CTC Leiderdorp, May 2017

What is wrong with automotive color data? [a green opportunity for companies to save time and money]

Ever wondered how damaged cars can be repaired in exactly the right color? Well, there is an entire world of professionals taking care of that. Automotive Repair Paint companies* dedicate a great deal of resources to enable “an invisible repair”.

This article is about the behind the scenes processes of refinishing cars in the right color. After reading this article you will understand the world of color in car refinishes a lot better and if you are involved in the process, how to save time and money. Lots of it. I will explain sustainable opportunities for improvement.

Cars of the same type and color are often manufactured in different locations with paint coming from different suppliers. This means that if you switched the doors of two cars manufactured in different locations you would probably see an unacceptable color difference. Therefore, it is hard for paint companies to supply paint in the right color that can be used to refinish both cars. That’s the reason why all major paint companies deliver so called variant color fan decks with 2 to sometimes 5 different variations of the same color. The number of different colors used in each paint product can reach up to about 30.000 with millions of euros/dollars being spent in these processes.

Paint companies do not supply car refinish shops all the individual colors. This would be too difficult and a logistical
nightmare. Instead paint companies deliver so-called mixing colors (typically 20-60 for each product) together with a large number of color formulas. A color formula tells which mixing colors and how much of them should be mixed to successfully imitate the color of the car to be refinished. A typical example of a color formula would be 50% Red, 20% Yellow, 10% Black and 20% White. Figuring out the type of mixing color and the exact amounts is called color formula development.

There are different types of mixing colors: solid mixing colors and effect mixing colors that give these special sparkling effects under different angles/lighting conditions. Colors that contain effect mixing colors are much more difficult to develop than colors that only contain solid mixing colors.

The data gathering and color formula development process

During the manufacturing of cars, the color of the cars is thoroughly checked in the factory with special measuring instruments called spectrophotometers. Despite these QC processes substantial color differences still occur regularly. You could assume that car manufacturers make this color information available for the paint companies so they can develop their color formulas easier. Well, they hardly do. The main reason car manufacturers do not want to disclose their QC information to the outside world is that making this information public could damage the image of their brand, which is quite understandable, of course.

Therefore, major paint companies have teams that collect information about car colors (let’s call this automotive color data). They do not have to monitor only new colors, previously delivered colors also need to be monitored to detect colors that deviate over time. This is a complicated, expensive and time consuming process executed by all major paint manufacturers, so executing the same activities.

In most cases the car color information-gathering process starts at the so-called points of entries (POE) where cars enter a country. These POEs are often harbors where ships deliver massive amounts of new cars. The teams of paint suppliers enter those POEs and start measuring the colors with their own spectrophotometers on different spots of the car. This information is then stored in databases. Because a measurement of complicated colors is not enough to describe the color sufficiently, paint manufacturers bend over backwards to collect physical samples of cars to visually check the developed color formula. The measurement information and the collected samples are then analyzed and used in color formula development centers to develop the right color formulas for each paint product. Major paint suppliers have dozens of experienced color matchers that use the measurement data, the physical samples, and computer programs to develop the color formulas.

How to save money?

The process of color formula development is very specific to every company and it will not be possible to save money by sharing that type of information. This process is different for each company because they all have their own products with their own specific mixing colors. The way companies can save substantial amounts of money (millions again), increase their quality level and shorten lead times is by sharing the collected automotive color data in the form of digital measurements and physical color samples. Color Technology Consultancy approached almost all of the major paint manufacturers and asked if they would be interested to participate in such an idea. Most companies were interested but eventually indicated that the costs associated with the color information gathering are secondary to its benefits. These perceived benefits come from the idea that controlling the color information gathering process will enable them to quickly provide the market with the right color formulas. This, in their own view, is a unique selling point. We doubt that very much. We think that the USP comes from evaluating the data in a smart way and the efficiency of the subsequent process to develop and distribute the color formulas. So, not the redundant data gathering process.

How to share color information?

One obvious way to share information is that paint companies simply make color information available for each other. This seemingly simple way however comes with many hurdles because each company uses different processes, measuring equipment, methods and data formats. In addition, sharing information between competing companies can be risky because intensive contacts could lead to accusations related to price fixing. In our view the best solution would be to establish an independent company or consortium that would take over the worldwide automotive color collecting activities of the paint companies. For easy reference, we denote this company or consortium as the automotive data broker. We guesstimate that the automotive data broker needs about 20-30 people worldwide. The data results of such a data broker will be made available to paint companies. Because contingency of the results is of crucial importance for paint companies, solid contracts with the automotive data broker must be made.

What information could be shared?

Currently, there are two types of spectrophotometers used in the automotive paint industry namely the “BYK-mac I” of BYK Instruments (BYK-Gardner) and the MA98 of X-Rite. Each of these instruments also has simpler derivatives mostly used in the car refinish repair shops. Since the measurements are taken at the POE, it would hardly require additional effort on the part of automotive data broker to take measurements with both devices. The extra costs would be minimal, and other measurements could also be taken such as gloss, orange peel, and even microscopic images. In addition, information like geographic location (GPS), Vehicle Identification Number and, of course, brand, model and year information can be determined and stored. This set of data is probably more extensive than what any of the individual companies currently collect.

How to make the data available?

The digital information (measurements and additional data) can be stored in cloud databases and the physical panels in a central library. Because each company will have its own data formats an interface must be created that enables the flow between the automotive data of the data broker stored in the cloud and the databases of the paint companies. There are multiple state if the art methods available to make such an approach possible and cost effective.

Can smaller paint companies benefit from this?

Usually smaller automotive refinish companies cannot afford the expensive procedure of collecting color information. For this reason, they usually spray out the color formulas of major paint companies and figure out (develop) color formulas in their own product. In this way, they bypass the color collection process but they must wait until a color formula from the big brother competition is available. Under reasonable payment conditions, the larger paint companies could agree to make the information available to smaller companies as well. This would strengthen the business case, but could be scary for the major paint companies. Perhaps a time delay to make the data available could mitigate this difficulty.

“A hostile takeover”

Suppose the color data broker is established as a startup and simply starts to collect the automotive color information in the way described above. This information could then be sold completely independent from the major paint companies. From our contacts with mid-sized paint companies we know they scream for this information and are willing to pay for it. Eventually, larger companies will also be interested because it is not their core business to gather automotive color data. Such an approach would require venture capital but we think a sound business case can be made for this model.

Interaction between the color data broker and other stakeholders

The color data broker will collect so much valuable information about the colors of car manufacturers that they must be interested to interact. Car brands and their color quality performance can be compared and used to improve internal QC procedures. Other stakeholders can be the insurance companies that will be interested in the color QC performance of car manufacturers


In this article, I simplified the steps of the automotive refinish process to focus on the issue that paint companies spoil substantial resources by being reluctant to share Automotive Color Data. We think the quality of car repair jobs can be improved while their costs can be reduced. The investments needed are substantial but manageable and will deliver crucial information needed to get the repair job done. In a shrinking market this seems like something to consider.

*Companies like:

AkzoNobel, PPG, Axalta, Kansai, Nippon Paints, Sherwin-Williams, Valspar

Further information

CTC thoroughly investigated the possibilities for automotive color data sharing in 2016. If you are interested you can contact us via email: info@coltechcon.com.

For more information about our services and other articles please refer to our website www.coltechcon.com

Roel Gottenbos is an experienced color research manager and developer of game changing color tools. He helps companies to improve their color processes from raw material to end product.