At Lux, we are in the business of helping innovation leaders plan for the future and make strategic decisions around emerging technologies and megatrends. We aim to create an ecosystem where innovators across industries can come together to share learnings. In this vein, Lux’s CEO Marisa Kopec recently interviewed Nouryon CTO Phil Clark to learn about his efforts to drive innovation within his own organization. Nouryon is a specialty chemicals company spun out of AkzoNobel in 2018.
Some highlights from the interview:
- We asked Phil about the emerging trends he foresees shaping the future of his industry. Phil said that any chemicals company is going to be paying attention to the regulatory environment. However, what is different today is that regulatory changes are taking place, even in cases where replacements have not yet been identified. He also mentioned how AI and machine learning are changing how Nouryon works from an R&D perspective but also how it supports and engages with customers. Lastly, he called out sustainability as no longer a “nice-to-have,” especially for Nouryon’s customers in home and personal care.
- We asked about AI and machine learning. Phil referenced a quote from a book called Quantum Supremacy — the book argues that quantum computers will not replace chemists but that chemists that use these types of machines will replace those who don’t. Phil thinks the same about AI and machine learning. These tools aren’t going to replace the need for chemists but will enhance their abilities and advance the science and insights from the data Nouryon has. With regard to machine learning, Nouryon has a lot of data throughout the world in Europe, Asia, and the U.S. that it is not fully leveraging. Once Nouryon gets these data into the cloud, it can build models that can become predictive of what Nouryon may need. For example, Nouryon has over 40,000 personal care formulations that, once it pulls these data into the cloud, it will be able to understand how the individual components of a formulation are impacting a given performance factor. Phil cited the ability to achieve performance consistency across different product formats (e.g., mousse or gel) as an important outcome — at least machine learning has been more effective toward this aim than trial and error.
- We asked Phil some tips and tricks for fellow innovation leaders based on his experience, as well as his secrets to success. Phil mentioned that he is a natural collaborator. He also emphasized the importance of getting input from others and starting from where there is a problem that needs to be solved. In the case of machine learning, for example, it is a tool that needs to be focused on where it has utility, like where there are vast amounts of data and where customized and personalized solutions are needed — like for home and personal care and food. It is important to build up use-cases and allow people within the organization to opt in. Phil emphasized how change management is also critical. Strong communication is really key here: bringing groups together to decide on what needs to be done. Phil also mentioned the objectives and key results (OKRs) methodology — a practice that comes down to the critical things an organization needs to be prioritizing. The “objectives” are things that need to get done, and the “key results” are the 3–5 things that if you deliver, you will meet your objective. Phil mentioned the book Measure What Matters as a crash course in OKRs.
To hear more about how Phil works specifically with Lux and why he considers himself to lead more like a Rugby official than an NFL referee, watch the interview here.