Blog: show me the money

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.

Initial steps

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

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.

More information:

Partner Flemming von Holck, flemming.von.holck@glaze.dk, +45 30 66 30 61

Positioning technologies currently applied across industries:

Global Navigational Satellite System: Outdoor positioning requires line-of-sight to satellites, e.g. GPS: the tracking device calculates its position from 4 satellites’ timing signals then transmits to receiving network
–    via local data network, e.g. wifi, proprietary Wide Area Network
–    via public/global data network, e.g. 3G/4G

Active RFID: A local wireless positioning infrastructure built on premises indoor or outdoor calculates the position based on Time of Flight from emitted signal & ID from the tracking device to at least 3 receivers or when passing through a portal. The network is operating in frequency areas such as 2.4 GHz WiFi, 868 MHz, 3.7 GHz (UWB – Ultra Wide Band), the former integrating with existing data network, the latter promising an impressive 0.3 m accuracy. Tracking devices are battery powered.

Passive RFID: Proximity tracking devices are passive tags detected and identified by a reader within close range. Example: Price tags with built-in RFID will set off an alarm if leaving the store. Numerous proprietary systems are on the market. NFC (Near Field Communications) signifies a system where the reader performs the identification by almost touching the tag.

Beacons: Bluetooth Low Energy (BLE) signals sent from a fixed position to a mobile device, which then roughly calculates its proximity based on the fading of the signal strength. For robotic vacuum cleaners an infrared light beacon can be used to guide the vehicle towards the charging station.

Dead Reckoning: Measure via incremental counting of driving wheels’ rotation and steering wheel’s angle. Small variations in sizes of wheel or slip of the surface may introduce an accumulated error, hence this method is often combined with other systems for obtaining an exact re-positioning reset.

Scan and draw map: Laser beam reflections are measured and used for calculating the perimeter of a room and objects. Used for instance when positioning fork-lifts in storage facilities.

Visual recognition: The most advanced degree of vision is required in fully autonomous vehicles using Laser/Radar (Lidar) for recognition of all kinds of object and obstructions. A much simpler method can be used for calculating a position indoor tracking printed 2D barcodes placed at regular intervals in a matrix across the ceiling. An upwards facing camera identifies each pattern and the skewed projection of the viewed angle.

Inertia: A relative movement detection likewise classical gyroscopes in aircrafts now miniaturised to be contained on a chip. From a known starting position and velocity this method measures acceleration as well as rotation in all 3 dimensions which describes any change in movement.

Magnetic field: a digital compass (on chip) can identify the orientation provided no other magnetic signals are causing distortion.

Mix and Improve: Multiple of the listed technologies supplement each other, well-proven or novel, each contributing to precision and robustness of the system. Set a fixpoint via portals or a visual reference to reset dead reckoning & relative movement; supplement satellite signal with known fixpoint: “real time kinematics” refines GPS accuracy to mere centimetres; combine Dead Reckoning and visual recognition of 2D barcodes in the ceiling.

LoRaWAN: A low power wide area network with wide reach. An open standard that runs at unlicensed frequencies, where you establish a network with gateways.

Sigfox: A low power wide area network reminiscent of LoRa. Offered in Denmark by IoT Danmark, which operates the nationwide network that integrates seamlessly to other national Sigfox networks in the world.

NFC: Used especially for wireless cash payments.

Zigbee: Used especially for home automation in smart homes, for example. lighting control.

NB-IoT: Telecommunications companies’ IoT standard. A low-frequency version of the LTE network.

2-3-4G Network: Millions of devices are connected to a small SIM card, which runs primarily over 2G, but also 3G and 4G.

Wifi: The most established standard, especially used for short-range networks, for example. in production facilities.

CATM1: A low power wide area network, especially used in the United States.

Glaze IoT Cloud Project Process

Beacon Tower is Glaze’s Industrial IoT Cloud Platform that can act as either a stepping stone (Platform-as-a-Service, PaaS) or as an out-of-the-box solution (Software-as-a-Service, SaaS) for collection of IoT-data.

Beacon Tower resides in Microsoft Azure and is designed as a customisable and cost-effective IIoT Cloud Platform that helps simplify deploying, managing, operating, and capturing insights from internet-of things (IoT)-enabled devices. Our customers have the full ownership of their data.

When running it as a PaaS we utilise the design and can run it on our customers’ Azure tenant and customise it fully to their requirements.

Beacon Tower connects to all sensors, PLC, DCS, SCADA, ERP, Historians and MES to gain maximum automation flexibility and ​prevent vendor lock-in.

For more information visit www.beacontower.io or read the PDF.

Edge Computing Categories and Questions

Device:
o Sensors
o Internet connectivity
o Battery consumption
o Field Gateway
o Communication protocols (HTTP, AMQP, MQTT, Gateway)
o Format of the telegrams sent to the cloud (JSON, Avro, etc.)

Data:
o Number of devices & number of signals
o Amount of data to transfer per day
– Event-based or batched or mix
– Transfer rate (every second, minute, hour)
o Device timestamps
– Synchronized timestamps with cloud or not
– Local buffering on device, late and/or repeated data
o Any time-critical notifications / alarms
– Latency expectations for non-time critical data
– Alarms generated by device and/or by cloud platform
o Cloud-to-device messages & commands
o Analytics
– Results from time-series data / Streaming analytics
– Analytics workflows on data, machine learning etc.
– Edge analytics / intelligence

Cost expectations:
o Retention periods (for reporting purposes)
o Aggregation of data, possibilities for cost saving

External integrations:
o Reference data / online data

Administration, rights and access:
o Requirements for multi-tenancy (segregated owners)
o Owners/tenants and operators/technicians
o Administrating access to data, auditing use
o API management, consumption of data, 3rd party integrators

Operation:
o KPI measurements for device
o KPI measurements for cloud platform
o Requirements on operators and SLA’s

User-interfaces and functions:
o Operators/technicians
o Customers/end-users

Glaze Business Innovation and Development Framework (BIDF)

1. Strategy

Creating an IoT Strategy that aligns with the existing company strategy and/or points out any discrepancies that needs to be addressed. The IoT Strategy should pinpoint type of IoT opportunities that should be sought and how they can support the Company delivering on their overall strategies.

2. Ideation

The Ideation phase is an innovative and creative phase where we identify the IoT opportunities within the company. This is done by using existing assets, industry expertise, industry analysis, strategy and IoT expertise to find opportunities for IoT endeavors. This is done in an structured but open-minded and creative setting.

3. Refinement

In Refinement the opportunities are detailed, prioritized and evaluated in a series of steps with the goal of finding a short list of initiatives the company want to pursue. These steps takes strategy, competence, risk level, customer maturity etc into account during prioritization.

4. Valuation

The short list of opportunities are detailed even further and business cases are created for each of them. This will lead to a decision which opportunity to pursue further.

Moving on from the Business Innovation phases to Development activities we focus on taking the minimum possible risk of building the wrong solution by using agile development practices.

5. Exploration

Proof of Concepts carried out in this phase in order to map out technology as well as user-oriented risks. This also refines the budget and thus valuation and business case. Also giving valuable input to baseline system architecture and eco system involvement.

6. Planning

Moving to Planning phase, the most promising business case has been selected and now it is time to plan the Minimal Viable Product (MVP), in terms of timeline, resources and detailed design.

7. Foundation

Implementing the baseline architecture, toolchains and most critical points of the project.

8. Development

Full MVP is developed using these three principles: Start small, don’t over-engineer; Agile software development – late changes welcomed; Continuous delivery – every change is immediately visible.

9. Operations

Operations in an IoT-project is more than just keeping the product alive. It is life-long updates and continous sharpening of features and business model, meaning new ideas are fed back in the Innovation and Development Framework.

Heat map example on a typical business case: