Ville: In a very similar way as on the business side, this area aggregates a long list of emerging technologies: IoT, cloud, edge computing, distributed ledger technology, digital contracts, artificial intelligence, machine learning, predictive analytics, PKI, secure elements, 5G and even augmented/virtual reality technology. It is probably due to this wide spectrum of business impacts and diverse technology landscape that I became fascinated by this opportunity in early 2019. My day job in Nordea is Head of Emerging Technology and my role in the Industry 4.0 team is to lead the initiative and make sure we seize this opportunity together with our customers. I am a technologist by background and have been working in the financial technology space for close to 18 years around the world, and it is a lot of fun to see so many technologies and solution areas from my past converge in this project.
Our current focus in the Industry 4.0 initiative is to initiate meaningful dialogues with customers, OEMs, technology vendors, integrators and other financial institutions. We’re keen to build a common understanding of what we want this future data-driven economy to look like.
How do you see the concept of Industry 4.0? Is it about technology or business models, or both?
Marina: Coming from the business side, the way I see it, the technology is already to some extent out there. Manufacturing equipment already has connected sensors. What corporates now need to realise improvements is business models that make the continuous payments actually work. We can look at subscription-based models in e-commerce as the first step in this direction and then move forward to machine-to-machine payments between two companies as the ultimate example. As an illustration, imagine a robot on a manufacturing floor that picks up screws from another robot which is owned by another company. Payments for the screws are made instantly between the two machines and settled to virtual accounts with pre-defined thresholds which are then being reflected to the companies' real bank accounts. The banks act as trusted partners and provide the legally binding contract between the companies. Or imagine instead the simple example of a consumer product, such as a vacuum cleaner, with a dynamic pay-per-use model. You could pay based on how many square meters you clean and how intense the cleaning is.
Ville: One of the key things we have learned throughout our journey is that this is not just another technology bubble, but in fact a paradigm shift in our customers’ business models. The move to pay-as-you-go models is happening across the entire value chain, and technology that makes it feasible (eg IoT, AI, 5G) has now reached a point where it also makes economic sense to deploy it. Once our customers start operating accurate digital representations of their entire business value chain by using sensory data, we as a bank need to ask ourselves: are we with our customers in this transformation, or do we expect them to build on or circumvent a transaction banking model that has not seen radical evolution for decades?
One of the related macro trends that has appeared in many of our industry dialogues is the changing landscape of original equipment manufacturer (OEM) businesses, where capital-intensive equipment sales have been slowing down and increasingly replaced by significant growth in services businesses. Pioneers like Rolls-Royce, with its “power by the hour” model developed in the 1960s, have already shown that there is high optimisation potential from integrating equipment sales and services directly at the OEM. This model typically guarantees the best performance and output from any production system, and increasing measurement accuracy with real time IoT data and ubiquitous broadband connectivity makes it possible to create extremely granular pay-as-you-go service packages. These can also incentivise sustainable and responsible day-to-day usage of the production system itself.
How would you describe the benefits of usage-based business models compared with traditional produce-and-sell models? Would there be benefits only for OEMs, or across supply chains, including for customers?
Marina: The benefit is to get a continuous payment stream from your product, determined by the data displaying how it is being used. The manufacturer will be able to get an overview of how the product is being used, and can increase uptime by predicting when repairs are needed. And increased uptime improves the users' cash flow. There is a difference between waiting 60 days to get a single original sales invoice fully paid, and getting continuous payments related to the usage. Another difference is which balance sheet the product resides in. This new model is not for all companies. Some will want to invoice and get paid the full amount after 60 days. But for others that already work with leasing models, a usage-based model can be an updated form of doing business. In this new model you can also add predictive maintenance and repairs to the offering, and you can get close to your customer over a long period of time. For supply chains, we are just starting to look into if there can be new forms of supply chain financing, which could unlock opportunities also for the suppliers to obtain some of the premium that the manufacturer obtains from pay-per-use or even pay-per-outcome models. For consumers, the benefits are easy to understand. With pay-per-use models, more people can afford to use the goods they want to use, and pay only according to their actual usage. This new affordable way also makes it possible for the manufacturer to get more customers!
Ville: Usage-based business models combined with sensory data could offer distinct benefits to all three parts of the value chain: the supply chain (raw materials and parts), manufacturing (factories) and operations (pay-as-you-go). The key theme across all these categories is working capital optimisation.
- Raw material and part suppliers can get paid in real time, as their products are used by the manufacturer (eg a robot picking up electronics components from a tower and paying for each component in real time)
- Factories could be filled with production robots that are operating under pay-per-use digital contracts; This could potentially free up incredible amounts of capital as OEMs could become value adding factory operators owning IPR to produce something rather than being burdened with the need to own vast amounts of commodity manufacturing equipment
- Equipment users/customers could benefit from lower upfront capital requirements and be incentivised towards more sustainable equipment usage.
The obvious question here is: On what balance sheet does all this capital sit if everyone operates under pay-per-use contracts? This is the exact question that led us to develop the digital contract model. We still have a lot of work to do and technical questions to answer, but in a situation where we can have secure and trusted metering of physical assets linked to legally binding contracts that trigger pre-authorised payment flows over a fixed time period, we can predict the risk of that pay-per-use contract very accurately and monitor its actual performance in real time. Predictable risk is two words that investors and other finance entities tend to like. A lot.