Digital twin in retail: the art of the possible

Today we will shed light on the possible use cases of the operations digital twin in retail industry.

What is a digital twin?

A Digital twin has a broad definition; it is a virtual representation of physical objects, processes, or a combination of the two. That representation, connected to the data layer, reflects the real-time state of the object and/or process and provides the ability to simulate different scenarios predicting the future state.

The near real-time connectivity between the physical and digital worlds transforms how we monitor, control, and manage equipment, systems, and processes, shifting from a reactive to a proactive paradigm. Combining a simulation model, real-time data flow, and machine learning, a digital twin helps managers make better decisions. It can spot critical signals of process execution, customer behavior, and externalities impact, not to mention its ability to predict future scenarios. In the retail industry, the adoption of such a powerful technology has only just begun.

Store digital twin

At the moment, most examples of implementation of digital twins for the retail field are store digital twins, the virtual replicas of the physical store itself. Therefore, most of the cases are focused on store operations - local space utilization, product placement, customer journey management, and the paths robots might follow down store aisles for inventory. You can read more about such examples from the Lowe's case.

Retail industry trends

At the same time, for the last two years, the retail industry incumbents' challenges have been tangent to the supply chain and stock management disruption caused by COVID-19. These disruptions resulted in four out of five (82%) retailers changing their approach to supply chain management because of systemic changes [1]: 

• Fluctuation of the delivery lead time caused by supply chain congestion.

• Localization of stock due to demand fluctuation entails goods shortage, making just-in-time obsolete.   

• Visibility and accuracy of inventory management to balance stock flow versus stockpiling 

• Profit maximizing stock optimization due to demand fluctuation  

• Supply chain resilience in order to protect against disruption 

Operations digital twin

An operations digital twin is a simulation model replicating operations structure along with various assets, including those in production and supply, finishing and warehousing, logistics, and others facilitating operations execution. Therefore, an operations digital twin identifies areas of operations volatility, uncertainty, and risk, as well as opportunities for optimization, alleviating contemporary retail operational challenges over different impact horizons and positively affecting companies’ financial performance, for example, a 5% reduction in sustainable inventory, a 10% reduction in capital expenditures, and EBITDA growth of 1 to 3 percentage points. [2]

Long-term horizon cases

Over the long-term horizon, a digital twin of the supply chain can better inform for improved investment decisions and reveal an optimal supply chain structure given company objectives.

• A digital twin of the entire supply chain system can unfold bottlenecks, capacity constraints, and other system-level challenges affecting a company’s performance. Such insights will help companies allocate capital to improve the global performance of the supply chain versus the local one, which often undermines the company’s performance despite improving the performance of a specific function or step in the supply chain. 
• A company can simulate various scenarios with different supply chain configurations and structures to find the optimal one satisfying business performance criteria. Of course, these models can be run in different operating environments, including the new normal with high volatility of delivery lead time and demand.
• Management can explore various mitigation strategies to protect supply chain performance from various disruptions.

Mid-term horizon cases

The mid-term horizon cases primarily concern sales and inventory planning for upcoming seasons that retail companies can benefit from. 

• With a supply chain digital twin, a company can explore the performance of various planning decisions and order sourcing rules, simulating how they perform with different customer demands and the existing supply chain configuration with a specific costs structure and constraints among distribution, warehousing, point of sales, etc.
• Through scenario simulation with different sourcing rules, pricing strategies, and cost structures ( fuel, staffing, delivery, etc.), management can find the optimal purchase plan tailored to the specific objective of profit and inventory turnover.  

Short-term horizon cases

It might be reasonable to highlight the following cases from a short-term perspective. A particular store management can:

• Find new fulfillment opportunities if a customer's demand changes or can predict the performance of a particular item given the customer profile.
• Understand the required inventory level given a specific disruption, like a weather pattern.

We outlined the cases that are on the surface and obvious, but there is much more that retail can do with operations digital twin technology. The retail industry is just beginning the journey of adopting digital twin technology. The potential impact on the industry can and will be huge. We envision the VSOptima, operations digital twin platform, accelerates the adoption of such a powerful concept and makes retail incumbents more efficient, eventually benefiting their customers.