MaxOptra -

MaxOptra

Loading app

I’m working for MaxOptra, a parcel delivery and tracking software service, designing mobile apps and developing new features for their SAS software. The first app I created was Digital Manifest, which manages the loading of delivery vehicles from the warehouse.

My Role

UX / UI Designer and researcher

Working with Victoria White Product manager

The assignment

Our client, a large e-commerce company, has a warehouse that employs several hundred employees. The employees are responsible for processing orders, packing, and shipping products to customers. The current loading process is highly manual, time-consuming, and error-prone, which is resulting in low productivity, increased errors, and employee dissatisfaction.

Duration

The project took three weeks split into three one week sprints, conducting research first, analysis and prototyping

Tools

I used Figma to prototype and FigJam for tram updated and project planning.

The research

To understand the loading process of the warehouse employees, we conducted a series of interviews and observations. We identified the following pain points with their current process:

Manual data entry:

Employees are required to manually enter data into the warehouse management system (WMS) for each order. This is time-consuming and prone to errors.

Inefficient product order:

The current product order system is not optimized, which results in employees spending more time reordering products for loading.

Lack of real-time feedback:

Employees do not receive real-time feedback when loading vehicles, which makes it difficult for them to identify errors and make corrections.

Current workflow

The research enabled us to design a user flow diagram of their current workflow

Design

From the research and the flow diagram we created a user flow for the app.

This enabled us to improve the UX work process and develop a set of design recommendations:

Automated data entry:

We recommend integrating barcode scanning with the WMS to automate data entry, which will reduce errors and save time.

Optimize product order:

We recommend optimizing the product order system using location data to identify the order of delivery.

Real-time feedback:

We recommend implementing a real-time feedback system that provides employees with feedback on their work. This will help them identify errors and make corrections more quickly.

Implementation

We worked with the client to implement our design recommendations and create a prototype. The barcode scanning was integrated with the WMS, and the product order system was optimized using location data. A real-time feedback system was implemented, and the loading process was streamlined.

Conclusion

Improving the UX work process of warehouse employees is critical to the efficiency and productivity of the warehouse. By understanding the pain points and developing design recommendations, we were able to significantly improve the UX work process of the warehouse employees. The implementation of our design recommendations resulted in reduced errors, increased productivity, and improved employee satisfaction.