How Taxi Hochelaga transformed their scheduling process to become an industry leader. Taxi Hochelaga knew they wanted to improve their scheduling process, but weren’t sure where to start. They were scheduling an average of 700 trips per day (~200 vehicles) with a scheduling team of 5 people, plus input from dispatchers, and they were required to generate a new schedule each night between 8pm and 6am, when the first trips were dispatched. They were growing quickly, and having a hard time balancing their growth with important considerations like driver satisfaction, mostly due to the increasing pressure on their driver’s schedules. Learn how we worked with them to transform their scheduling process, ultimately reducing the size of workforce needed by 10%, while increasing the work capacity by 15-20%.

1. Case Study: Improving a
Scheduling Process
How Taxi Hochelaga Transformed Their Process
& Became an Industry Leader

2. The Situation
Growing Quickly
They were scheduling an
average of 700 trips per
day for 200 vehicles, but
were expecting more
growth.
Already Busy
Planning happened
through the night, usually
from 8pm to 5am, with a
scheduling team of up to
5 people involved.
Efficiency + Satisfaction
Balancing growth and
maintaining minimum
revenue targets for
drivers, and driver
satisfaction, was a
constant challenge.

3. Goal:
Build a process, and use tools, that
would reliably give control over
scheduling, while allowing easy
adjustment of the rules applied, to
maximize efficiency and driver
satisfaction.

4. Step 1: Initial assessment

5. 1. Initial Assessment
Examining the current process was the main focus here.
We observed their schedulers to gain an understanding of the
workflow, as well as the rules and heuristics applied.
Example discovery: recurring rides placed in the schedule
first.

6. Step 2: Rule Extraction

7. 2. Rule Extraction
Goal: Based on Step 1 and historical data, generate a set of
rules governing the scheduling process.
We got feedback from scheduling team on our first try at a
ruleset - often there will be ‘informal’ rules that come up.
Example discovery: a certain subset of drivers was being
favoured due to more flexible operating rules.

8. Step 3: Counter-Intuitive
Discoveries

9. 3. Counter-Intuitive Discoveries
By recognizing and adjusting things like removing the
preference for certain types of drivers, they were able to
decrease fleet size over 10%, while completing 15-20% more
work.
This is the opposite of their original plan, which was to hire
more drivers.

10. By bringing in experts, making the process data-driven, and
being open to sometimes painful discoveries about their
scheduling process, Taxi Hochelaga was able to bring their
scheduling process to the cutting-edge, and find the optimal
balance between crew satisfaction, customer service
reliability and company business objectives.

11. If you’d like more details about this particular case study,
the original full article can be found here.
You can read more articles about scheduling, optimization,
and how to improve operations on our blog here.

12. leansystems.co
@leansystemsHQ
Full article on our blog about optimization!
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