assets.
Do you work with materials that need to be stored, produced, and/or shipped within a controlled environment?
If so, you likely have employee(s) reading temperature and humidity sensors within machines or rooms at required intervals. For example, someone may manually read and input data at the start and end of every batch. By implementing connected sensors, these manual checks are eliminated. Real-time readings are captured, enabling more proactive resolution at the moment of variation. Whether stopping production before more materials are consumed or speeding the relocation of inventory, companies can dramatically reduce waste with IoT. When integrated into a connected factory, this data can be leveraged to identify downtime trends, perform real-time forecast adjustments, and improve quality.