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IoT has enormous applications. Every person in supply chain hungers for more data, especially real-time data, and IoT promises to satisfy that hunger. But, it’s difficult to see all the business cases that IoT can solve. We also need to be prepared to handle the unforeseen consequences of having tons of data.
While we may not see all the ways to use IoT data, once it’s available our colleagues will come up with new and clever ways to use it. We have to be prepared to encourage new ideas and ways to apply all this data. Our normal discipline of approving projects that have a proper return on investment still applies; however, the innovation stage of projects can now be much broader and non-intuitive, allowing non-linear conclusions.
Having more data is a huge advantage. It can make an organization more competitive. We should encourage our users and colleagues to test ideas and hypotheses using these data sets. This can range from getting engineers to apply sensor data for better product design, to insights in cutting costs via processes, to the knowledge of how the products are actually being used by customers.
One complication is the legality of collecting all the data. Collecting data on machine performance itself is unlikely to cause problems. However, if it is used to track people’s performance, or, more precisely correlated to performance, then we need to address opt-in/ opt-out questions and make sure sensor data is properly matched to people. This gets murkier if we are going to start tracking actual data about people– think health data such as heart rate or breathing rate, or even where someone’s eyes are on a screen. In supply chain operations, some of that data can be used to improve safety, which is overwhelmingly important. Yes, some of this problem is covered under the USA’s HIPAA policies, but not everything.
In supply chain operations, some of that data can be used to improve safety, which is overwhelmingly important
We need to be very mindful about privacy issues, and recognize that we in IT will be responsible for governing ourselves, and have an obligation to protect our people and processes.
Just as important as the privacy issue is the issue of data ownership. If a company makes a machine with lots of sensors and those sensors are reporting to both the manufacturer and the user/owner of the equipment, then who owns the data? Can the owner forbid the manufacturer from collecting the data, or the reverse? If one of them uses the data for better profit, is that party obligated to pay the other party a royalty? In the logistics space, the most obvious example is the data coming from a truck. Can the truck owner forbid the collection of the data, even if the manufacturer is anonymizing it? Equally, does the manufacturer have the right to charge the owner for the performance data on the truck? This question is way beyond the old questions of data security or storage.It gets right to the fundamental question of ownership. We, as IT leaders, should be leading the discussions about legality, privacy and ownership.
We also need to look at our skill sets in-house or with our vendors. Many of us have outsourced our desktop support and related activities. Now we’ll need more general hardware talent and networking talent to install and manage all the sensors we want. These hardware specialists are going to be crucial to logistics operations – our mechanics will need to have IT skills. Even more, interestingly, this group also will need to work very closely with the data warehouse and data scientists – a brand new pairing of talent. The project startups for the early projects are likely to create interesting team dynamics that good leaders will need to watch carefully.
Long range, we need to consider the reliance our people have on data to make decisions. For leaders, making good decisions with incomplete data is a skill and hard to develop. Future leaders, at the supervisor level in both warehouse and plant, will have all the data they need and more. Given this level of automation, what tools will we need to develop leaders? IoT might make it more difficult to select and guide our future leaders because junior leaders will have fewer chances to make decisions. Will all this data make our leaders lazy? Also, all this data removes the need for many current leaders, shrinking our management pipeline.
IoT is inevitable and exciting for most of us, especially in the supply chain space. The ability to manage real-time is something we’ve thought about for our entire careers. All this data gives us chances to experiment cheaply, manage with less uncertainty, and increase our productivity dramatically. These dramatic increases in productivity will come from unexpected directions because we have allowed and encouraged people to go where the data takes them, however unexpected that may be. The question is, are we ready?
Founded in 1960, DSC Logistics offers critical business strategy based on collaborative partnerships, innovative thinking, and high-performance operations.