Machine learning in the shopping cart: MENY's recipe for effective home delivery
Machine learning in the shopping cart: MENY's recipe for effective home delivery
Machine learning in the shopping cart: MENY's recipe for effective home delivery
Client
MENY
MENY's prediction system helps the grocery chain plan the number of employees needed to process all orders, reducing both overstaffing and understaffing.
Client
MENY
MENY's prediction system helps the grocery chain plan the number of employees needed to process all orders, reducing both overstaffing and understaffing.
Client
MENY
MENY's prediction system helps the grocery chain plan the number of employees needed to process all orders, reducing both overstaffing and understaffing.
Challenge
Together with Forte, MENY wanted to streamline and optimize logistics and operations related to the delivery and packing of goods to customers.
MENY faced challenges in planning their capacity for online order processing and delivery. They struggled, among other things, to predict the expected number of orders, which led to inefficient resource allocation and frequent over- or under-staffing.
The goal was to create the greatest possible value from historical data and make that knowledge available to decision-makers responsible for operational activities.
Challenge
Together with Forte, MENY wanted to streamline and optimize logistics and operations related to the delivery and packing of goods to customers.
MENY faced challenges in planning their capacity for online order processing and delivery. They struggled, among other things, to predict the expected number of orders, which led to inefficient resource allocation and frequent over- or under-staffing.
The goal was to create the greatest possible value from historical data and make that knowledge available to decision-makers responsible for operational activities.
Together with Forte, MENY wanted to streamline and optimize logistics and operations related to the delivery and packing of goods to customers.
MENY faced challenges in planning their capacity for online order processing and delivery. They struggled, among other things, to predict the expected number of orders, which led to inefficient resource allocation and frequent over- or under-staffing.
The goal was to create the greatest possible value from historical data and make that knowledge available to decision-makers responsible for operational activities.
Solution
In collaboration with Forte, MENY has developed a prediction system based on machine learning that predicts the number of orders by analyzing historical data, campaigns, holidays, and other relevant factors.
The system uses advanced algorithms to identify patterns in the order history and provides accurate forecasts that the operational team uses to plan capacity and staffing – up to 20 weeks in advance.
Solution
In collaboration with Forte, MENY has developed a prediction system based on machine learning that predicts the number of orders by analyzing historical data, campaigns, holidays, and other relevant factors.
The system uses advanced algorithms to identify patterns in the order history and provides accurate forecasts that the operational team uses to plan capacity and staffing – up to 20 weeks in advance.
In collaboration with Forte, MENY has developed a prediction system based on machine learning that predicts the number of orders by analyzing historical data, campaigns, holidays, and other relevant factors.
The system uses advanced algorithms to identify patterns in the order history and provides accurate forecasts that the operational team uses to plan capacity and staffing – up to 20 weeks in advance.
Results
The solution has created a more precise and efficient distribution of resources, reducing the risk of both overstaffing and understaffing. It provides better predictability for employees and third-party providers and allows for optimal vehicle ordering. This results in cost savings, higher operational efficiency, and better utilization of delivery capacity.
For customers, this means increased flexibility, higher delivery accuracy, and a smoother buying experience, resulting in higher revenue and stronger customer loyalty to MENY.
Reduction in the number of unused pickup times
25
%
Reduction in overcrowded pickup times
15
%
Increase in capacity for popular pickup times
50
%
Results
The solution has created a more precise and efficient distribution of resources, reducing the risk of both overstaffing and understaffing. It provides better predictability for employees and third-party providers and allows for optimal vehicle ordering. This results in cost savings, higher operational efficiency, and better utilization of delivery capacity.
For customers, this means increased flexibility, higher delivery accuracy, and a smoother buying experience, resulting in higher revenue and stronger customer loyalty to MENY.
Reduction in the number of unused pickup times
25
%
Reduction in overcrowded pickup times
15
%
Increase in capacity for popular pickup times
50
%
Results
The solution has created a more precise and efficient distribution of resources, reducing the risk of both overstaffing and understaffing. It provides better predictability for employees and third-party providers and allows for optimal vehicle ordering. This results in cost savings, higher operational efficiency, and better utilization of delivery capacity.
For customers, this means increased flexibility, higher delivery accuracy, and a smoother buying experience, resulting in higher revenue and stronger customer loyalty to MENY.
Reduction in the number of unused pickup times
25
%
Reduction in overcrowded pickup times
15
%
Increase in capacity for popular pickup times
50
%
This is a game changer for us because it will provide cost savings, increased efficiency, and better customer experiences. For our customers, it means more flexibility and efficiency when they want to order goods to be delivered to their homes.
Jørgen Normann-Larsen
,
CMO MENU
This is a game changer for us because it will provide cost savings, increased efficiency, and better customer experiences. For our customers, it means more flexibility and efficiency when they want to order goods to be delivered to their homes.
Jørgen Normann-Larsen
,
CMO MENU
This is a game changer for us because it will provide cost savings, increased efficiency, and better customer experiences. For our customers, it means more flexibility and efficiency when they want to order goods to be delivered to their homes.
Jørgen Normann-Larsen
,
CMO MENU
Contact us
Jesper Nørding Pedersen
Managing Director & Partner
Contact us
Jesper Nørding Pedersen
Managing Director & Partner
Contact us