⏮️ Context

🎯 Problem Statement

Lack of Automation in Drive-thru Mobile Orders

The drive-thru experience for Mobile Ordering customers is hindered by a lack of automation in the order-to-kitchen workflow in BookinAll. The QR code scanned by customers at the drive-thru does not include their Loyalty ID, necessitating manual intervention by cashiers to send the order to the kitchen for preparation. This lack of automation not only consumes valuable time but also increases the likelihood of human error, ultimately resulting in longer wait times and a degraded customer experience. Streamlining this process is essential to improve service speed and enhance customer satisfaction.

🎯 Problem Statement

Inefficiencies in Drive-thru Mobile Ordering Workflow

The current drive-thru Mobile Ordering workflow is inefficient due to the lack of automated integration between the QR code system and the order-to-kitchen process. When customers scan their QR codes, the system fails to capture their Loyalty ID, requiring cashiers to manually intervene to ensure the order reaches the kitchen. This process is not only time-consuming but also prone to human error, adversely affecting the overall speed and quality of customer service.

• Manual Intervention: Cashiers need to manually process orders, leading to delays and potential errors.

• Longer Wait Times: Increased order processing time results in longer queues and customer dissatisfaction.

• Human Error: Manual input increases the risk of mistakes, impacting order accuracy and customer experience.

• Customer Dissatisfaction: Waiting longer for their orders frustrates customers, potentially affecting retention and brand loyalty.

• Operational Inefficiency: The need for manual intervention reduces the efficiency of drive-thru operations, leading to increased labor costs and decreased throughput.

Current Experience

Target Audience

1. Mobile Ordering Customers

Profile:

• Needs: Quick, seamless ordering process; accurate order fulfillment; loyalty benefits.

• Behaviors: Frequently use mobile apps for convenience; value speed and efficiency;

• Pain Points: Long wait times; manual errors in orders; lack of loyalty point automation.

• User Story: As a regular customer of Burger King who frequently uses mobile ordering, I want to scan my QR code at the drive-thru and have my order automatically sent to the kitchen, so I can get my food quickly without any errors.

Example Use Case:
John, a loyal Burger King customer, uses the Whitelabel App to place a mobile order while driving to the restaurant. Upon arrival, he scans his QR code at the drive-thru. The current manual process approves the Order of the person behind him first, causing a delay in his order and frustration. Automating the process would significantly improve John’s experience, ensuring quick service.

2. Drive-Thru Cashiers

Profile:

• Needs: Efficient order processing; reduced manual tasks; error-free workflow.

• Behaviors: Handle multiple tasks simultaneously; rely on quick, precise systems; aim to minimize customer wait times.

• Pain Points: Manual order entry; risk of human error; increased workload during peak times.

• User Story: As a drive-thru cashier, I want the QR code system to automatically send the order directly to the kitchen, so I can focus on other tasks and reduce wait times for customers.

Example Use Case:
Maria, a drive-thru cashier at Popeyes, often finds herself manually approving orders in the wrong order, which creates confusion in the kitchen and prolonged wait times for customers. With an automated system, Maria could serve customers faster and more efficiently, improving overall service quality.

3. Restaurant Managers

Profile:

• Needs: Streamlined operations; high customer satisfaction; efficient workforce management.

• Behaviors: Monitor order flow and staff performance; implement operational improvements; ensure high service standards.

• Pain Points: Inefficient workflows; high labor costs due to manual processes; customer complaints about wait times.

• User Story: As a restaurant manager, I want an automated order-to-kitchen workflow that reduces manual intervention, so I can enhance operational efficiency and improve customer satisfaction.

Example Use Case:
Tom, a manager at a busy Burger King location, frequently deals with customer complaints about long wait times at the drive-thru. By implementing an automated system that integrates the Loyalty ID into the order process, Tom can reduce bottlenecks, lower labor costs, and ensure a smoother operation, leading to happier customers and better staff productivity.

❔ Expected Outcome

To address the identified opportunity, the proposed solution is to enhance the existing BookingAll system by integrating the customer Loyalty ID into the drive-thru order workflow. This involves updating the getOrders endpoint to include the customer's Loyalty ID. Once the endpoint is updated, the BookingAll system will be configured to automatically send the order to the kitchen without requiring manual intervention from the cashier.

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1. Reduced Wait Times: Automation can cut down the time required to process drive-thru orders, leading to faster service times and improved customer satisfaction.

2. Enhanced Accuracy: Minimizing human intervention will reduce the likelihood of errors, ensuring that orders are accurately prepared.

3. Increased Efficiency: Streamlining the order-to-kitchen workflow will lead to better resource utilization and operational efficiencies.

4. Customer Retention: Improved service quality and reduced wait times will contribute to higher customer retention rates and increased loyalty program engagement.

5. Alignment with Strategic Goals: This solution aligns with RBI's strategic goals of enhancing customer experience and leveraging technology to improve operational efficiencies.

Must-Haves

1. Automated Loyalty ID Integration

   • Description: Update the getOrders endpoint in the RBI Partners APIs to include the customer Loyalty ID.

   • Rationale:

     • Essential for eliminating manual intervention and reducing order processing time.

     • Leverages the existing getOrders call.

     • Documentation: https://euw3-dev-bk-partners-api.rbictg.com/docs/market/#tag/OrderAPI/operation/getOrders

   • Business Value: High; improves customer experience and operational efficiency.

2. Automated Order-to-Kitchen Workflow

   • Description: Modify BookingAll to automatically send orders to the kitchen once the QR code is scanned.

   • Rationale: Critical for streamlining the drive-thru process and minimizing human error.

   • Business Value: High; enhances service speed and accuracy, leading to higher customer satisfaction.

Out of scope

1. Enhanced QR Code System

   • Description: Upgrade the QR code system to ensure seamless capture of all necessary order details including Loyalty ID.

   • Rationale: Important for ensuring the system’s reliability and ease of use for customers but a change in the QR Code might impact other partners.

   • Business Value: Medium; supports the primary automation features and improves user experience but could impact other partners that are also scanning the QR Code.

❓ Open questions

1. How is this integration working now? What is the trigger point?

   1. The Customer scans a QR Code containing an ID of the Order

   2. The BookingAll solution gets information from the getOrders endpoint

2. Is BookingAll an RBI or Partner tool?

   1. It’s a partner tool

3. Is there a dependency on BookingAll? (new endpoint?)

   1. They will need to adjust the order-to-kitchen workflow to read the new LoyaltyId data from the getOrders endpoint and automatically send the Order to the kitchen.

   2. BookingAll to confirm the development timeline

   3. Need to organize integrated tests and UAT with BookingAll

4. Does this impact other countries? Is BookingAll used by all of Iberia?

5. Should this be sent to any other partner platform? (autoking?)

   1. By adding the information to the Partners API any other platform that might make use of it can already benefit from this solution.

6. Is there documentation on BookinAll integration?

7. Do we have data on how many Mobile Ordering orders are picked up in the drive?

   1. No, the data is not specific enough at the time.

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