Stress-testing products as they are designed and developed, before the potential for costly errors and rework, has long been standard practice for businesses. It was once achieved through a physical prototype, but then digital twins emerged. As digital representations of real-world entities, digital twins are a more efficient, cost-effective, and less risky, virtual solution.
Now the technology has undergone another wave of evolution with enterprises creating a virtual replica of their business processes so they can put them through the same rigorous inspection and optimization. This development is a game-changer for digital transformation and operational efficiency.
Let’s explore how digital twins have evolved, as well as the different ways businesses are using them to drive tangible value across their top, bottom, and green lines.
Digital twin technologies began life in manufacturing. The digital representation of a physical object, product, or component has allowed manufacturers and product developers to assess the suitability of designs and any areas for optimization, as well as gauge resource demands and construction requirements. This can all happen before production begins, but even after production is underway digital twins can be used to improve the manufacturing process. They can even be used to decide what to do with products when they reach the end of their lifecycle.
Digital twins have been used at breathtaking scale in the construction industry. Entire rooms and units can be prefabricated virtually to evaluate asset performance and how each physical counterpart fits together, minimizing rework when construction begins. Real-time sensor data from the physical counterpart means an asset twin can be used for running analytics and monitoring throughout the building’s lifecycle.
Digital twins are also used extensively in the life sciences and pharmaceutical industries. By simulating biological processes within the human body, they support medical research and the development and testing of new treatments.
The virtual model created by digital twins enables teams to check briefs are fulfilled and products are fit for purpose. Digital twin technology can be used to understand impacts and dependencies across departments and processes, from procuring different materials to delivering to the customer. And there are green-line benefits too, as virtual twins can simulate and compare the outcomes of using different materials and production processes on sustainability KPIs.
Digital twin technology can be applied to more than just a physical asset. Businesses are using process mining to construct a digital twin model of the processes that support their entire organization, using tasks, activities, and transactions drawn from system data (in much the same way a physical digital twin uses sensor data).
This process digital twin, or Digital Twin of an Organization, is a living, breathing virtual replica, fed with real-time data, that businesses can use to explore and scrutinize processes at a granular and high-level view. Everything from bottlenecks to duplicated processes and disconnects can be inspected, diagnosed, and triaged.
Digital twins can level up predictive analytics to help take your business from reactive to proactive. The technology enhances supply chain resilience, for example, by lowering risk through a greater ability to model scenarios such as disruption, stock-outs, and predictive maintenance. These improvements also benefit customer experience with more reliable service levels and consistent outcomes.
Delving deeper, the clear, forensically-detailed virtual representation of your processes that digital twins provide can unlock value in the key revenue-driving functions.
Gain visibility into payment blocks to prevent late payments and consequent delays to supplier deliveries.
Understand where payment delays are resulting in penalties or preventing cash discounts being fully utilized.
Investigate how payment term mismatches are creeping into PO processes, and where blindspots are masking optimal payment terms.
Improve vendor relationships by pinpointing delays and bottlenecks stalling efficient remittance processes.
Read: What is Accounts Payable? The process, business objectives and KPIs that matter
Identify and model opportunities to prioritize collections earlier in the process, maximizing dunning efforts, timely payments, and cash flow.
See where invoices are typically lost or duplicated in your AR and wider processes.
Streamline credit review and dispute processes by bringing to light unnecessary steps in escalation and approval flows.
Read: What is Accounts Receivable? The process, KPIs and metrics that matter
Detect and correct upstream and downstream order errors, such as improper shipping labels or erroneous addresses and prices, to slash cycle time.
Improve processing and on-time, in full (OTIF) delivery by spotting unnecessary delivery, credit, and billing blocks.
Investigate opportunities to automate many of the manual order management activities, such as inventory updates, generating shipping labels, and tracking fulfillment.
See how reverse logistics run and interact with the rest of your order management processes, to reduce clashes and returns getting delayed or lost.
Read: 7 Ways to Improve Your Delivery Performance with Celonis
Diagnose why discrepancies in purchase requisition (PR) fields are happening.
Eliminate free text orders by making it easier to analyze the root cause of PRs lacking catalog references, so they can be correctly linked to an item and stop slowing down processing cycle time.
Gain a clear picture of supplier lead times, and any bottlenecks, so you can take action to prevent impacts to your business further down the line, including exploring alternative suppliers.
Track emissions sources and duplicated processes impacting sustainability KPIs, as well as vendors not complying with your ESG requirements.
Uncover how excess stock is being purchased to lower operating costs.
Read: What is Procurement? The process and KPIs that matter
Despite such wide and varied use cases, not all businesses are yet maximizing the digital twin opportunity. Research found only 8% of senior decision makers in the life sciences industry understand the importance of digital twins for process optimization.
More broadly, HFS Research – in partnership with IBM and Celonis – discovered less than a fifth (17%) of businesses are using digital process twins across multiple departments.
Businesses further along the path to process excellence, meanwhile, are using digital twin technology to gain unrivaled end-to-end process visibility and transparency.
The Celonis Process Intelligence Graph builds a system-agnostic digital twin of a business and combines it with the business context in which the organization operates. It shows how the business is running, where and how things could run better, and how teams can capture the value hiding within the business.
Learn more about how digital twins and Process Intelligence can match your ambition and drive measurable value, fast.