Predictable performance

How can we collect and augment data more innovatively to make predictions for real world surface performance more accurate?
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Countdown visual
Countdown visual


What would the world be like without paint? In addition to the color and beauty they bring into our lives, paints and coatings provide protection for walls, bridges, buildings, ships, automobiles, energy infrastructure and even home electronics.

They also offer a way to add additional functionalities – like resistance to heat or increased aerodynamics and much more – to the materials they cover. So, we really do rely on paints and coatings. To ensure all our coatings are up to the long-term challenges they face and provide our customers with the best results that live up to their needs and expectations, we need effective ways of predicting the real-world performance of our coatings. This will help us speed up the process of bringing new products to market.

The limits of traditional methods of testing

We have more than 200 years of experience behind us. Over that history, we’ve developed many ways – often based on empirical methods – to understand how our current products will behave over time, how long it takes for colors to fade and when surfaces will need a recoat.


During development, we often rely on accelerated testing of our products under laboratory conditions, but we also test them under extreme external conditions by leaving coated surfaces out in the elements to see how they survive over time. These are tried and true methods, appreciated and often specified by our customers. However, we’re always looking to do it better and faster, allowing us to accelerate the development and introduction of warranted products.

Better ways to measure and predict

To improve the acceleration of our innovations, we’re looking for your unconventional solutions for predicting performance. We know incredible advances in digital technology have the potential to dramatically change and improve the ways we measure and predict how paints perform in the real world.


Incorporating new, faster or more accurate ways of collecting and augmenting data from both new and existing sources into our products and processes will help us bring better solutions to our customers, faster.

Outside the can at AkzoNobel

Curious what we’ve come up with already? Check out our Intertrac Vision tool. We augment marine ship positioning data with hull performance data and globally collected environmental data to generate predictive models for the performance of marine anti-fouling coating. This helps predict future performance bespoke to each ship, allowing for a superior customer value proposition directly related to ship fuel savings. Read more here.

What we’re looking for

  • Your solution is not just in your head. The concept has been fully developed and is ready to apply
  • Scalable, cost effective and easy to implement around the world


Should include one of the following elements:

  • New ways of creating and/or collecting real world data
  • Extracting new insights from (existing) data sources
  • Improved or accelerated testing
  • Predictive analysis (specifically applied to paints and coatings)

Have you got the solution?

Help us generate and collect surface performance data quickly and accurately. Work with us to accelerate our testing and formulation time, as well as develop new ways to monitor coating performance in real time, or even predict future behavior.
Join us

We are closed for submissions, we will announce the finalists on April 11!


We respect ownership of Intellectual Property (IP). IP that you already own prior to the Paint the Future Challenge remains yours; and similarly, our existing IP remains ours. In addition, our starting point is that both parties should have appropriate rights in what we create together during the Paint the Future Challenge. If you get invited to the final of the Challenge, we will communicate clearly what specific IP terms will apply.


Whilst we respect IP rights, we also value the open sharing of non-confidential information, and building on contributors’ ideas. This is what makes the Challenge useful for all participants, and contributes to identifying successful innovations. This means that during the submission phase, your submission, and the information you share with us, will be received by us only on a non-confidential basis.