Business Research Proposal: Evaluating AI Smart Glasses vs. Traditional Devices in Last-Mile Delivery

1. Understanding the Core Problem and Final Output

• Problem Category: This is a Technology Evaluation and Process Improvement study. The central question is whether investing in a new technology (AI smart glasses) yields a sufficient return over the existing method (handheld devices) to justify adoption.
• Industry: B2B Technology within the Logistics & Supply Chain sector.
• Your User Profile & Required Output: As a consultant presenting to management, your final deliverable cannot be just a collection of data. It must be a decisive business case. Your research should culminate in a strategic recommendation that is clear, evidence-backed, and actionable.

1. Executive Recommendation: A clear, definitive stance on whether to broadly adopt the "Amelia" smart glasses. This could be a "go," "no-go," or a "phased rollout" recommendation.
2. Comparative Business Case: A detailed comparison of the two technologies across four key dimensions:
   • Financial Impact: A projection of the Return on Investment (ROI).
   • Operational Impact: Quantified improvements in efficiency, accuracy, and safety.
   • Customer Impact: How the technology affects the end-customer experience.
   • Employee Impact: Analysis of the effect on driver experience, satisfaction, and retention.
3. Implementation & Risk Mitigation Plan (If "Go"): A high-level roadmap for a broader rollout, including key phases, training considerations, and strategies to overcome potential challenges identified in the research.
4. Success Measurement Framework: A list of Key Performance Indicators (KPIs) that the company should track post-implementation to confirm the technology is delivering the expected value.

2. Recommended Framework & Rationale

• Framework Teaching: The Balanced Scorecard is a strategic planning and management tool used to evaluate performance from more than just a financial perspective. It forces you to look at the business problem from four distinct but interconnected viewpoints:
  1. Financial: Does this decision make financial sense? (e.g., profitability, ROI, cost savings).
  2. Internal Business Processes: Are we improving our core operations? (e.g., speed, quality, safety, efficiency).
  3. Customer: How does this affect our customers? (e.g., satisfaction, retention, on-time delivery).
  4. Learning & Growth: How does this impact our employees and our ability to innovate? (e.g., employee satisfaction, skills, tools, and culture).
• Applicability Explanation: The BSC is perfectly suited for this problem because your client needs to weigh operational gains against the driver experience and financial cost. A simple cost-benefit analysis would be insufficient.
  • The Internal Processes perspective directly addresses the need to measure operational efficiency metrics.
  • The Learning & Growth perspective provides a formal structure for evaluating the crucial "driver experience factors."
  • The Financial and Customer perspectives ensure your recommendation is grounded in business value and market competitiveness.
• Key Information to Collect for the BSC:
  • Financial: Cost of smart glasses vs. handheld devices; maintenance/software costs; potential savings from increased efficiency and reduced errors.
  • Internal Processes: Quantitative data from the field test (route completion times, delivery accuracy, safety incident rates) for both device types.
  • Customer: Industry data linking delivery speed/accuracy to customer satisfaction; qualitative insights on how new features (e.g., proof-of-delivery photos) might enhance the customer experience.
  • Learning & Growth: Qualitative feedback from drivers on usability, comfort, stress levels, and perceived effectiveness of each device; quantitative data on training time required.

3. Part 1: Information Collection Plan

A. Web Search Content

• Search Queries:

  1. cost of enterprise smart glasses vs rugged handheld scanners 2025

  2. ROI calculator for logistics technology implementation

  3. impact of last-mile delivery accuracy on customer satisfaction

  4. best practices for training employees on wearable AR technology in logistics

• Purpose of this Information:
  • Financial Inputs: The cost comparison between device types is a fundamental input for your ROI calculation. Finding existing ROI calculators or frameworks for logistics technology will help you structure your financial analysis.
  • Customer Impact Justification: Research shows that last-mile delivery is a critical component of overall customer satisfaction. Timeliness and accuracy are paramount. This allows you to argue that the operational improvements you measure (e.g., fewer missed deliveries) translate directly into a better customer experience and stronger brand loyalty.
  • Implementation Planning: Understanding best practices for training helps you proactively address the "Learning & Growth" aspect of the rollout and create a more realistic implementation plan.

B. User Interview Planning (Driver Field Study)

• Interview Subjects:
  • Group A (Test Group): A representative sample of delivery drivers using the "Amelia" AI smart glasses.
  • Group B (Control Group): A comparable sample of drivers performing the same routes using traditional handheld devices.
• Interview Purpose: To collect qualitative data on usability, physical and mental comfort, perceived effectiveness, and pain points for both technologies. This is crucial for evaluating the "driver experience" component.
• Core Interview Questions:
  1. "Walk me through a recent delivery where the device you used was particularly helpful or unhelpful. What happened?"
     • Analysis Purpose: To uncover specific, real-world examples of how each device performs in context. This provides qualitative evidence for your "Internal Processes" analysis.
  2. "On a scale of 1 to 5, how mentally demanding was it to use this device throughout your shift? What made it easy or draining?"
     • Analysis Purpose: To directly measure cognitive load. A device that is operationally faster but mentally exhausting may lead to burnout and lower long-term productivity. This is a key "Learning & Growth" metric.
  3. "Describe the physical experience of using this device for a full day. Did you experience any discomfort, eye strain, or other issues?"
     • Analysis Purpose: To assess the ergonomic impact of the devices. For wearables, this is a critical adoption barrier that must be evaluated for the "Learning & Growth" quadrant.
  4. "If you could change one thing about how this device works for your job, what would it be?"
     • Analysis Purpose: To identify key areas for improvement. This information is vital for your final recommendation, as it might highlight software tweaks or hardware adjustments needed before a full rollout.

4. Part 2: Information Analysis Plan

1. Populate the Balanced Scorecard:
   • Internal Processes Quadrant:
     • What to do: Take the quantitative performance data from your field test (e.g., route completion time, missed delivery rate, safety incidents).
     • How to analyze: Create a clear comparison table showing the average performance metrics for the "Amelia" group versus the "Handheld" group. Calculate the percentage difference for each metric. This is the evidence for your operational efficiency claims.
   • Learning & Growth Quadrant:
     • What to do: Transcribe and code your driver interviews. Group comments into themes like "ease of use," "physical comfort," "stress/cognitive load," and "perceived helpfulness."
     • How to analyze: Quantify the qualitative feedback where possible (e.g., "7 out of 10 Amelia users mentioned eye strain"). Use powerful quotes to illustrate key findings. Directly compare the driver sentiment between the two groups. This analysis forms the core of your "driver experience" evaluation.
   • Customer Quadrant:
     • What to do: Combine the findings from your web search with your internal process metrics.
     • How to analyze: Construct a logical argument. For example: "Our field test shows Amelia glasses reduce missed deliveries by X%. According to industry reports, every 1% improvement in delivery accuracy correlates with a Y% increase in customer retention. Therefore, adopting this technology is projected to improve customer loyalty."
   • Financial Quadrant:
     • What to do: Use the device cost data (from web search), the efficiency gains (from your field test), and potential savings (e.g., reduced fuel from faster routes, lower costs from fewer re-deliveries).
     • How to analyze: Build a simple ROI model. Project the total investment cost for a fleet-wide rollout. Project the annual savings based on the productivity lift. Calculate the payback period (e.g., "The initial investment of $Z will be paid back by efficiency gains within 18 months").
2. Synthesize and Formulate the Executive Recommendation:
   • What to do: Review your completed Balanced Scorecard.
   • How to analyze: Weigh the four quadrants against each other. Is the financial ROI compelling? Are there significant red flags in the Learning & Growth (driver experience) quadrant that might outweigh the operational gains? Your recommendation (Go/No-Go/Phased Rollout) will emerge from this holistic view. For instance, you might recommend a "Phased Rollout," starting with depots where route density is highest, if your analysis shows that is where the benefits are maximized.
3. Develop the Actionable Plans:
   • Implementation Plan: Use the insights from the Learning & Growth quadrant and your web search on training best practices. If drivers found the glasses difficult to learn, your plan must include a detailed, multi-stage training program.
   • Success Measurement Framework: The KPIs you will recommend are the very same metrics you used in your Balanced Scorecard (e.g., route completion time, driver satisfaction scores, device uptime, and cost per delivery). This ensures a continuous feedback loop for the client after they make their decision.