Glossary

BEES: a business-to-business e-commerce platform built to empower small and medium-sized retail partners and help grow their businesses. It mainly caters to CPG (Consumer Product Goods), such as beverages, packaged food, etc.
BEES Deliver: a suite comprising a mobile application for truck drivers and delivery personnel, along with a web application for back-office employees at DDCs (Distribution and Delivery Centers) to facilitate delivery fulfillment.
DDC: Direct Distribution Center
 

📝 The context

BEES Deliver is the T2, last-mile delivery logistics solutions for BEES goods. The web portal is used by distribution center employees as the central hub through which the field operations of the delivery team can be resolved to ensure that customers get the goods they ordered.
Control Tower is a feature inside the Portal, in the Dashboard tab, where users can check some big numbers and KPIs on how the deliveries of their DDC is going on that day, such as:
🗺 General route status
🚚 Deliveries status
🐝 Usage of the BEES Deliver app by delivery personnel
⏱ Time en route
📍Adherence to delivery radius
🔃 Product returns
At the time of this research, Control Tower had with low adoption and unclear ownership. Users lacked actionable data, filters, and historical views. The product needed a clearer direction grounded in actual user needs and workflows.

⭐ Executive summary

The BEES Deliver Portal users must do a series of analyses in the system to ensure the logistics of deliveries to clients go smoothly. 📈 In addition, they also must use it to do performance analyses and make sure the operation is meeting the KPI goals of the company. 📊 This study focused on the Control Tower feature, a dashboard inside BEED Portal. The team aimed to gain more clarity about CT and we were able to get information about: ⚙ User preferences 🔍 What data CT users want to see 👥 Use cases and scenarios
 
💡
Takeaways
To the participants, Control Tower should: ⬇ Allow users to both: consult information on the Portal and export it for sharing. ✅ Include the data that's more relevant to users, such as information related to time on operation, to the route, to the truck/driver, to the POC, and to refusals and modulation. 🗂 The scenarios in which users would most use Control Tower are: performance analyses, to address action plans, real time analyses and historical analyses.

🧪 Methodology

  • 10 remote interviews with logistics leads from Brazil, Argentina, Paraguay, Peru, Ecuador and Panama
  • CSD (Certainties, Suppositions, Doubts) stakeholder workshop
  • Persona and role definition
  • Thematic clustering via Dovetail
  • Use case and scenario mapping

💡 Key Findings

✅ What Worked

  • Live delivery tracking
  • Clean, intuitive UI

❌ Pain Points

  • Current-day data only
  • Lack of filters
  • Low clarity on ownership and usage

📊 User Needs

  • Filters by driver, date, DC
  • Exportable reports
  • Historical & performance data
  • Modulation and refusal visibility
  • Customized views by role

👥 Users & Use Cases

Primary Users
  • Distribution center managers
  • Route supervisors
  • Monitoring analysts
 
Use cases
  • Performance analysis
  • Action plans for critical POCs
  • Modulation management
  • Real-time and historical tracking
 

✅ Recommendations

  1. Add role-specific filters (date, DC, driver)
  1. Display critical logistics data (refusals, delivery times, modulations)
  1. Enable export/share functionality
  1. Customize dashboard views by role
  1. Clarify intended users and use cases

🙋🏻‍♀️ My Role

  • Conducted and synthesized interviews across 6 countries
  • Facilitated strategic workshops
  • Created persona-role scenarios
  • Delivered findings to Product and Design teams
  • Prioritized recommendations for the product roadmap
 
 
 
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