One company that's been thinking long and hard about the impact of connected products in these industries is global energy management and industrial automation giant Schneider Electric. I recently gained a fascinating glimpse of how its research and development teams are preparing the ground for a new generation of connected products and the associated business models. This is the responsibility of Twila Osborn, vice president of Information Process Organization (IPO) for R&D and Innovation Efficiency, who I met during ServiceMax's recent conference in Paris.
Osborn runs an initiative known as IPO 2020, which aims to put the foundation in place for the company to operate new IoT-enabled business models such as subscription-based contracts and digital field service. It is already running a proof-of-concept based on an IoT platform that not only connects to products in the field but also into other information systems across the company. These systems include product management, field service management and customer relationship management, she told me.
What we're really working on is connecting these backend systems so that we have this connected loop to enable some of these processes and business models.
Connecting to product data management (PDM) systems such as product lifecycle management and CAD systems has been particularly powerful, she said.
The ability to connect back into the PDM and get the product data, it now becomes this connected loop that we can close. Now we have to think differently about how we design to help those products to talk back to you.
In the proof of concept, a connected UPS (uninterruptible power supply) at a datacenter that develops a potential fault is able to autonomously open a case directly in the Salesforce service cloud application. The field engineer can then view a 3D diagram of the product that originates from the product management system.
We've got the opportunity to be predictive. You know when something is failing, you know what parts you need to take to site.
There's the option to have augmented reality, in which the engineer can view the product diagram as a 'digital twin' of the physical device, with data streamed from sensors inside the UPS system superimposed on the image. This means the engineer can have a good idea of what the issues might be before even opening up the cabinet.
Osborn and her colleagues are also working to close the loop from field service back into product design. So for example, the service engineer might suggest a missing feature that can then be delivered out to devices in the field as a firmware or software upgrade.
Collecting data from products in the field can also help to monitor performance metrics, which can not only be reported to customers tracking their own assets but is also useful for competitive analysis against data stored in the product management database.
Product designers can also analyze the 'digital twin' in the IoT cloud, for example running a heatmap analysis of a part that's overheating to understand what caused the problem and what the effects are.
It is the impact on product design that Osborn foresees as the most profound.
I think the asset talking back to us is going to change the way we design. It's like a change activity coming in. How do I take advantage of all this data coming back to me?
One important factor to consider is whether the right data is coming back. That means careful planning from the outset when defining the data that's going to be stored in the IoT cloud, she said.
One of the key things you have to do is concentrate on your master data architecture.
You've got to understand the ontology and really design it way out in front so that you can build it into your architecture.
That then flows through to how the connected products themselves are designed.
You can't just assume the product is going to deliver what you want from it. You have to take the marketing objectives you want to achieve in the product design.
If we don't have the characteristics and the attributes we can't build them in. If we don't think about R&D we won't design in these attributes that are needed for these new business models.
If the data definitions have been correctly planned, then it may even become possible to gather intelligence from the installed base and to analyze where opportunities may exist to sell additional products, she said.
If we do the data ontology we then will have the opportunity to look at the installed base. If our products know each other in the environment, there are new opportunities to upsell additional products and services. If you do it right, you'll have a competitive database of products. Then you can start to build your go-to-market strategy if you do it right.
What's really important, she said, is to be clear about the marketing objectives first as it is the business requirement that will dictate what the technology infrastructure must deliver. Then test as much as possible:
All the while you're constantly doing iterations — prototypes, simulations. If your prototypes and simulations and your real product all match you know you've got a stable, repeatable product.
As my diginomica colleague Derek Du Preez is fond of saying, there's no point in pursuing an Internet of Things strategy unless you're also developing a service-centric mindset rather than one that's product-focused. Schneider Electric certainly understands the need to transform to as-a-service business models and is clearly doing the groundwork to make sure it has the data and systems foundation in place to deliver that transformation.
Image credit: IoT concept with cup of coffee © Melpomene - Fotolia.com.
Disclosure: ServiceMax and Salesforce are a diginomica premier partners. ServiceMax funded my travel to its Paris event.