How to introduce our smart, connected products and solutions to their customers, be they external or internal, B2B or B2C? For solutions, this usually involves a dedicated rollout process, while for products the Go-to-Market is important.
Smart, Connected Solutions: Rollout
Effective management of the rollout process for AIoT-enabled solutions is a key success criterion. How exactly this looks like will depend on many factors: is this for one site or one asset only, or is this for multiple sites with multiple assets? Is this for internal customers only, or for external customers? Will this require customizations for individual target sites?
We have already discussed several different examples representing different scenarios, e.g.,
- Single site, single asset: monitoring of particle collisions at the Large Hadron Collider
- Multi site, multi asset: Rollout of a predictive maintenance solution for escalators in train stations
- Multi site, multi asset with customization: Rollout of a predictive maintenance solution for different users of hydraulic components (requires customization of the AI for each customer)
The following describes a generalized process that could be suitable, for example, for a multi site, multi asset situation.
During rollout preparation, a portfolio of all relevant assets and sites (e.g., train stations and escalators) must be created. This portfolio must be evaluated and prioritized. Based on this assessment, a project plan including rollout schedule and resource management must be created.
Rollout execution will then require a generalized plan which can be applied to each individual site. In this case, it includes site preparation (e.g., aligning with the train station's facility management, preparing for deployment), asset preparation (e.g., cordoning off the escalators, enabling access to the required internal parts), solution deployment (e.g., deploying an IoT gateway and an ultrasound sensor), testing the solution (e.g., simulating a problem with the escalator and checking if this is recognized by the solution), and finally transferring everything to operations.
Back to the portfolio level, the next area is performance and control. For example, this can monitor the rollout of the escalator monitoring solution and suggest corrections in case of inefficiencies. Finally, if this is a fixed set of sites/assets, the rollout project needs to be closed properly. This will include preparing measures for new assets being onboarded. For example, new escalators acquired in the future should also be equipped with the monitoring solutions.
Smart, connected products: Go-to-Market
For the Digital OEM, a strong focus on the commercialization of new digital/physical offerings is key. For an incumbent, this needs to start with a look at existing sales and marketing processes, as well as the skills and networks of the existing team. How can this be applied to successfully market and sell new, digital/physical offering? And which changes might be required?
For digital/physical offerings, we often need a much closer alignment between the product development and the marketing/sales organization, since both marketing and sales functions need to be digital and built directly into the product. This is particularly true for any kind of digital subscription services or digitally managed physical-feature-on-demand offerings.
If the new offerings include some kind of fleet/asset/feature-as-a-service element, it will be important that the sales organization be adopted accordingly. This will include many aspects, including sales commissions and incentives, sales processes, and customer engagement.
An interesting on-demand example is seat-heating-on-demand, as shown in the figure following. Traditionally, seat heating is sold as an add-on during the car sales process. Only if it is configured in the beginning will the car be equipped with it in the factory. The on-demand version assumes that all cars are equipped with the seat heating functionality. Customers can then use the car app to activate the feature on demand. The pricing for the feature could be dynamic, determined by an AI. In this example, responsibility for selling this feature would move from the sales rep, who is selling the car in the first place, to the team, which is responsible for demand generation for digital features. Another aspect is the change from a traditional, one-time payment via bank transfer to a subscription model based on micropayments.
Continuously Improve Commercialization
One cannot expect to get the product/customer fit from the very beginning. So a clear focus on the continuous improvement of all relevant aspects of commercialization is required. In the example shown here, three key KPIs have been identified: number of signups, how many customers are actively using the freemium services, and how many are paying for premium services. There will always be a gap between these three KPIs, but of course the challenge is to drive them all up and minimize the gap. In order to do this, one will constantly have to monitor the customers along their customer journey. AIoT-generated insights can play a key role here, in addition to the standard digital analytics channels. The learning from the analysis must be applied for the continuous improvement of the offering and its commercialization: marketing and sales processes and campaigns can be adapted almost in real-time, especially if they are driven through digital channels. The digital product features can be adapted usually in a relatively short term, e.g., using Over-the-Air capabilities. Finally, even the physical product can be improved from generation to generation using the insights from the analysis of the customer journey. Managing this continuous improvement process effectively will be key to successfully scaling up an AIoT-enabled, digital/physical business.