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Fleet Management

Data Analysis to identify patterns in the different components of Fleet Management, operations, vehicles, drivers and customers, in order to improve efficiency and maximize net value.

Business question: How costs relates to maintenance and fuel? How net revenue relates to goods value? How is km traveled distributed by driver? How many inactive vehicles, drivers and customers are? What are the cities with most freights?

Tools used: Looker Studio (Google).

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Key Insights

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  • In the first semester of 2019, overall KPIs (goods value, revenue, costs, maintenance) increased when compared with the previous period (1st semester 2018).

  • Revenue ratio increased 3% and maintenance ratio also increased 12% when compared with the previous period.

  • There was a pattern of increasing order profit until mid of 2017, after that decreased sharply.

  • The East Coast States present higher net revenues than the West ones, South Carolina has the highest net revenue.

  • Fuel has the highest contribution to the fixed costs.

  • The period between January and March 2019 has a sudden peak in fixed costs, without any evident explanation.

  • USA is the country leading ahead of the other countries in terms of orders placed.

  • The customer 19,999 ranks second in goods value, but ranks first in net revenue, meaning it is a vey 'profitable' customer.

  • Amost a third of the vehicles and drivers are inactive, this may affect the performance of the operations.

  • The average age of the vehicles are 12 years old, this may contribute to high maintenance costs.

1. Data Source

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  • Data source from a website, check button 'Data Source' above.

  • DataSet with 5 tables, 2 fact tables - Costs and Freights and 3 dimension tables - Vehicles, Drivers, Customers.

  • Relevant fields: cost, net revenue, km traveled, maintenance cost, fuel cost, liters consumption, driver id, truck id, customer id, city and state.

  • 5 Excel file with 92060 rows and 10 columns.

2. Data Visualization
 

  • In Looker Studio (Google), created varios graphs, calculated measures, blend tables (union), filters and sliders.

  • The graphs used were  Scorecard (for KPIs), Pie chat, Vertical bar chart , Combo chart, Line, Scatter and Geo chart.

    • Each vizualization has its specific tooltip.

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