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Three ways to make (new) money from enterprise IoT data

A great number of enterprise IoT projects remain stuck in pilots, put aside for another day. Before they even start, the challenge is how to make money from, at least to cover the initial investment and take a first giant leap into the unknown. But promising new IoT monetization models are emerging.

Apart from technological aspects, the great challenge with enterprise-wide IoT projects is they do not work like traditional IT programmes; their scope is different, and their value is undefined. The traditional system of payments – once for hardware, and periodically for service – does not scan. The volumes in play are askew: the number of devices, or endpoints, is through the roof, and the amount of data is through the floor.

Fortunately, innovative new IoT monetization models are taking root; some are just emerging and some are well-formed. Theresa Bui, director of IoT strategy at Cisco, talks with Enterprise IoT Insights about three of the most promising.

1 | Device-as-a-service

Enterprises have been moving to a device-as-a-service model for some time. The prevailing wisdom in the enterprise market – and especially in the industrial market, where equipment is expensive, and single big-ticket purchases are hard to bear – is subscription-based asset provision works, and encourages a ‘stickier’ relationship with customers, and a better return on investment.

It is an increasingly familiar model for IoT monetization in the consumer market too, where subscriptions are increasingly attached to everything from consumer electronics to car buying. The fee covers purchase and maintenance, typically, but the service-wrap is being multiplied out with airtime, content and analytics. “It behoves manufacturers to keep devices up and running, since service costs cut into their subscription revenues,” notes Bui.

She cites a couple of examples. In the industrial sector, the likes of automation specialist ABB have deployed robot arms in factories across the world, including the latest production-line simulators, on subscription-and-maintenance models. Tractor maker John Deere has been selling its farm vehicles bundled with an expanding roster of services for monthly and annual fees.

Three ways to make (new) money from enterprise IoT data
Theresa Bui – Cisco’s IoT strategy chief says cities and enterprises are just starting to test value-based pricing models

The data gleaned from IoT sensors in and around the original product are driving the services mix. John Deere, for one, is not hiding out in a distribution centre any longer, its hand across the bonnet of a shiny tractor; it has an “everyday relationship” with farmers for the services it delivers.

“All sensors on its tractors, combined with its cloud platform, means John Deere does everything from weather forecasting to sophisticated stuff like soil analysis – to provide information on to plant and harvest crops. John Deere has an everyday relationship with farmers for all of the services it delivers,” says Bui.

2 | Data sharing

Data sharing is a newer IoT monetization concept, or process at least, and gnarlier in terms of the rising privacy and security regulations around it. But it is lucrative for multiple players, and begets better services and new innovation across industries, in theory. As the number of installed IoT devices, in the home and workplace, rockets in the next years, insight into the behaviour of people, machines, enterprises and society becomes profound.

There is money to be made along the way, as signposted by many connected home manufacturers. Energy device brand Nest, maker of the ‘learning thermostat’, has been packaging up and reselling anonymous data from smart homes to insurance companies for five years already.

Insurance is the primary customer for anonymised user data; home cover and vehicle cover are the best informed. Cisco has a large number of car brands on its books, which discuss with insurers ways to package and use randomised vehicle data. Bui points also to the value of data gathered by sensors in windows and basements.

“They detect water leaks and flooding,” she explains. “Flooding is the biggest pay-out in insurance. There is great value in packaging up data for insurers to use in their own actuarial analysis in product development. It’s a newer model, and enterprises are still figuring out whether it’s a business want to get into.”

3 | Value-based pricing

Value-based pricing, the newest method for making money from IoT data, makes perfect sense in a market dominated by billions of cheap miniature devices that use hardly any data. “Value-based pricing is a new idea, which people are only just starting to test. The whole model of products and devices as-a-service lends itself to value based pricing,” comments Bui.

The principle of it is that, for smart devices in smart enterprises in smart cities, not all events are equal. “A connected trash can notifying a smart city operations manager it needs to be emptied, is very different to traffic light issuing an alert that it needs changing. The second is a higher value event, and could have a different charge attached,” explains Bui.

More sophisticated agencies and enterprises in smart cities in Asia are already testing the mode. Tech providers in the industrial sector are also looking hard at ways to make their IoT services pay. The opportunity is immense. A factory might have 10,000 sensors, generating one petabyte of data per day; an oil rig might have 30,000 sensors, generating 1.5 petabytes of data per day, she says.

An IoT device manufacturer that can show its sensors have reduced valve failures on rod pumps in an oil field by 30 per cent has a new line of negotiation, she suggests; the same for a vendor offering a product that detects gas leakages in hazardous scenarios, or predicts outages on assembly line equipment. The question for the customer is what they would you pay each month for reducing downtime and improving productivity,” says Bui.

She adds: “In the world of LPWAN, and specifically NB-IoT, the economic model is no longer feasible to charge per-device per-data-usage each month.”

ABOUT AUTHOR

James Blackman
James Blackman
James Blackman has been writing about the technology and telecoms sectors for over a decade. He has edited and contributed to a number of European news outlets and trade titles. He has also worked at telecoms company Huawei, leading media activity for its devices business in Western Europe. He is based in London.