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The time is right for IoT for manufacturing applications

IOT technology adoption is growing as it becomes more feasible and delivers useful data. However, manufacturers should resolve issues of security, scalability and data quality.

I was speaking to a friend who works outside of IT about how his business was going. He mentioned that he thought 2019 was going to be the year when the Internet of Things would become the Internet of Something, meaning that all the hype and proof of concepts around IoT would finally start hitting the bottom line in a positive way -- and that his business was planning to monetize it.

It made me realize that IoT is making the same journey that all types of major IT innovations typically make and that it is finally reaching the stage where IoT technology can be implemented without concerns about it actually working.

Three drivers of IoT for manufacturing

As with many technologies, the driver for "why now" is a combination of the three dimensions of design thinking -- feasibility, desirability and viability. Here's a look at how each of these can drive the adoption of IoT for manufacturing.

Feasibility. The advent of many SaaS platforms like SAP Leonardo means a reduction in the hassle and technical know-how required to make an IoT manufacturing application work. The various proof of concept (POC) and front runner projects have hit and ironed out technical problems, which leaves  time now to focus on the functional aspects of the solution. This also means that the costs to achieve IoT solutions are dropping, which significantly boosts the business case for implementation.

Desirability. One of the most attractive features of IoT for manufacturing is the ability to match what is happening in the real world with what is recorded in IT systems. Without IoT, these updates  require human input that is often delayed, incorrect or just missing. But when machines talk to machines you can now put more trust into the data in your systems, which should lead to better decision making. In addition, consumers (both public and commercial) have higher expectations on the level of visibility they require for their transactions. For example, what is the order status? When will it arrive? When does it need servicing? With IoT, companies can get the same kind of information about their supply chains.

Viability. IoT for manufacturing can be strengthened in two ways. First, gaining greater insight into how products and supply chains actually function is great feedback for process and product improvement and could enable new business models where you can sell outcomes instead of products. For example, energy companies selling temperature regulation, appliance companies selling clean clothes, or tire manufacturers selling grip. Second, IoT can enable companies to monetize gathered data (with users' permission) to deliver additional revenue streams either as a new business line or as a feed to another organization that can use the data to enhance its offerings. For example, Visa is partnering with Google to improve Google's advertising services. This can even go a step further with solutions for data analytics and machine learning, making the exploration of this data much easier for non-data scientists.

Three key enablers of IoT for manufacturing

Once your business has decided to pursue IoT manufacturing to help optimize the current business model and introduce market-leading innovations, it is important to identify and address key enablers that are required for a successful deployment.

Security. First, it's critical to establish security around all devices and data, as reputational damage is not something to take lightly. These issues can be mitigated by working with an IoT SaaS platform that has already pre-determined many of these problems and offers a framework to mitigate them.

Scalability. With IoT, it is also important to think about how your solution will scale beyond an initial pilot. Fortunately hyper-scale cloud providers deliver this type of elastic infrastructure so you can start small but scale big.

Data quality. Additionally, companies need to establish a robust data quality and governance program around IoT initiatives. The volume of IoT data can be mind boggling, as each of these devices will have an identity that needs to be mapped to its Digital twin, and the data associated with that digital twin will also need be managed. With the right data quality measures and governance in place, the IoT solution can become a trusted asset.

Get to the Internet of Something

So now is the time to turn the Internet of Things into the "Internet of Something." Keep a close eye on the IoT in manufacturing enablers (your IT department should be able to help), and with the right SaaS platform behind you, you can focus on competitively delivering what your customers want. Pretty soon you will be selling outcomes -- rather than products -- and reaping the benefits of innovation and customer retention.

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