Hypermarket. Digital Twin. Use Case

**Hypermarket. Digital Twin. Use Case**

**Given:**

*   Software exists.

*   A general-purpose VR constructor.

1.  **VR as a helmet** is an *option*.

    *   The essence is the creation of interactive, immersive digital spaces.

2.  **Control via keyboard, mouse, hand tracking, manipulators** – *optional*.

3.  **Output to monitor, projector, VR helmet/glasses** – *optional*.

4.  **A helmet is not required** for operation.

5.  **No compile, build, deploy.**

6.  **Runtime editing.**

7.  **Runtime content import.**

8.  **Runtime scripting.**

**Problem:**

Replacing the physical infrastructure of a large hypermarket with a digital twin deployed on an existing VR constructor platform (featuring runtime editing, built-in CMS, integration, and management modules, as well as a module for generating 3D models from photographs). It is necessary to evaluate the structural changes, cost redistribution, and economic efficiency, taking into account the development of related technologies (logistics, automation) and changes in consumer behavior.

**Analysis. Initial Conditions:**

1.  The VR constructor platform exists and is acquired via license/rental. It includes:

    *   CMS, payment system, ERP, CRM, behavioral analytics integration modules (as plugins).

    *   A 3D model generation module from photographs.

    *   Data management and standalone operation tools.

    *   Built-in cybersecurity.

2.  3D product models are created by the platform itself or supplied by manufacturers.

3.  IT infrastructure is reduced to renting cloud servers (with auto-scaling) or deploying in-house ones; rendering can be performed on client devices (PCs, smartphones, VR headsets).

4.  Minimal IT staff is required: platform administrator-engineer, virtual space designers (level artists), 3D digitization operators, data analysts.

5.  The hypermarket's physical infrastructure (building, utility systems, equipment) is eliminated, except for optimized warehouse spaces and pickup points.

6.  Logistics is evolving towards automation (robotic warehouses, direct delivery from the manufacturer).

7.  Ancillary services (food courts, cafes) are separated from the hypermarket format and moved to leisure centers.

**Solution Options (Structural Changes)**

**1. Eliminated Physical Components**

*   Building and surrounding area (customer parking is reduced to a pickup zone).

*   Trading floor utility systems: heating, air conditioning, lighting, water supply (except for the warehouse/office).

*   Retail equipment: shelves, refrigerated displays (except for the warehouse), checkout counters.

*   Display samples of large appliances, furniture, cars.

*   Trading floor security and surveillance systems (hundreds of cameras, anti-theft gates).

*   Trading floor fire and sanitation systems (except for the warehouse).

*   Food courts and public dining points.

*   Advertising stands, POS materials, physical merchandising.

**2. Preserved/Modified Components**

*   **Warehouses:** Remain for storing high-turnover goods, but area is reduced by 60–70% due to the absence of display zones and the transition of large goods to direct delivery from the manufacturer.

*   **Pickup points:** Automated logistics hubs for self-collection.

*   **Logistics:** Delivery from manufacturer to customer (direct or via a consolidating hub).

*   **Personnel:**

    *   Platform Administrator-Engineer (1–2 people) – setup, module integration, monitoring.

    *   Virtual Space Designers (3–5 people) – creation and updating of the digital twin.

    *   3D Digitization Operators (2–3 people) – model generation from photos, validation.

    *   Behavior Analysts (1–2 people) – working with analytics module data.

    *   Warehouse Operators/Robotics Specialists (headcount depends on automation level).

**3. New Necessary Components**

*   License/rental for the VR platform with modules (Photo→3D, CMS, integrations, analytics).

*   Cloud infrastructure (IaaS) with GPU instances for model generation and rendering (optional, with auto-scaling).

*   API integrations with logistics platforms (autonomous vehicle/robot-picker management).

*   Data transmission channels for clients.

**Evaluation by Criteria**

**1. Economic Efficiency**

*   **CAPEX Reduction:**

    *   Elimination of building construction/rental costs (30–50% of the hypermarket's cost).

    *   No costs for retail equipment, display samples, floor security systems.

    *   Elimination of food courts (savings on utility infrastructure).

*   **OPEX Reduction:**

    *   Utility payments reduced by 80–90%.

    *   Elimination of maintenance costs for floor cameras, fire systems, plumbing (up to $100–300k/year).

    *   No losses from in-store theft (1–2% of turnover).

    *   Staff reduction by 70–80% (cashiers, merchandisers, security, cleaners).

    *   Elimination of physical merchandising costs.

*   **New Costs:**

    *   Platform subscription (estimated $50–200k/year depending on scale).

    *   Cloud infrastructure (variable, depends on traffic).

    *   Salaries for the new category of specialists (designers, 3D digitization operators).

**2. Technical Feasibility**

*   The Photo→3D module exists (photogrammetry, NeRF, Gaussian Splatting); platform integration solves the content problem.

*   Ready-made ERP, CRM, payment system integration modules reduce implementation time.

*   Cloud rendering and auto-scaling allow handling peak loads.

*   The development of logistics automation (robotic warehouses, autonomous transport) optimizes fulfillment.

**3. Operational Flexibility**

*   Instantaneous inventory and layout updates without operational downtime.

*   Dynamic merchandising and space personalization for the customer.

*   Global accessibility from anywhere.

*   Detailed behavior analytics (attention heatmaps, conversion).

**4. Limitations and Risks**

*   Tactility and smells are unavailable (critical for categories: food, fabrics, cosmetics).

*   Dependence on the customer's internet connection for an immersive experience.

*   Legal issues regarding the conformity of digital descriptions to physical goods.

*   Need to educate customers on interacting with the VR environment.

*   Competition with VR store aggregators (a single platform for all retailers).

**Conclusion**

1.  **Economic viability** of transitioning to a hypermarket digital twin becomes indisputable within a 3–7 year horizon:

    *   Main savings are achieved by eliminating CAPEX for construction and OPEX for maintaining physical infrastructure.

    *   Expected savings per hypermarket: $2–5 million annually; transition payback period: 1–3 years.

    *   Costs shift towards operational expenses for platform licensing, cloud infrastructure, and salaries for niche specialists.

2.  **Technological prerequisites** are ready:

    *   The platform with the 3D generation module solves the content problem.

    *   Ready-made integration modules accelerate implementation.

    *   The development of logistics automatically reduces fulfillment costs.

3.  **Personnel structure** changes radically: headcount is reduced by 5–10 times, requiring creative and IT specialists.

4.  **Risks** are concentrated in the area of consumer acceptance (the need to adapt to VR) and in the legal regulation of digital representations of goods.

**Final Recommendation:**

For a retail chain – pilot deployment of a digital twin for 1–2 product categories (electronics, furniture) with parallel integration with an automated logistics platform. This will allow for refining technological processes and evaluating customer behavioral metrics before a full-scale transition.