H2O.ai Case Studies Shipment Volume Forecasts Powered by AI at Senko Group

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	Shipment Volume Forecasts Powered by AI at Senko Group H2O.ai

Shipment Volume Forecasts Powered by AI at Senko Group

H2O.ai

Technology Category	Analytics & Modeling - Machine Learning Analytics & Modeling - Predictive Analytics
Applicable Industries	Retail
Applicable Functions	Logistics & Transportation Warehouse & Inventory Management
Use Cases	Fleet Management Inventory Management Predictive Maintenance
Services	Data Science Services
Challenge	Senko Group Holdings, a large integrated logistics service provider, was facing challenges in manpower planning due to the shortage of workers in Japan. The company needed to maintain a high level of customer service despite the inability to cut operational tasks. The logistics staff was burdened with the task of predicting shipment volumes from their warehouses, a task that was time-consuming and complex. The company initially tried using R and IBM SPSS for AI-based shipment volume forecasts, but found them challenging for the logistics staff to use for actual operations. The structure of the model was complicated and required a great deal of effort for creating models as well as for applying feature engineering. Read More
About Customer	Senko Group Holdings is a large integrated logistics service provider that operates logistics business as one of their core businesses focusing on apparel and ecommerce in the Tokyo metropolitan area. The company provides services to their contracted customers and works on improving the efficiency of their operations. One of the key challenges they face is securing workers for operations at warehouses due to the current shortage of workers in Japan. In order to maintain the customer service level, the company has been exploring ways to cover part of these tasks. Read More
Solution	Senko Group decided to introduce AI for shipment volume forecasts and chose to use Driverless AI. This AI tool repeatedly performs feature engineering, selects prediction method and performs tuning, delivering highly accurate results without depending on the skill of creating statistical analysis model. The company uses SPSS for data processing and Driverless AI for predictive modelling and prediction output, which help them streamline the operational procedure. The accurate shipment volume forecasts allowed them to plan and allocate workers more efficiently, reducing the workload of logistics staff and improving the efficiency of manpower planning. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Machine Learning

Analytics & Modeling - Predictive Analytics

Applicable Industries

Retail

Applicable Functions

Logistics & Transportation

Warehouse & Inventory Management

Use Cases

Fleet Management

Inventory Management

Predictive Maintenance

Services

Data Science Services

Challenge

Senko Group Holdings, a large integrated logistics service provider, was facing challenges in manpower planning due to the shortage of workers in Japan. The company needed to maintain a high level of customer service despite the inability to cut operational tasks. The logistics staff was burdened with the task of predicting shipment volumes from their warehouses, a task that was time-consuming and complex. The company initially tried using R and IBM SPSS for AI-based shipment volume forecasts, but found them challenging for the logistics staff to use for actual operations. The structure of the model was complicated and required a great deal of effort for creating models as well as for applying feature engineering.

About Customer

Senko Group Holdings is a large integrated logistics service provider that operates logistics business as one of their core businesses focusing on apparel and ecommerce in the Tokyo metropolitan area. The company provides services to their contracted customers and works on improving the efficiency of their operations. One of the key challenges they face is securing workers for operations at warehouses due to the current shortage of workers in Japan. In order to maintain the customer service level, the company has been exploring ways to cover part of these tasks.

Solution

Senko Group decided to introduce AI for shipment volume forecasts and chose to use Driverless AI. This AI tool repeatedly performs feature engineering, selects prediction method and performs tuning, delivering highly accurate results without depending on the skill of creating statistical analysis model. The company uses SPSS for data processing and Driverless AI for predictive modelling and prediction output, which help them streamline the operational procedure. The accurate shipment volume forecasts allowed them to plan and allocate workers more efficiently, reducing the workload of logistics staff and improving the efficiency of manpower planning.

Impact #1	The company was able to deliver a high degree of accuracy of 87% for forecasts.
Impact #2	The accuracy of the forecasts remained high even when the forecast period was extended from one week to one month.
Impact #3	The workload of logistics staff dealing with a wide range of tasks was reduced.

Impact #1

The company was able to deliver a high degree of accuracy of 87% for forecasts.

Impact #2

The accuracy of the forecasts remained high even when the forecast period was extended from one week to one month.

Impact #3

The workload of logistics staff dealing with a wide range of tasks was reduced.

Benefit #1	Achieved a high degree of accuracy of 87% for forecasts.
Benefit #2	Improved the previous accuracy level from 60% to 87%.
Benefit #3	Reduced the workload of logistics staff by 5%.

Benefit #1

Achieved a high degree of accuracy of 87% for forecasts.

Benefit #2

Improved the previous accuracy level from 60% to 87%.

Benefit #3

Reduced the workload of logistics staff by 5%.

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Overview

Shipment Volume Forecasts Powered by AI at Senko Group

Operational Impact

Quantitative Benefit