In two decades the Internet of Things (IoT) has become a reality both in our everyday life and business. Many industries use IoT, and in manufacturing, the industrial Internet of Things (IIoT) is being used to understand consumer needs in real time, become more responsive, improve machine and system quality, streamline operations and discover innovative ways to operate as part of digital transformation efforts.
How, though, can businesses be sure that they are really getting value from their IoT investments?
Change the way of thinking
IoT use cases are extremely broad and span a wide spectrum. For example, pharma companies use IoT data to improve their operations right across the product life cycle, from initial research through to distribution of products. Farmers and animal insurers use IoT data to improve the lives of farm animals and farmers through careful tracking to identify potential problems. In telecommunications, IoT is redefining the ecosystem by driving both operational and philosophical changes.
But perhaps the most important change is the move from thinking about "revenue generation" to "value generation." Tech for its own sake, or to drive revenue, is not enough. Instead, we need to be thinking about how we generate value for ourselves, for customers, and for the ecosystem as a whole.
Bringing ideas together: IoT meets AI
This idea of generating value will become more important as the IoT is increasingly linked with more advanced analytics supported by artificial intelligence (AI). There will be more and more data available, from a much wider range of (IoT-) connected sources, and better analytics tools to analyse them and provide insights. But the connection goes deeper than that.
The IoT will actually be crucial to getting value from AI-based analytics tools. These tools and algorithms need huge amounts of training data. The growth of the IoT has really made them viable – but it is also AI that has made the IoT so valuable. The relationship is symbiotic. The sector in which this is most true could be manufacturing and the industrial IoT. There is a general view that the artificial intelligence of things (AIoT) is crucial to getting value from both AI and the IoT in that sector in particular.
The 5-step framework for value
The IIoT is flooding today’s industrial sector with massive volumes and varieties of IoT sensor data, from production line equipment to products used in the market, sales data and more. To succeed in this environment, industrial leaders need an edge-to-enterprise IoT analytics platform and a strategy that generates intelligence in lockstep with business needs.
There will be more and more #data available, from a much wider range of ( #IoT-) connected sources, and better #analytics tools to analyse them and provide insights. But the connection goes deeper than that. Click To TweetA recent SAS report provides one possible framework for generating value from the industrial IoT. It describes five steps that need to be taken:
- Define your goals for the IoT project.
You cannot generate value if you do not know what value will look like. - Create a holistic IoT analytics strategy.
You need to be sure that your strategy is coherent and works across the whole project – and that it fits with your other analytical work. - Assess the need for edge analytics.
It may be better to analyse data at the edge, as it is generated. This will ensure that it is up-to-date, and also avoid the need for storage. - Choose a proven solution and trusted partners.
You do not need to make your life more complicated than necessary. - Focus on continuous improvement.
Keep looking for the insights that will help you to improve how you operate and make things better for your customers.
For more about the five steps needed to accelerate value from the industrial IoT, you can download the full report here.
