An action shot of a warehouse, with forklift trucks and people moving between huge racks of boxes on pallets, awaiting shipment.

How can seeing double make things clearer?

If you’re a fan of Science Fiction, then you’re probably already familiar with the concept of a ‘Digital Twin’, even if you’ve never heard the term. The idea of a machine mirroring reality has long been held as a concept of interest – from the real-life example of NASA operating simultaneous simulations of rocket launches, to cult movie ‘The Matrix’ capturing the imaginations of millions.

The reality, while far less heart stopping, is even more world changing. Technology has finally caught up with the idea and brought with it a world of applications for what is essentially the parallel operation of one scenario in two places. Today’s Digital Twins are not just simulations, they are very much enmeshed in the real world and feed on a feast on the data of technologies such as IoT, Cloud, Extended Realities, Deep Learning and Artificial Intelligence to create maximum impact with minimal risk. But let’s rewind a little and clarify how and what a Digital Twin might look like, how it might be used, and for what purpose. Imagine, for the sake of illustration, that you are a retailer. You have a warehouse and a logistics operation that serves multiple bricks and mortar stores. Your biggest challenge lies in getting products into as many customers’ hands as quickly as possible, while ensuring that they do so in the most cost-efficient way. How might Digital Twins fit into your key activities and help to achieve this goal?

Action for inventory: Monitor, analyse, streamline

Streamlining warehouse operations has traditionally been something of a task, but the ability to digitally visualise and manoeuvre the path of inventory in real-time is nothing short of game changing. Automated equipment and staffing levels can easily be adjusted to maximise picking time. Bottlenecks are detected and eased as they happen, and engineers can be deployed before machines become problematic, based on predictive usage data. Then factor in other complexities – such as achieving optimum operational efficiency while adhering to required standards of sanitisation and social distancing. The visuals already produced by existing on-site network cameras can be immediately analysed and used to create new and safer ways for employees to move around the space, showing the value of using live data in order to create an environment of advance planning and immediate reactive response.

Two smiling young women in t-shirts, jeans and white tennis shoes are in a shopping mall. They are carrying boutique-style shopping bags and looking in the window of shop.
Using data from sensors and visual sources, shopfronts and shop floors could be entirely redesigned for the optimum customer engagement.

Telematics for fleet: Send, receive, adjust

As the low latency of 5G continues to open up possibilities, a constant flow of information between fleet and management would prove invaluable for course-correcting, forecasting and keeping logistics costs to a minimum. Temperature sensitive shipments, such as vaccines or food can be monitored through sensors to ensure the perfect future conditions – and used to calculate the cost of maintaining those conditions across the fleet. The packing of lorries can be modelled to ensure maximum load for fuel efficiency and minimum impact on long-term wear and tear. Not to mention how the vehicle and driver are performing – are drivers taking their legally required breaks? How fast are they driving? What does the vehicle’s fuel consumption look like? Is there enough air in the tyres? All these things and more can affect eat into the margin of the products in transit and affect how quickly they reach customers. With this in mind, consider how valuable it would be to have enough data to factor logistics into your pricing with absolute accuracy. The same principles can be applied to other areas of transportation, even air freight.

Goods across the line: Observe, model, test

In-store is often the most visible and ‘magical’ way that Digital Twins can have an impact on the bottom line. Customer routes of travel, when, where and how they interact with goods, time of queueing, the performance of merchandising and store layout – all can be gathered using updated security technologies, such as electronic tags and network cameras. This data can then be layered with that from PoS terminals and self-checkouts, integrating with loyalty card and payment information. It can even take weather reports and other external factors into consideration. Customer modelling and strategy testing has never been easier, and as bold retailers look to Extended Realities as a way to encourage shoppers both in-store and online, they are effectively learning more about the activities of their consumer base outside of the limits of shop floor, app or website than was ever thought possible.

Mind blown? Welcome to a calculated world

All this progress doesn’t even take into account how a retail business might Digitally Twin itself in order to test scenarios of multiple financial decisions. Or their use in the design and manufacture of the very goods they sell to refine production, improve sustainability and increase speed to market. In fact, just about every aspect of a ‘real world’ execution in any industry can be simulated, modelled and tested using live data. A new Digital Twin consortium (with founding members Ansys, Dell Technologies, Lendlease and Microsoft) describes the technology as “virtual models of a process, product or service that allow for data analysis and system monitoring via simulations” and talks of an imminent “technology explosion” in the space. Adoption across enterprises, innovative new tech and the advent of Industry 5.0 is the perfect storm for the future of data and the Digital Twin. And too for human ingenuity, as we make complex and original decisions based on more – and more accurate – information than has ever been available before.

Written by Andreas Herrnboeck, European Business Development Manager

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