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Money-making opportunities in manufacturing: Translating big data into ongoing revenue streams

This article appears in the issue November/December 2018 [Volume 27, Issue 6]
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Predictive services

The capacity to feed predictive models via IoT is well-documented, particularly in the industrial internet. For example, it behooves an oil drilling company with offsite pumps to utilize predictive maintenance to ensure consistent productivity. According to Wills, “predictive maintenance and fault monitoring equal reduced or eliminated downtime,” as well as revenue for those responsible for such tasks. In the consumer sector, the monitoring and maintenance of manufactured goods’ performance is one of the most immediate ways to add revenue streams.

Courtesy of sensors abounding in everything from appliances to personal items such as computers, “what’s new is the products themselves now have IoT embedded in them,” Walker said. This sensor data is directly responsible for an assortment of manufacturing entities now seeing that they can profit from it, Walker noted. “And, there’s every little mom and pop shop saying [for example], I know everything about ovens. I’m going to build a niche for myself and build analytic models to make your oven run perfectly.” In addition to the third-party providers, contemporary manufacturers can leverage IoT to offer predictive maintenance, whereas before, consumers would generally rely on warranties from retailers once products failed. Predictive analytics is also used in the industry to forecast accurate supply chain demand. Additionally, IoT data helps supply chain management with insight into “better asset utilization through knowledge of location, for example—where is it, has it moved—and guaranteed quality and yield control improved through monitoring of temperature, humidity, etc.,” Wills said.

Strategic data as a service

Another lucrative means of monetizing IoT data is to sell the data to strategic partners, which they can leverage for competitive advantage when providing goods or services. This reliable revenue source arose because IoT’s constant data created a “demand for that data and those [consumer] behaviors,” Long explained. Use cases abound in markets related to manufacturing. For kitchen appliances, for example, connected refrigerator data can be sold to partners to market or sell items such as filters. With other home appliances such as washing machines, IoT data can be sold to vendors marketing laundry detergent “so you can know in a target demographic, this is a suburban home with this average income in this part of the country, [and] they tend to use cold water and do this amount of laundry a week,” Long said. “So now the makers of Tide know that you’re doing more permanent press loads in cold water, and they’re going to market you a different type of cleaner.”

Subscription services

Instead of disseminating IoT data to partners, manufacturers can devise subscription services to capitalize on ongoing customer relationships. The precept is that consumers subscribe to—as opposed to purchase or own—the data. Additionally, this concept includes using personal assets for profits. Uber is the quintessential example as it empowers people to use another’s car for rides (instead of purchasing one) and enables monetization for the driver/owner. Although applications for subscription services in manufacturing are vast, some are more accessible than others. Partly due to data from connected cars, vehicle subscription services are gaining traction in the automotive industry. “The vehicle has features in it which allow someone with a phone app to come in, pilot the vehicle around [and] the vehicle knows its location,” Long said. “It’s not something that someone can just unplug; it’s built into the vehicle. As an owner, you would always know the location of your vehicle and who’s signing up to consume it at a certain rate, so that you could use it when you want to.”

Additionally, automotive manufacturers can market specific services based on driving habits so, for example, consumers can buy the mountain driving experience for a weekend with manufacturers tuning the engine so it’ll be optimized for that purpose, Walker said. “That can be across all types of different platforms.” Although not necessarily based on IoT data, there are even examples of entities providing (mobile) equipment for manufacturers as a service “where you take the equipment to where it’s needed, and then you move it on to the next place” Walker added. In all of these examples, traditional modes of production, ownership, and monetization are reconfigured for more flexible business models which empower consumers alongside manufacturers.

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