Olist E-Commerce Logistics & GMV Operational Audit
Conducted a comprehensive operational gap analysis of Brazil's leading e-commerce sales ecosystem to isolate shipping friction and model scalable carrier consolidation pipelines.
1. The Problem
Olist E-Commerce was facing a critical customer retention crisis. A review of buyer feedback surveys indicated rising dissatisfaction centered on long shipping lead times, delayed handovers, and erratic carrier performance. These logistics issues directly led to customer complaints, an increased refund rate, and stagnant Gross Merchandise Value (GMV) growth across key Brazilian regions.
Before proposing raw software solutions, Olist needed to understand **where** the system was failing. The core challenge was isolating whether delays originated from seller packaging inefficiency, logistics hubs, or final-mile carrier distribution.
2. The Approach
To address the problem holistically, I applied the **Nadler-Tushman Congruence Model** to audit the company's internal and external systems. I structured my analysis into three logical phases:
- Process Mapping: Modeled the entire order-to-delivery lifecycle using standard Business Process Model and Notation (BPMN) diagrams in Draw.io to identify manual handoffs.
- Data Ingestion: Ingested over 100,000 transaction, order, and location records in Microsoft Excel for data sanitization and variable modeling.
- Visual Analytics: Built operational logistics dashboards in Tableau Desktop to isolate state-by-state delivery delays.
3. The Process
I traced the operational flow step-by-step:
Checked for missing zip codes, resolved null values in delivery timestamp logs, and created calculated fields to isolate 'seller processing duration' from 'carrier transit duration'.
Mapped swimlanes for Sellers, Olist Platform, Warehousing Hubs, and Carriers. Found that the handoff from independent sellers to third-party shipping hubs had zero system-driven SLA controls.
Established core metrics in Tableau to track Carrier Lead Time Variance, Average Shipping Duration by State, and Hub-to-Buyer Distance Ratios.
4. The Analysis
The quantitative analysis of the 100k+ transaction records yielded three critical operational discoveries:
Nearly one-third of overall logistics friction occurs before the final carrier ever receives the package. Independent sellers spend an average of 48 hours packing and labeling orders, double the platform's nominal 24-hour target.
Deliveries destined for northeastern states (e.g., Bahia, Ceará) take over a week longer to arrive than shipments within Rio de Janeiro and São Paulo, directly stemming from fragmented regional hub networks.
Using the Nadler-Tushman model reveals a structural friction: the business relies on decentralized, loose logistics contracts while pursuing highly aggressive customer retention and growth targets.
5. Business Recommendation
Based on these insights, I delivered a structured operational restructuring proposal to consolidate Olist's freight and establish localized sorting hubs. I backed this with interactive Tableau logistics dashboards to empower category managers.
Recommended Strategic Impact
- Modeled 3.4-Day Shipping Reduction: Consolidating regional carrier networks is projected to achieve a 22% reduction in shipping durations across core states.
- Projected 12% Freight Savings: Auditing and optimizing rural dispatch parameters and routes could yield substantial localized savings.
- Recommended Dashboard Systems: Visualized operational metrics in a production-ready dashboard design to track seller packaging SLAs.