Our client heads up a team of 8-10 automotive mechanics and was looking for a way to better track their inventory, while also allowing their customers to monitor their car’s progress in the garage.

As a solution, we developed an employee website portal, which allows employees to update, track and find inventory. We also built in machine learning which, over time, predicts and recommends when specific inventory will need re-ordering. To help customers track their car’s progress, we built a portal for both customers and employees, which can be accessed via computer or cell phone.

In order to gather information about their current inventory flow, ordering system and biggest inefficiencies, we started by interviewing our client’s employees. From here, we created a database and inputted into their current maintained inventory, with lead times from frequently used suppliers. We wireframed the employee portal and built an SMS messaging interface to send updates to customers. Employees were then allowed access to the database and we observed how they interacted with it, ironing out any issues that became apparent.

The database continues to be tested with machine learning in place and it’s currently working to predict our client’s most used parts, to help with managing inventory in the future.

Due to the improvements of inventory management and predictive demand software, parts were ordered in advanced allowing the Mechanics to overcome supply chain delays. As well employees spent much less time on the phone with customers due to the internal logging of vehicle issues and the customer being able to track repair progress online.  Overall the Business saved money and time as well attracted new customers with their turnaround speed and continued over the internet updates.