Johnson Controls
Johnson Controls
Case study
Abour Johnson Controls
johnson Controls, Inc. produces electronics and HVAC equipment. The Company offers HVAC equipment, building automation, security, fire detection, batteries, and other related products, as well as building control systems, energy management, and integrated facility management services
One of Johnson Controls’ biggest business struggles was about their order allocation which was operated manually and had inaccuracies which led to client dissatisfaction in large amounts.
The solution was developing an allocation model and producing an automated recommendation engine which plans for the future and makes the results adjustable.
The implementation of the service decreased the time spent on the order allocation information gathering by at least 80% and the accuracy of the orders jumped from 0% to 95%
One of Johnson Controls’ biggest business struggles was about their order allocation which was operated manually and had inaccuracies which led to client dissatisfaction in large amounts.
The solution was developing an allocation model and producing an automated recommendation engine which plans for the future and makes the results adjustable.
The implementation of the service decreased the time spent on the order allocation information gathering by at least 80% and the accuracy of the orders jumped from 0% to 95%
S (situation)
T (task)
A (action)
R (result)
The inventory system of Johnson Controls was managed manually, causing inaccuracy in orders thus leading to huge problems with client satisfaction.
Developing an automated allocation model to enable planning and inventory forecasting.
Building a pipeline by collecting, cleaning, and organizing data from different sources to be gathered in one dataset. Developing an algorithm that accurately allocates resources Providing the results in the format that Johnson Controls requested.
Johnson Controls was able to cut down the time spent on the order allocations by at least 80%. Accuracy of the orders jumped to 95%, which before the implementation, the accuracy was close to 0%.
