description.txt

The error metric for this competition is the Root Mean Squared Error

For every row in the dataset, submission files should contain 2 columns: 

order_id and Time from Pickup to Arrival (Predicted time in seconds between arrival and Pickup).

Your submission file should look like this:

Order_No                Time from Pickup to Arrival
Order_No_19248          197
Order_No_12736          7533
Order_No_768            768

Logistics in Sub-Saharan Africa increases the cost of manufactured goods by up to 320%; while in Europe, it only accounts for up to 90% of the manufacturing cost.

Economies are better when logistics is efficient and affordable.
Sendy, in partnership with insight2impact facility, is hosting a Zindi challenge to predict the estimated time of delivery of orders, 

from the point of driver pickup to the point of arrival at final destination.

The solution will help Sendy enhance customer communication and improve the reliability of its service; which will ultimately improve customer experience. In addition, the solution will enable Sendy to realise cost savings, and ultimately reduce the cost of doing business, through improved resource management and planning for order scheduling.

Sendy helps men and women behind every type of business to trade easily, deliver more competitively, and build extraordinary businesses.

“We believe in them; we believe that logistics should be an enabler for them to achieve their goals, rather than a hindrance. We believe that everyone should be able to participate and thrive in the economy and that no small business should be left out because the cost of logistics is either too high or inaccessible.”
Data is a critical component in helping Sendy to build more efficient, affordable and accessible solutions. Given the details of a Sendy order, can we use historic data to predict an accurate time for the arrival of the rider at the destination of a package? In this competition, we’re challenging you to build a model that predicts an accurate delivery time, from picking up a package to arriving at the final destination. An accurate arrival time prediction will help all businesses to improve their logistics and communicate an accurate time to their customers.

This competition is being hosted by Sendy and insight2impact.