Are you ready to own the product lifecycle?
Operational data from smart products can unlock opportunities to delight your customers, improve your future designs and fend off competitive threats. To capitalise on those opportunities, you need an agile data platform, says Graham McCall, vice president operations UK, Aras.
The evolution of connected products is changing the relationship between equipment OEMs and their customers. For the first time, manufacturers can gain detailed, often real-time, visibility into the performance of their products in the field. With the agreement of their customers, they can even control, modify or enhance those products remotely.
Connectivity offers multiple sources of significant value for OEMs. It allows them to offer new and better services to their customers, from remote diagnostics and repair to ongoing improvements to product performance. Product development and business strategy teams can use new information and insights to improve future offerings or identify unmet customer needs. And closer, more collaborative relationships between OEMs and customers boost loyalty and help to keep competitors at bay.
Data, insight, action
The ability to use better information about the operational lifecycle requires more than just unstructured data flowing back from products in the field. To interpret such data, companies must understand the precise configurations of their products and the operating conditions they experience. This calls for the coordination of multiple sources of information from across the end-to-end product lifecycle, and the communication of that information to multiple internal and external stakeholders.
Therefore, every smart product needs its own digital thread of product data, capable of delivering complete, accurate, up-to-date, and actionable information to teams who need it, and coordinating their responses to that information. And once the product is in the field, the addition of configuration, service and operational data adds additional complexity.
A digital twin is a virtual representation of a physical asset and requires configuration management. To connect that digital twin to and from other parts of the organisation, you would use a digital thread to get the BOM to the digital twin or create traceability back to the requirements. It’s important to note that a complete digital thread does not equal a digital twin.
Time for a digital transformation
Plenty of companies are struggling to integrate the different processes and data sources required for today’s products, with mechanical, electronic and software components all requiring different tools, different workflows and different expertise. Tomorrow’s products will increasingly involve cloud infrastructure, artificial intelligence and interactions between multiple systems, adding further complexity to the challenge.
Organisations seeking to own the complete lifecycle of product information can’t rely on old technologies. When data and processes are locked in by the applications that manage them, the company’s available insights and actions are limited to the capabilities of the tools they reside in. Inflexible tools yield inflexible data, processes, and strategies.
Today, there is plenty of evidence that, while companies understand the need to for a digital transformation of the entire product lifecycle, most are struggling to turn the ambition into reality. In a 2018 global survey of 1,733 business executives conducted by McKinsey, just 14% said their digital transformation efforts have sustained performance improvements, while only 3% report complete success at sustaining change.
A digital transformation is a complex endeavour, with many moving parts. It requires people to learn new approaches and adopt new ways of working. It forces organisations to make difficult decisions about how, when, where and with whom they share data, balancing the benefits of openness with the need to maintain security and protect intellectual property.
Building strategic agility
Above all, however, companies need platforms and systems that enable them to connect, share and manage data in new and constantly evolving ways. That’s something that most legacy product development tools simply weren’t designed to do. It’s no surprise that dealing with legacy technology is one of the most common issues in digital transformations.
Strategic agility—the means to learn from and use the data in new ways—relies on improved flexibility: the opportunity to add new types of data, new stakeholders, new technology domains, and new tools, to continually improve the processes that deliver and manage products. It isn’t just product data that will be subject to continual change in this environment, companies will also need the ability to evolve and adapt the data platform itself.
The agile data platform
As any organisation thinks about the way it will manage product related data in the future, we believe that strategic agility should be top of mind. Can the proposed data platform create and manage the complex connections required throughout the end-to-end product lifecycle—including changes downstream to product data, and upstream in systems design? This helps to ensure that requirements are met, and that new requirements are captured and designed-in to improve the customer experience.
Can the platform manage the tool integrations and workflows across various teams that contribute to the digital thread of product data―enabling traceability and ensuring changes are communicated across different domains and authoring tools.
Can the platform manage the digital twins of every product in the field to provide context for their recorded data? This is essential to understanding if requirements were met, and providing the insights that will enable better service, added value for customers and inspiration for future product improvements.
Finally, and most fundamentally, how quickly and easily can the organisation modify its platform to accommodate new requirements? Is the system open to integration with any new tool, or tied to the offerings of a specific vendor? Can you alter workflows, connections and data models without incurring huge development costs and complex validation processes?
In a connected world, designing and building great products will no longer be enough. To delight their customers and outpace the competitors, companies will need to own the entire product lifecycle. That will be a fundamental shift for many companies, requiring them to modify their processes, tools and business models. For a business to sustain transformation year over year—including the next technology and service innovations that haven’t even been dreamed of yet—information and actions must be managed on a platform that can continually be adapted, upgraded, and evolved to meet the company’s ever-changing strategic needs.