How we achieved a 27% increase in operational efficiency for a home services business

The client: high-volume home services

A seasonal home-services business, providing delivery, set up, and removal of Christmas trees to over 400 households and businesses. During the months of December and January the client operates 2-3 trucks each servicing between 15-20 stops per day.

The problem: inefficient operations

The client was looking to scale operations which required the outsourcing of delivery operations to a third-party moving company rather than relying on in-house contractors. While this would offload a large portion of the administrative workload (such as vehicle leasing, hiring, scheduling, and payroll) and allow the business to enter new markets much faster, it would also increase the cost of labor from $50/hour to $120/hour. Given the significant increase in labor costs, the client needed to increase the number of deliveries per hour in order to maintain per unit margins at an acceptable level.

The solution: reduce driving time and re-visits

The client was operating off of an expansive delivery schedule on a city-wide basis, which meant that driving times between stops were often quite long. They also relied on manual data entry between three separate platforms, which was time-consuming and prone to errors that led to re-visits.

To reduce driving time, we developed clustering models to generate more efficient delivery routes grouped by postal code and expected demand density, which increased deliveries per hour by 16%. However, the resulting schedule was non-intuitive and hard to communicate to customers, so we built a custom application integrated with the client’s e-commerce platform to suggest available delivery times automatically.

To reduce revisits, we integrated the e-commerce platform and customer communication channels via APIs, and introduced automated pre-arrival notifications to customers via email and text. Together, these efforts significantly reduced customer no-shows and revisits, leading to an additional 11% increase in delivery efficiency.

The result: an improved and scalable operation

Together, these two efforts ultimately raised the delivery rate from 1.57 to 2 trees per hour. The combined 27% increase in delivery efficiency allowed the client to maintain per unit margins while transitioning the business to a more operationally sustainable model.