Introduction
When we talk about the digital twins, we’re usually talking about digital models or representations of real objects like machinery and parts that may be handled and changed over time. As they progress through their life cycles, these digital copies of actual objects adapt and capture data at the same time. They let organisations collect, analyse, acquire insights, and finally produce the final version by first testing and developing digital versions.
This is already standard practise in the aviation, automobile, and other industrial industries. However, there is a substantial distinction between a ‘digital twin’ in production and a ‘digital twin’ in consumer shopping. While a digital twin in the manufacturing or automation industries includes conducting simulations and what-if scenarios, digital twins of consumer items or “things” in retail use a different approach. Until recently, digital twins were not feasible. The idea of digital twins is becoming a reality thanks to secure, affordable, and widely available cloud technologies, much improved IoT, sensor, and data collection capabilities, and the digitization of common objects like autos.
The integration of many areas of our life, such as smart gadgets, smart cities, and smart homes, will drive digital twins even further in the future.
Digital twins in retail, unlike simulations in manufacturing, are more focused on tracking and tracing items, making them useful for logistic businesses and supply-chain managers. This data-driven digital twin information may be shared across stakeholders, organisations, teams, and even nations, and it can be deployed in several languages. It allows merchants and customers to keep track of items and the information associated with them as they are sourced, transported, purchased, utilised, or consumed.
Digital twins, like other forms of technology, force firms to reconsider the roles and responsibilities of human resources. Today’s proverb is “Technology will make things possible; talent will make them happen” – technology is a facilitator, not a replacement, and a manufacturer’s employees will need to learn how to utilise a variety of tools and rely on a variety of abilities. Hence, orkgroup goals/KPIs should be aligned via stakeholder analysis and participation, and with those identified, a company may better target the capabilities required to achieve. Gaps can be identified using external (or internal) techniques. Then devote resources to recruiting and upskilling current employees, such as through a qualifications programme with incentives linked with the company’s goals. External organisations and alliances might be relied upon for learning solutions or managed services, and a culture of constant learning is essential.
Although there are some changes to notice, these requirements are comparable for both control towers and strategic digital twins. At the planner/scheduler level, control towers rely on a wider base of end-users, whereas strategic digital twins are more precisely geared to managers, including product, supply chain, finance, and commercial directors. Control towers also necessitate people who are more focused on root cause investigation and remediation, whereas strategic digital twins facilitate executive decision-making.
The AR shopping learning curve
Even for habitual social media users, using social commerce is still a chore. For example, if Instagram users want to try out different lipstick shades or eyeshadows using the platform’s AR-powered makeover tool, they must first go to a participating brand’s profile or the “Buy on Instagram” tab of Instagram Shopping, find a product with the feature, and then click the “Try with the camera” button. The window of opportunity is widening as technology advances to allow for more immersive and integrated experiences. According to a poll performed by market research firm Bizrate Insights in October 2021, half of the American consumers have tried or are at least interested in utilising augmented reality (AR) or virtual reality (VR) when shopping. However, the perfect integration of AR technology with the purchase process is still required for commercial success.
Digital twins in the supply chain
By replicating all assets and relationships in a complicated supply chain, digital twins assist firms in addressing difficulties. It was explained in BCG’s paper “Conquering Complexity in Supply Chains with Digital Twins” how a corporation might use the insights to supplement decision-making across several planning horizons:
- Planning and executing short-term projects – Companies may use a digital twin to uncover execution risks early on, allowing them to mitigate rather than manage catastrophes. It allows the firm to decrease bottleneck asset idle time and enhance inventory positions.
- Sales and operations planning – By modeling the execution of a specific plan, emphasising risks and opportunities, and feeding the insights back into the planning process, the digital twin can improve sales and operations planning (S&OP). This enables the organisation to reduce losses caused by plan misalignment and system limits, as well as latent bottlenecks. The information also enables the organisation to better match maintenance and inventory build-ups to market demand.
- Longer-term planning – Understanding where the most important structural constraints are and how much extra capacity is required may help a firm enhance CapEx efficiency and optimise the entire supply chain system configuration.
Key Companies & Market Share Insights in Digital twins
Companies are investing in product R&D and process automation as a result of intense rivalry among major competitors to introduce improved and new goods. Furthermore, numerous car firms are implementing digital twin technology to boost consumer interaction by utilising interactive automobile dashboards on websites that allow buyers to modify automobiles at their leisure. This aids businesses in understanding consumer behaviour and modifying existing models.
Companies are producing customised goods in order to capitalise on new market possibilities and reach new clients. Dassault Systèmes, for example, established a cooperation with Renault Group in December 2021. The alliance aims to build programmes for new cars and other mobility services utilising Dassault Systemes’ 3DEXPERIENCE cloud platform. The technology would be used by Renault Group to manage virtual twins of its product variants. The following are some notable participants in the worldwide digital twin market:
- ABB
- AVEVA Group plc
- Siemens.
- Oracle Corporation.
- Cisco Systems
- IBM Corporation
- SAP
Conclusion
Organisations that are proactive and nimble will ultimately prevail. According to a recent LLamasoft retail research report, the most successful merchants are those who recognise and use technology such as digital twins, artificial intelligence, and machine learning early on – they are those who stay ahead of the curve in difficult times. According to a Gartner estimate published in 2019, at least half of big worldwide organisations will use AI, advanced analytics, and IoT in supply chain operations by 2023. Businesses must install the necessary enabling technologies to obtain insights into their supply chains and make them more flexible to adapt to quickly changing conditions if they are to survive and prosper in the new normal.”
