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Level III

What Makes a Car Detailing Job Great? Adaptive Multi-Stage Customer DOE (2020-EU-EPO-486)

Level: Power

 

Zhiwu Liang, Principal Scientist, Procter & Gamble
Pablo Moreno Pelaez, Group Scientist, Procter & Gamble

 

Car detailing is a tough job. Transforming a car from a muddy, rusty, full of pet fur box-on-wheels into a like-new clean and shiny ride takes a lot of time, specialized products and a skilled detailer.

But…what does the customer really appreciate on such a detailed car cleaning and restoring job? Are shiny rims most important for satisfaction? Interior smell? A shiny waxed hood? It is critical for a car detailer business to know the answers to these questions to optimize the time spent per car, the products used, and the level of detailing needed at each point of the process.

With the objective of maximizing customer satisfaction and optimizing the resources used, we designed a multi-stage customer design of experiments. We identified the key vectors of satisfaction (or failure), defined the levels for those and approached the actual customer testing in adaptive phases, augmenting the design in each of them.

This poster will take you through the thinking, designs, iterations and results of this project. What makes customers come back to their car detailer? Come see the poster and find out!

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Speaker

Transcript

Zhiwu Liang

Hello, everyone. I'm Zhiwu Liang statistician for Brussels Innovation Center for Procter and Gamble company I'm I'm working

 

For the r&d department. Hello.

Pablo Moreno Pelaez

Yep. So I'm Pablo Moreno Pelaez I'm working right now in Singapore in the r&d

 

Department for Procter and Gamble's

 

So we wanted to introduce to you this poster where we want to share a case study in which we wanted to figure out what makes a car detailing your grade.

 

So as you know, Procter and Gamble, the very famous company about job detailing for cars. No, just a joke. So we had to anonymize or what have they done. So this is the way

 

We wanted to share this case study, putting it in the context of a car detailing job and what we wanted to figure out here is what were the key customer satisfaction factors for which we then

 

Build interactive design that we then tested with some of those customers to figure out how to build the model and how to optimize

 

Job detailing for the car. So how do we minimize the use of some of our ingredients. How do we minimize the time we take for some of the tasks that it takes to do the job details.

 

So if you go to the next slide. And the first thing that we went to, to take a look. Yes.

 

Okay, what are the different vectors that a customer we look at when they they take the car to get detail and to get clean and shiny and go back home with a buddy.

 

A brand new car. What are they looking at clean attributes, they're looking at Shane attributes and they are looking at the freshness of the guy.

 

From a culinary view that we looked at the exterior cleaning the cleaning of the rooms are the king of the interior

 

The shine of the overall body, the rooms that windows and of course the overall freshness of the interior

 

And then we'll wanted to build this by modifying these attributes in different ways and combining the different finishes that it a potential

 

Car detailing job would give you wanted to estimate and be able to build the model to calculate what the overall satisfaction.

 

And also what the satisfaction with a cleaning and what their satisfaction with the shine.

 

Would be modifying those different vectors. These will allow us in the future to use the model.

 

To estimate. Okay, can we reduce the time that we spend on the rooms, because it's not important, or can we reduce the time that we spend on the interior or reduce the amount of products that we use for freshness. If those are not important.

 

So really, to then optimize how do we spend the resources on delivering the the car detailing jobs.

 

So in the next slide.

 

You can see a little bit with the faces of the study where

Zhiwu Liang

Yeah, so as popular as sad as the cart. The planning job company. We are very focused on the consumer satisfaction. So for this particular job.

 

What we have to do is identify what is the key factors which drive the consumer overall satisfaction and clean and shine satisfaction. So in order to do that we separate or our study design and

 

Data collection experiments industry step. First, we do the Pilar, which is designed to five different scenario. Okay, using the fire cars.

 

To set up the different level of each offer factors as a moment. We said, have to all of these five factor previous public described in the to level one is low and not as high.

 

Then we recruit the 20 consumers to evaluate all of the five cards in a different order. The main objective for this Pilar is check the methodology and track the

 

If the question we asked consumers consumers understand and provide the correct answer, and also define the proper range of each factor.

 

So after that, we go to the phase one, which is the extend our design space by seven factors. Okay. Some factors to keep, low, high level as we do the Pilar. Some extent to the low, medium, high because we think is more relevant to the consumer by including the more level in our factor.

 

And since we got more factor and from the customer design point of view, you will generate more

 

Experiments runs in our study so totally we have an it runs of the cost setting and each of the panelists. We ask them to

 

Evaluate still five but using the different order or different combination therefore accepted the custom design. When the consumer need to evaluate

 

Five out of the 90 I said him. We have to using the balance in company blog design technique and to use 120 customers, each of them evaluate five cars.

 

So totally this

 

120 customer data we collect we run the model identify what is the main effect. Okay, and what is the interaction in our model.

 

Then through that we three hours. Not important factor and go to the face to face to using the funnel identified the six factors and for course adding more level for some factor because we saying that low is not low enough in the faith from phase one study and middle it's not

 

Really matched to our consumer satisfaction. So we had some level of quality lol some factor level for the middle, high

 

Inserting currently design space, then

 

The face to design experiments his argument from the phase one.

 

Was that we get a different okay setting for the 90 different cars, then asked 120 consumer evaluate five in a different camp one

 

Through that we can remove non we can identify okay what is, what is the past.

 

Factor setting which have the optimal solution for the consumer satisfaction and clean and shine satisfaction. So as you can see here

 

We run the 3D model using our

 

Six factors setting.

 

Which each of them has played some role for the consumer satisfaction intense or cleaning as shine satisfaction.

 

For the overall. Clearly, we can see the cleaning ring and shine window cleaning in interior is the key driver for the overall satisfaction. So if consumers in the ring clean and window shine. Normally, either we all agree, he was satisfied for the

 

For our car detailing job and also we identified significant interaction.

 

Exterior clean and intuitive clean these two things combined together has different rate to the overall satisfaction with a clean satisfaction and the shine satisfaction model.

 

We identified very close, very significantly impact factors for clean

 

Clearly, all of the clean factor relate to the clean satisfaction and for shine also all of the shine one relate to the shine satisfaction.

 

But still the different perspective lighter clean his focus on the ring and shine is focused on the window. So from validating, we can have the better setting for all the car.

 

Relief factor which helpers to divide the new projects which achieved the best consumer satisfaction based on all of the

 

Factors setting. I think