Part 1 in a 5-part series on “Design-to-Operate with the Digital Supply Chain.”
This blog kicks off a 5-part series on the design-to-operate (D2O) lifecycle. Each blog will take up one phase of the lifecycle, spanning design, planning, manufacturing, delivery, and operations. Our goal is to show how integrating processes and sharing insights across all of these phases can help manufacturers drive efficiencies, reduce costs, and deliver better customer experiences. Our focus here is on the design phase.
It’s cliché because it’s true: Today’s customers are empowered by information and technology to get what they want, when they want it. With information at their fingertips and the ability to share it via social media, customers are in a position of power. Companies seeking to survive and thrive in this environment are in a position of meeting customer demands.
What exactly are these demands? Increasingly, what customers look for are positive experiences. Whether you operate in B2C or B2B markets, if you’re difficult to work with, customers will go elsewhere. What customers want is “easy.”
But making things easy for customers can be difficult – especially when critical phases of the product lifecycle are siloed and disjointed. To address this challenge, companies seek to integrate the end-to-end digital supply chain across the phases of the D2O product lifecycle: design, planning, manufacturing, delivery, and operation.
The design phase (aka engineering, product development, or R&D) plays a critical when it comes to translating requirements into innovative products that amaze customers and make their lives easier. Sometimes the design team focuses on improving existing products or reducing costs. Other times, it brings entirely new formulations and designs to life with speed and accuracy.
In either case, design teams that work in silos put themselves at a disadvantage. Increasingly, designers and engineers are finding that the exchange of information and insight from other phases of the product lifecycle helps to improve not only product design but the entire customer experience.
Let’s run through a few examples:
- Planning: The planning phase takes in demand signals from consumers. With integration into design, planners can efficiently communicate spikes and troughs in demand – with insight, perhaps, on how the design of the product is impacting this demand. As final design plans solidify, the design team will want to connect with the planning team to ensure that the best materials are available. If not, the design team needs to make adjustments that, in turn, will impact MRP requirements, sourcing, inventory levels, purchase orders, and more.
- Manufacturing: Design choices impact manufacturability. Thus, design and manufacturing need to be in constant communication to determine the feasibility of meeting expectations implied in the product design. Based on decisions made, the manufacturing team needs to set up its lines and prepare for any configuration variabilities. Manufacturing will also want to report back to design on any design flaws that impede the production process.
- Delivery: Failure to deliver on time can ruin an otherwise pleasant customer experience – which is why fine-tuned logistics play such an important role in meeting customer expectations. Say the final product is a large piece of capital equipment. Is it designed to be delivered in pieces and assembled on site? Does the final product require refrigeration or some other environmental requirements? Considerations like these should be communicated to logistics partners from the earliest stages, making collaboration with design teams critical.
- Operations: How a product performs once it’s with the customer can provide important details back to design about how customers use the product and how it holds up under certain conditions. If the product is designed with sensors that transmit data on product status and health, design teams can run analyses to make product improvements. How often are certain parts breaking down? Is the product designed with tolerances appropriate for actual usage? Answers to such questions can help design teams better meet customer expectations and deliver better experiences.
A little help from digital twins
In these examples, themes of connectedness, collaboration, and insight predominate – all of which can be facilitated by digital twin technology.
Most products today are designed with the help of computer-aided design (CAD) tools. CAD plans – which, of course, are natively digital – can be used to create a digital mirror image for every product manufactured. This digital twin can be maintained throughout all product phases. The result is a single source of truth – a unique and always up-to-date digital blueprint for any particular product or asset as it has been designed, made, delivered, and operated over time.
The digital twin, then, becomes a tool that facilitates connectedness, collaboration, and insight across the D2O lifecycle. Here are some examples:
- Enhanced customer collaboration: With a digital twin, you can show customers the product design as it exists today – and then quickly run simulations that demonstrate how changes to that design can impact the product and the customer. This reduces risk for you and the customer alike.
- Faster innovation and personalization: Based on changes made to the digital twin, you can quickly generate a new bill of materials (BOM) that manufacturing can use to drive production. With a single source of product truth, you can speed the pace of innovation, meet the challenges of variable configuration, and deliver highly personalized products while maintaining profitability.
- Improved maintenance: For every product or asset in the field, digital twin technology can be used to generate animated video instructions that guide technicians through the steps required for repair or maintenance. Training is delivered on demand – helping you to streamline maintenance operations.
- Insight at scale: If you string all of your digital twins together into a network, you can collect product data on a much larger scale. By subjecting this data to machine learning algorithms, you can then detect patterns regarding usage, wear, and performance that can yield new insights for continuous improvement.
As explained above, fundamental decisions made in the design phase can impact all other phases of the product lifecycle. At the same time, information from these other phases can act as important inputs for consideration by product engineers. And with digital twin technology, information can flow across all phases of the D2O product lifecycle with greater ease – which can lead to more sustainable products and better customer experiences.
Stay tuned for the next installment in this series, where we focus on the planning phase. In the meantime, if you need more information on the D2O product lifecycle, have a look at the new IDC report, “Design as a Critical Element of Digital Supply Chain.”