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How to Monetize IoT

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It is known that IoT increases revenue, profitability, security and customer loyalty while reducing and avoiding costs and risks. But how do you understand the business potential of this technology? How to make it an integral part of the Digital Transformation strategy?

It is necessary, first, to clarify the difference between “smart” products, “connected” products and effectively “IoT” products. Smart products have been around for at least 50 years, using systems embedded in non-intelligent objects. The iPhone, basically a connected product, has been around for at least 10 years. However, the advent of IoT products, systems, and environments is recent. These products, systems, or environments have four components: a Value Proposition, a Model, an Application, and Analytics.

The Model is closely linked to the Value Proposition of the product, translating it into variables, which will be collected, analyzed and projected. An IoT-based clothes dryer, for example, has as its Value Proposition “to reduce drying time and the use of electricity, and to generate savings for the consumer.” The variables of this Model would be temperature, electricity consumption and cost. The Application, in this case, would be the code developed to capture, store and provide the information for the Analytics. The latter will predict wear of parts, the need for general maintenance and even the maximum optimal load of clothes to be dried in the same cycle. These are four integrated components that constitute a genuine IoT product.

Using these components of an IoT product, you can identify at least four forms of this technology to generate value to the business: produce better, operate better, maintain better and make new products better.

Produce Better

There are several ways to make a better product. You can add features that competing products do not have, create an experience of superior use or even make preventive repairs. But, the best way to add value to the product via IoT is undoubtedly through innovation or invention.

Let us take, as an example, a product of the medical world. Total hip arthroplasty surgeries are interventions that usually last from 60 to 90 minutes and aim to reestablish the connection between the femoral head and the pelvis. For this purpose, an instrument called an “acetabular reamer” is used, a kind of drill, which prepares the cavity (acetabulum) to receive the new femoral head. A major challenge is that if the temperature of the tissue exceeds 55 degrees C (131 degrees F), there is a risk of bone necrosis. Also, if the enlargement is not done in a perfect way, there is risk of the joint gap, causing immense pain to the patient, requiring new surgery.

A Value Proposition for the IoT acetabular reamer would then be: “to perform the procedure as fast as possible while maintaining the patient’s health.” The model that will represent this proposition will be a function of temperature, pressure, rotational velocity and time of surgery. The Application should, in turn, monitor these variables, always lowering the rotational speed if the temperature approaches the 55-degree limit. Analytics can address a number of situations, such as the likelihood of the patient needing a second repair surgery.

Operate Better

The increase in efficiency is, undoubtedly, the most well known benefit of IoT. Having reduced all that was possible from inefficiency through IT, it now focuses on the Internet of Things to further reduce it.

Consider the utility sector. Efficient operation of power grids has been a challenge for more than 130 years. Even with the advent of SCADA systems and other smart technologies, it is still necessary to send field classes to physically solve incidents and events in nature.

Let us take as an example an IoT product of grid operation, whose Value Proposition is “to reduce operating costs and increase the availability of the network.” Our Model will then consider the variables related to labor cost, network efficiency and average network downtime. The Application will monitor all points on the network, identifying which ones are overloaded, as well as working on equipment and reducing labor costs. Analytics may predict trees falling on the network wires, for example if the winds exceed a certain velocity.

The main added value of this type of IoT product is that the Model can be applied to all network nodes, from generation, transmission and distribution, to the residences of consumers and their appliances. This creates absolutely innovative possibilities.

Maintain Better

One of the first things that comes to mind when thinking about IoT for the industry is preventive maintenance, seeking to optimize assets and reduce costs. We will see that the possibilities with IoT here are much larger.

The Bagger 293 is considered the largest land vehicle. A 25-story tall excavator the width of two football fields, this machine is used for mining and is able to remove material equivalent to the volume of 10 average cars of material per second. Let’s consider the Value Proposition here “to use IoT to increase machine downtime as well as reduce unplanned downtime.” As a Model, we will be considering the relationship between temperature, charge, angular velocity and vibration frequency. The application will monitor these variables and, if the temperature falls outside the optimum range (20o and 110oC), it will also act by throwing water on the joints. Analytics will predict the fatal wear of a particular joint by dispatching a maintenance crew with the correct part before the incident occurs or in the time of preventive maintenance.

Make New Products Better

The self-quantifiable product category is one of the largest prospective businesses. Based on IoT, this category of products measures our metabolism and the activities we carry out, constituting an extremely promising market. Let us examine here the added value for the manufacturer of an IoT clock.

The Value Proposition here is “to use the data of a product to launch other products.” The Model will be based on the usability of the clock – that is, the features that are actually being used and how often. Analytics can then identify, from various clocks, which interfaces and features are most commonly used. You can also identify which information is monetizable for other companies (sports, health) or customers (competitors in the same sports mode). This type of opportunity we call Digital Exhaust, which currently represents one of the largest sources of added value in IoT.
 

The essence of the Internet value of Things is the transformation of data into useful information, whether present or predictive. This will enable preventive, corrective actions or monetization of information. But how to monetize the information?

Monetizing IoT

There is a fundamental difference between a product that uses IoT and a common product. In addition to embedded technology, of course, the IoT product requires a backward infrastructure and constant software updates – for both new functionality and error correction. Because of this, an IoT product can cost up to 10 times more than its basic counterpart. It will, therefore, be necessary for the IoT vendor to seek new sources of revenue to support its products.

The very nature of IoT products leads companies to develop other forms of collection, other business models. It is no longer about the product that is just sold and delivered. A product-as-service perspective is created, along with a more sophisticated result-as-service scale. Within this range, IoT suppliers will have to adapt their business models in an increasingly integrated way to the business model of their clients.

For example, if Rolls Royce, an English company that manufactures IoT aircraft turbines, offers the turbine-as-service product, its billing metric will be “miles flown on filled seats.” We can clearly see how business models are becoming more and more based on success rates.

The Evolution of Business Models in IoT - B2B

In the same way that IoT is under development, the ways of monetizing it are also evolving. They start with the IoT product sale to an IoT Result-as-Service model. The difference between these models lies in the sophistication of the functionality, the expansion of service scope, the degree of partnership with customers (and other partners), as well as in the form of collection.

The IoT Product

This model corresponds to the current way of marketing IoT products. Known as “one-and-done,” it is basically about selling, delivering and eventually solving some problem via SAC. The difference, as already mentioned, is that IoT products have embedded technology, with features and automatic updates. For example, the Tesla car receives OTA software updates for product evolution and correction of bugs. There is no greater connection between the customer and the company. However, Tesla has already started using analytics to obtain information on the use of its cars, thus creating the conditions of evolution for the second model: the “IoT Product-Service” as well as for the self-driven car.

The Product-Service IoT Model

In this model, a physical product is offered along with an optional information service. The objective is to take advantage of the data obtained by sensors embedded in the product and, through analytics, identify problems, prevent failures and suggest corrective actions. For example, sensors on trucks and tires are already a reality. Some tire manufacturers already offer services that help customers save on their fleets. The sensors installed on the tires control variables like pressure, temperature and depth of the grooves, informing the time to change the tires or the need to increase their pressure.

The IoT Service Model

The IoT Service Model is not new. It is the model found, for example, when we use “residence as a service” in AirBnB, “transportation as a service” in Uber or “food as a service” in Instacart. The difference is the variety of goods, equipment and objects available today for use as a service. In addition, the driving force behind this model is the increasing preference of customers not to have assets, but only to have access to them. Just look at the auto industry, where since 2015 there has been a decrease in the number of new driver licenses.

The first interesting example of IoT Service is the information service provided by Rolls Royce. Through sensors installed in aircraft turbines, data on altitude, speed, location and fuel consumption are analyzed to generate reports on the energy efficiency of each flight plan. As a result, airlines can compare their efficiency with the market average for the same competitive flight plans.

The second example, a bit more exotic, would be a theater in Barcelona, ??the Teatreneu, which instituted the pay-per-laugh service. Facial recognition sensors can detect an audience's laughter, with each laugh costing .30 Euros, reaching a maximum of 24 Euros (80 laughs).

The Service-IoT Result

The Chinese company ParStream (later acquired by Cisco) is a specialist in wind energy efficiency. It installs its sensors at no cost to the customer. It establishes a baseline with the client from which it is remunerated by a success rate. This quarterly rate is based on increased billing or energy savings from the technology. In addition, ParStream identifies which turbines are having lower productivity (considering speed, generation power, blade angle and turbine distance), suggesting changes in blade angles.

In the IoT Service-Result model, the supplier establishes a partnership with the customer, not only assuming the initial costs of installing their product orservice, but billing based on a success rate.

The IoT Result-as-Service Model

American companies John Deere and AGCO are creating true IoT platforms, ??where using sensors and software, they along with other suppliers are being plugged in. The goal is to deliver a complete solution, a result to the end customer. They can answer questions such as, “what variety of seed produces the best results for a given geography, climate, and irrigation rate when planted, planted, and harvested by your brand of agricultural equipment?”

These competing ecosystems bring together agricultural machinery, planting management, irrigation and weather data, giving farmers a better result: lower final prices due to higher productivity.

The IoT Result-as-Service Model is still under development and has several challenges. The main one is the billing system, where a detailed analysis of the customer’s profitability has to be made, so that one can identify the value effectively added by the platform.

The Internet of Things brings immense opportunities to IoT’s suppliers and service providers, through specific business models, from the simplest to the most sophisticated. At the more complex end of this continuum, risks and profits are shared with the customer, establishing a true ecosystem of IoT customers and suppliers.

However, to reach these more sophisticated levels, it is necessary for suppliers to change their organizational structures, the profile of their vendors, their production and operation. The big strategic goal, the real race for companies like Amazon, Facebook, Google and Tesla, is being designed to create a platform, a complete ecosystem, focused on results for customers. With this strategy, the company will centralize contact with customers and dominate its ecosystem.




Edited by Erik Linask

Project Manager

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