As part of my responsibilities at SAP, I spend a lot of time talking with companies all over the world about product lifecycle management (PLM). Here’s something I’ve noticed: Most companies see PLM almost exclusively as a function of design and engineering.
This is too bad because such a narrow outlook on PLM leaves a lot of opportunity on the table. Let me explain.
Today’s economy is an experience economy where customers evaluate your company based on the overall experience you deliver. Are you easy to work with or not? Do you provide prompt service? Do you make payments a hassle or a breeze? If you want to differentiate yourself in a crowded market, the experience you deliver is what matters most.
A key aspect of the customer experience is the product experience – which is where PLM (with an emphasis on the “L”) comes into play. When PLM is narrowly focused on R&D productivity and the efficiency of design teams, the opportunity lost is the opportunity to focus like a laser on customer wants and needs. But when PLM encompasses the full product lifecycle, opportunities abound.
Closed-loop engineering and the voice of the customer
Think of the product lifecycle less as a straight line and more as a loop. A good place to start is with the demand signal – because after all, whatever you make, you need to know that customers want it.
Armed with a sense of demand, you then design and develop the product. Next, the product is released further down into the supply chain – where it is made and delivered. This is followed by the operations phase – where the product is monitored or maintained. Information from the operations phases – such as machine data – can then be fed back to engineering to inform product design choices moving forward.
This process is sometimes known as closed-loop engineering. The critical idea is one of information feedback. The starting point – where the demand signal is detected – is often known as the “voice of the customer.” By listening closely to the voice of the customer, engineering can start the design and development phase with an understanding of what the customer actually wants.
Do customers want a specific feature? Lower price? Higher quality? Improved usability? Better post-sale service? Whatever the case, the product needs to be designed with customer requirements in mind. And the only way to understand customer requirements is to collect the data.
The digital thread
There are many ways to collect requirements data: surveys and focus groups, customer service logs, or maybe astute salespeople who communicate back to headquarters. One of the most promising methods, however, is to collect data directly from the product or asset itself.
It is now possible to collect this data – even at scale – using IoT sensors that communicate a wealth of information on asset state and performance. The idea is to tap into the “digital thread” associated with an asset throughout its lifecycle to help improve the overall customer experience.
In many companies, the digital thread begins with a model of the system or product – leading, eventually, to CAD assemblies and drawings produced by design teams. These drawings include a bill of materials (BOM) that can be used to model the asset. While some companies use these models to generate digital twins (full-blown 3D representations of the physical asset), other companies simply track the relevant data. Whatever the case, access to the digital thread enables you to now manage the product lifecycle much more effectively.
The power of visibility and insight
Information from the digital thread can make all the difference in the world. One advantage is more effective coordination between engineering and manufacturing. When it comes time to hand off the designed product to the manufacturing team, the digital thread supports a single source of truth that eliminates confusion and avoids production bottlenecks. The same information in the digital thread can also extend further downstream into logistics to help speed delivery.
But when it comes to the customer experience, it’s the operations phase that delivers most. Today, for assets in the field, you can track everything from temperature, moisture, and vibration to performance, uptime, and usage modes. Based on this data, you can also run machine learning algorithms to uncover insights about how your customers use your products – or even predict machine failure before it happens.
Such insights – enabled by holistic lifecycle tracking – are helping companies create new business models and up their service levels. Predictive maintenance and increased uptime are only the beginning. Leading companies are going a step further, using their PLM data to support product-as-a-service models.
Instead of selling HVAC machines, for example, you might offer temperature-controlled facilities as a service and bill your customers on something like a subscription model. You would still design, manufacture, deliver, and install the machines – only now it would be your responsibility to manage the machines as well to ensure uptime and performance per the details of service level agreements.
According to this model, you now have more incentive than ever to use your PLM data to streamline all facets of the end-to-end to process – which will help you deliver higher levels of service and drive down costs. The result is a better experience for your customers and ongoing, sustainable revenues for your company – all made possible with a proper approach to PLM.
Find out more from the IndustryWeek research into “Innovate for Success with Product Lifecycle Management.”