Once the decision to overbook workshop resources is made, it becomes essential to understand how to distribute booking hours effectively and automatically among workshop personnel. This is a critical step in ensuring the right overbooking workshop strategy is implemented without causing disruptions.

One of the best practices is to utilize resources based on skill level, with the most skilled person being only slightly overbooked.

How would one practically calculate that?

This is the topic I want to describe in my next article.

There are different algorithms available for overbooking. These algorithms include “proportional,” “sequential,” “progressive,” or “conditional” overbooking methods. There are many options to choose from, which means that one can write a book on this subject.

Based on personal experience, the ‘spread’ algorithm is a popular choice that best fits dealers’ demands. This method focuses on distributing booking hours among all resources, considering the skills each resource possesses. It ensures that less skilled resources are booked more, while more skilled individuals are booked less. As a result, more skilled mechanics are available, a crucial point in efficient service scheduling.

Does it seem complicated?

Well, let’s delve into the specifics, and I’ve created a practical example for you to follow.

Assuming the following scenario:

One workshop has four technicians with four different types of skills.

· Mechanic (MECH),

· Diagnostic (DIAG),

· Painting (PAINT),

· Body shop (BODY).

See example below:

Now, let’s get to how to distribute booking hours if, for example, 7 MECH Hours are booked for doing a service task, but the workshop lacks MECH available skills.

The spread overbooking algorithm takes into account a mathematical formula to determine the optimal overbooking amount.

Conclusion: Thanks to this automatic algorithm, John, the most experienced person, is now less overbooked than others.

As a result, some decimals can be seen, but it does not really matter. These numbers do not bother end-users but are crucial for dealer management systems or scheduling systems to manage overbooking effectively on a skills level.

I hope my article provided you with valuable insights. I am waiting to receive your feedback!

Dr. Juraj Hanus, hanus@taxapa.com

Data Analytics & Automotive Applications Expert for Dealerships

The post Overbooking Workshop Strategy appeared first on TaXaPa.

There is a great principle, which I use in seeking to understand which functional variables have the highest cumulative effects on the usage of the application. Neither broad knowledge nor magical formulas are required to implement this technique. It is a purely rational thing, and it works perfectly.

Now, I want to draw your attention to the Pareto principle, also known as the “80–20 rule.” The Pareto principle says that, for many events, approximately 80% of the effects come from 20% of the causes. Mr. Vilfredo Pareto (1848–1923) was a genial Italian engineer and sociologist who observed that 80% of the land in Italy was owned by 20% of the population. Later, the same phenomena (“80–20 rule”) were detected in different spheres of the everyday world. There is a book collection referring to this phenomenon, and I’m attaching two of my best picks here (Blue Ocean Strategy and The 4-Hour Work Week).

The “80–20 rule” is an observation, and surely it is not a law of nature. Consider the above before starting to apply it either in analyzing optimization efforts (QA) or determining functional specifications. Personally speaking, I found the Pareto Chart powerful in requirements analysis. It helps to visualize what matters most.

Let’s imagine we are designing a workshop scheduling application that is used to manage service appointments and utilize workshop resources effectively (core idea). Such a sophisticated tool consists of very different requirements; therefore, the Pareto principle may help. To support the product’s core idea, one should classify use cases as functional variables and measure them (frequency, quantity, cost, or time). Here, I would suggest grouping different service appointment types per period. However, someone may consider a different approach. Standard services to offer, resources skill set available, or a source of appointments could also work with the Pareto Principle.

Procedure: Sample data are collected and recorded in each category in the table below:

Using the data above, we now build the Pareto Chart.

The figure presents how many service appointment types were received in each of the five categories, with cumulative values. If all categories require a particular set of functionality, starting with functional requirements dealing with small and quick services would have the most substantial impact on the usage.

The Pareto chart is a suitable instrument to analyze data about the frequency of events (problems) or causes in a process. Or by encountering different requirements on the same application, and one wants to focus on the most significant. I am successfully using it in communication with stakeholders about product-related decisions.

Please see the useful links related to the topic above.

The 5 Guidelines For Functional Design

What is a Pareto Chart?

Functional Analysis and Allocation

Dr. Juraj Hanus, hanus@taxapa.com

Data Analytics & Automotive Applications Expert for Dealerships

The post The Pareto Principle in Functional Analysis and Requirements (FRA) appeared first on TaXaPa.