The Sweet Science of Product Development

Welcome to the second installment in our series of articles shining a spotlight on the researchers and leaders working in industry to develop, commercialize, and deploy analytical technologies – transforming how we analyze and understand the world. 

Here, we speak with Colin Merrifield, Director of Product Management at BrightSpec. Merrifield began his career as a research and development scientist in the lab at a venture-backed startup out of the Massachusetts Institute of Technology. He then worked for a decade as an applications scientist in the pharmaceutical industry, before joining BrightSpec, where he is responsible for the product development roadmap: from voice-of-customer, prototyping and beta testing, through to commercialization.

Below, he shares his lessons learned developing and delivering the company’s digitized molecular rotational resonance (MRR) spectroscopy technology to the wider scientific community. 

How has your scientific training and lab experience shaped your approach to product development and management?
 

From the outset, my career as a scientist in the lab was in product development – in my first job I spent seven years helping to develop a new immunoassay platform. This experience helped me to learn the language of the lab, work alongside day-to-day operations and ultimately understand how someone might use a piece of technology within the larger context of a lab-based goal they’re trying to accomplish. This is something that comes in handy even now, as ensuring we understand how scientists think shapes how we develop products to solve their challenges.

A huge part of my job today is talking with scientists. This is in order to learn about the needs of a given market or application, before communicating these needs to our development scientists. My previous lab experience enables me to speak the language of scientists and understand the applications at a deep technical level, which helps to ensure we’re building the right product for the community.

Would your younger self be surprised if they could see you in your current role?
 

Yes – I thought I'd be a scientist my entire career! I did consider pursuing a PhD once, but serendipitously I was offered an opportunity with a company in product management. At that time, I didn't even know what a product manager did, so I did my own research to find out. The company told me, “You have the technical background, with a firm grasp on how this technology works and how people employ it – we can teach you the product marketing side of the equation.” Everyone on that team was also a scientist, so having that technical and scientific foundation really is crucial when working in these industries.

What is the most challenging aspect of your role? 
 

Our strategic goal is to democratize MRR technology and allow it to diffuse across multiple scientific industries – to do that I need to be connected to all of the different aspects of our business. I like to say that product marketing is a function that sits at the center of a spider’s web, requiring a high level of organization and planning to ensure products meet customer expectations.

What do you consider the biggest challenges in translating scientific technology into commercially viable products?
 

Managing the complex interrelationships between market requirements can be challenging. Sometimes a particular feature or benefit cannot be partially or fully realized without a supporting ecosystem composed of additional features.

I think it’s also important to bridge the gap between new and expert users. On the product development side, you have expert users and scientists who use the technology and immerse themselves completely in the nuances of how it functions. This enables us to gain an idea of where customers might need extra support and pre-empt pain-points. At the same time, this can also make it hard to step back and look at the technology from the perspective of a newer customer, and to recognize the areas that may not be as intuitive on a wider scale.

The analytical science sector is considered relatively conservative. Has this presented any challenges when bringing a new technique to the market? If so, how have you tackled this?
 

Regulatory frameworks can be complex to navigate, and real change is therefore often difficult to achieve. Other barriers can emerge from the huge bodies of historical data that are available, which often provide perspectives on our current ways of working. The introduction of a new technique can break established historical patterns of data, and as a result, maintaining continuity becomes more difficult.

To fully understand adoption barriers, it is therefore crucial to engage customers early in the development process. While it’s not always possible to speed up the replacement of technology within labs, ensuring that there aren’t artificial or avoidable barriers to adoption is key as this helps us to understand how new technology can fit into an existing workflow. Engaging with thought leaders in relevant industries as part of this process is also important. Scientists look to other scientists, and having evangelists outside of your organization is important for building credibility and critical mass within an industry or application.

Do you have any tips for maintaining an innovative edge while ensuring the technology remains scalable and meets regulatory and market demands?
 

Thoughtful architecture and modularity, both in system and software design, as well as the supporting business and support functions, is key to ensuring that a technology or platform maintains a level of agility over its lifetime. Additionally, the ability to react to new customer needs or requirements or exploit new commercial opportunities is key to maintaining a successful product line.

What is the most important quality of an innovative team? 
 

Cross-functionality – innovation in the analytical world today requires input from all areas of a business to be successful; R&D, engineering, software, marketing, sales, service and applications.

As someone who’s been involved in both science and product development, what trends do you see shaping the future of analytical technologies – especially in the life sciences and pharmaceutical industries?
 

Automation and more holistic solutions are set to shape the future.  With corporate restructuring and pharmaceutical and life science portfolios changing and reprioritizing, being able to employ solutions immediately out of the box (and with as few hands as possible) is an important part of the way companies consider new techniques today. Furthermore, the drive towards data science and big data will always alter the technological landscape.

What is missing from the spectroscopy toolkit today? 
 

For some time, MRR spectroscopy has largely been overlooked as a spectroscopic technique. More recently, the confluence of several enabling technologies has brought this to the modern analytical arsenal, and for many applications it’s going to be an enabling technology for structural analysis. 

For scientists looking to move from the lab into roles that blend science with business, what advice would you offer?
 

For me, roles that allowed me to gain insight into the commercial world were a great stepping-stone; both in terms of the way that industrial science is executed and the way that technology companies sell and deploy solutions. This area of field applications science provides valuable exposure to both R&D and more commercially focused roles.

I would also recommend gravitating towards startups; you get the ability to wear multiple hats, teams are more cross-functional and supporting customers requires all hands-on deck. With this, there are naturally more opportunities to learn and get increased exposure to the commercial side of the business.

Ultimately, It's important to keep an open mind about where your career path might take you. Grasp the opportunities that come your way, and learn new skills that build upon your existing background – to understand not just the science, but also how to communicate it effectively. Taking your hard skills and learning additional softer skills can help you to provide unique value and benefit to an organization.