In this blog we dive into new business models that are directly linked to the introduction of IoT products and services.
First, we introduce a couple of pointers on how to go about identifying the business cases to pursue.
Glaze recommends refining initial business assumptions and subsequent data retrieved to verify the hypothesis. Further we recommend forming a strong framework for concluding whether the project should be continued or stopped. Keep the investment low during initial experimentation phases and once evidence of a valuable proposition is proven, refine the first fickle mock-ups for future applicability. Most importantly is to learn and fail fast.
An innovative business development team will quickly produce ideas from instincts and insights to where digital knowledge can enable new products and services. Alternatively, existing warehoused data can be scrutinised with the aid of skilled data scientists to spot missed opportunities already in-house. Any idea worth testing should then be dismissed fast if not sustainable; hence the recommendation to fail fast throughout the initial trials to keep up with the threat from other competitors exploiting similar ventures in the exponential race to win.
In other words: do not allow R&D to spend months developing a dedicated and novel solution; instead find inspiration from best practices already around and demand patching together generic building blocks. Test functional requirements quickly by Of-The-Shelf hardware modules using standard interfaces and connectivity supported by software tools. Modularity enables replacement of any component creating bottlenecks for the desired business experimentation.
Business models valuable for one business vertical may be applicable across completely different areas. Recent research suggests that a comprehensive list of business model patterns will cover the bulk of conventional business domains. The patterns have been repeatedly recognised as recurring patterns in sectors of chemicals, construction tools, machinery, electricity metering, software, audio tech, health care, telecom, etc.
IoT technologies offer completely new business models that are also applicable to almost any industry and can be used in combination with traditional business model patterns. For inspiration, the following introduces the business models from a group of researchers from St. Gallen University in Switzerland coupled with a few real-life examples:
Physical freemium: Physical products are sold with free digital service (e.g., free apps, software updates); it is anticipated that some customers would be willing to pay extra for premium services. The initial 100koll project from E.ON is a good example of this business model where a physical unit was provided for free to customers and then later on added services could be bought by the customers.
Digital add-on: Physical products are sold (sometimes) inexpensively, but customers can purchase/activate various digital services at high margins (e.g., software programs, additional functionalities). An example is Tesla’s “Acceleration Boost” in which a new customer is offered to buy a software update that will increase acceleration.
Digital lock-in: Physical products are protected to be used with other digital services via sensor based, digital handshake to limit compatibility, prevent counterfeits, etc. The examples here are numerous as this business model reflected many companies’ intuitive way of defending their business and IP. John Deere has previously been a company that had a closed and very limited digital eco-system. This has during the last 5 years however changed and many companies are now providing open APIs and even open eco-systems in order to create more value for its customers by letting third parties add services to the customer experience, thereby creating new possibilities for recurring revenue and in some respect defacto creating a digital lock-in by supplying a comprehensive eco-system.
Product as point of sales: Physical products offer digital sales and marketing services; the customer can consume the content either directly or via smart devices (i.e., tablets, phones). The product itself is now point-of-sales and may bring something completely different to the customer that is far away from its core offering. Best examples are the smart speakers from Amazon and Google, where the speaker now has the very different added services of a sales channel to web-shops and hub for the smart home by utilising the powers of the cloud back-end via speech recognition. The price of the product itself may not be the main source of income, but the services and products ordered through the point-of-sales channel become a regular revenue stream instead.
Object self-service: Physical products can autonomously place orders online. For example, a heating system automatically and independently orders oil to refill the tank. There are consumer products, medical devices that use consumables and industrial products with wear parts that now have the intelligence to detect the shortage and automatically order the consumable or spare part that is needed.
Remote usage and condition monitoring: Physical products can transmit data about their usage, status, or environment thereby creating a digital entity of the product itself. This digital entity provides the customer with easily accessible and understandable data about the state of the product that can be used to plan production. This digital layer will now represent a new regular revenue stream and if done right will work as a guarding fence preventing the customer from changing vendor. Vestas has done particularly good in this area and now has higher revenue from its support business than from new sales of wind turbines.
Sensor as a service: Data itself is the key resource and primary currency that is produced from the IoT-product. Shared and traded within the IoT ecosystem. This is a debated and highly hyped business model. It taps into the “data is the new oil” mantra that was/is pushed by many tech companies and management consultancies. Truth is though, that it is hard to find a business model where a company can allow to sell data to third parties that itself or its customers are generating. A good example is though Weather Underground that aggregates data from weather stations from around the world and sell this data to third party companies.
Glaze Business Innovation and Development Framework comprises both the process of identifying the most promising business cases, developing prototypes and how to scale the technologies and the supporting business within enterprises.
Partner Flemming von Holck, firstname.lastname@example.org, +45 30 66 30 61