I previously discussed some of the business benefits that have been identified by business executives in a recently conducted survey. Here I will focus on some of the uses cases being deployed and considered to achieve the top two priorities, increased productivity and improved customer service.
The use cases for the Internet of Things (IoT) are very broad ranging and will vary industry by industry and company by company based on individual priorities and business challenges. Connected products and things can communicate their condition and how they are used and performing. This data can then be leveraged across the extended supply chain to provide real time views and changes in supply and demand, optimize logistics processes, and schedule maintenance when it is needed. Usage and performance data can be fed back into product design, and predictive analytics will be used to reduce failures and outages.
The top areas identified in the survey were Logistics, Manufacturing, Demand Management and Short Term Planning
It’s Full Speed Ahead for Logistics Processes
When we look at the extended supply chain, the survey shows that currently, the top use cases fell into the area of logistics with track and trace (63%), and transportation (58%) being the top areas of focus. The logistics ecosystem has many players, and moving parts as items are stored and shipped between suppliers, distribution centers, manufacturers, retailer, and customer. Tracking the movement, physical location and physical state (e.g. temperature) of good across the network is therefore seen as a major benefit.
Keep Those Assets Up and Running
Managing and automating predictive maintenance using internet-connected sensors and big data analytics can transform the way businesses operate as was confirmed by the fact that 57 percent of the survey respondents identified asset management as a high priority use case area.
The Internet of Things can take asset management to a whole new level. When an asset requires maintenance, manufacturing capacity is lost as the maintenance crew have to be called to repair the equipment. With IoT enabled devices, you can get advance notice about a potential issue and in some cases, the device can be fixed remotely in much less time.
Predictive maintenance benefits the asset owners by being able to analyze trends, better understand defect and failure patterns, and minimize downtime so that they get the most operational value out of equipment assets. It also creates new opportunities for service providers who can expand service offerings to asset owners and deliver standard and add-on services more quickly and efficiently. Asset manufacturers can also see benefits through identifying design issues more quickly, lower warranty costs, predict recalls, and create innovative aftermarket business models.
Industry 4.0 and Manufacturing
Today, manufacturers face pressure on several fronts. They must achieve sustainable growth as rapid changes in customer buying behavior and geographies increase market volatility. At the same time, they must adapt to new business models – from embedded services to increased partnering – that are challenging the fundamental way they create and deliver their products. For these reasons, it was not surprising that manufacturing featured in the uses cases that companies are considering, with Production Planning & Scheduling and Discrete Manufacturing (56%) featuring strongly.
Responding to Change with Improved Demand Visibility and Short Term Planning
Over recent years becoming “demand driven” is a common theme with supply chain executives, so as expected short-term response planning (46%) and demand signal management (46%) were high in the list of uses cases identified. To become a truly demand-driven organization requires the ability to capture external market and retailer data in real time, and to combine it with internal business data and state-of-the-art analytics, to sense, assess, and respond to demand signals faster than ever before.
The Internet of Things will play a major role in driving business processes moving forward. In the next installment I will discuss some of the challenges when considering where and when to leverage these capabilities.
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