Retail Digital Twin Discovery

• Defines and Accelerates a Retailer's Digital Twin Journey
• Lays the foundation for a real-time digital replica of operations, surfacing hidden insights and enabling agile, efficient, customer-centric operations
• Identifies opportunities for data integration across sales, inventory, fulfilment, CDPs, computer vision (footfall, queue length, shelf engagement), and more
• Recommends AWS services to power insights that improve responsiveness, reduce inefficiencies, and optimise supply chain and workforce management
• Aligns business goals, evaluates systems, identifies integration opportunities, and delivers a roadmap to realise value early and often
• Produces a clear, actionable strategy aligned with business goals and technical feasibility, minimising risk and unlocking long-term value

A successful digital twin begins with a focused Discovery phase. Zühlke help define scope, align stakeholders, and prioritise high-impact use cases to ensure measurable value from day 1.

Discovery unlocks:

Identify where a digital twin delivers value (e.g., reducing stockouts, optimising space, enhancing customer experience). Our approach reduces risk and accelerates value by addressing integration, data quality, and stakeholder alignment early.

Simulate shopper journeys, inventory flow, staff productivity, and energy use. Discovery ensures models reflect real-world complexity.

Plan for integrating IoT, POS, supply chain, and app data. Discovery defines architecture and strategy to scale across the ecosystem and support future innovations like autonomous stores and hyper-personalisation.

Ensure the solution is designed with AWS-native services (e.g., AWS IoT TwinMaker, Lambda, Kinesis, S3, Sagemaker), for a secure, cloud-optimised foundation tailor-made for multi-site retail.

Define KPIs and metrics to track store performance and customer experience. Set the stage for testing layout changes, demand forecasting, and proactive issue resolution, enabling cost savings and improved CX.

Discovery includes:

• Outcome Definition: Align stakeholders on target outcomes and a unified vision
• Technical Review: Analyse data sources (IoT, CCTV, POS, CDP, ERP, OMS, WMS, 3PL, etc.), systems, and infrastructure
• Operational Assessment: Identify potential challenges and optimisations, setting realistic expectations

• Data Integration Assessment: Identify and prioritise required data sources, focusing on quality, accuracy, and timeliness
• Collaborative Workshops: Agree operational goals, data priorities, and surface any gaps in current technology estate
• Skills and Capacity Analysis: Identify and evaluate competencies needed for digital twin management

• Stakeholder Identification: Identify user groups (e.g., operations, suppliers, store managers, purchasing, logistics) and their decision-making needs
• Interaction Modelling: Design user interactions with the digital twin, emphasising ease of access
• Operational Scenario Exploration: Surface typical operational challenges like delay management, resource optimisation, and passenger flow, to shape actionable insights

Zühlke will deliver:

• Executive Summary: Clear, actionable insights, highlighting key findings and recommendations
• Strategic Alignment Roadmap: A plan for business and IT alignment on implementation
• UX Recommendations: Insights, user interactions, and use cases
• Architecture Proposal: A high-level architectural design tailored to a retailer‚Äôs needs
• AWS Guide: Recommended tools and frameworks
• KPI Framework: A suite of metrics to monitor effectiveness
• MVP Proposal: A costed plan for MVP implementation

After Discovery, Zühlke will be able to deliver an MVP to validate assumptions and refine the approach using live data, ensuring the digital twin delivers measurable value.