The Fundamentals of Commercialization
The three elements you need and some luck doesn't hurt
When I was working in product development as a chemist, we would often refer to product commercialization as “getting lucky,” because there didn’t seem to be any specific reason for why certain products did well while others flopped. Part of the luck was also in the short timelines for commercialization. If an executive wants something new out in the market competing and gaining revenue in 2 years then you basically need to be finished in the lab by the end of year 1 and running manufacturing and customer trials in year two. Getting all your technical “ducks in a row” within a year can be challenging both from a design of experiments approach (statistically doing enough experiments to generate a model) or a parallel hypothesis driven approach (carrying 3-4 hypothesis in parallel until a winner emerges). Some luck with your customers and suppliers doesn’t hurt either. I’ve seen plenty of failed product launches because all three of the following elements were not there to start:
Technology: Something that underpins your product either a patent or a trade secret. This is often the value you bring to a customer.
Infrastructure: Your suppliers, your manufacturing operations, your raw materials, your transport and packaging.
Market: The people willing to pay for your stuff and their customers
Getting these three things to overlap might seem obvious and yet in practice you’d be surprised at how often when running a manufacturing trial you and the plant engineers realize you need $100k in CAPEX that no one thought about, there is a contamination concern with other products that get produced on the same equipment, or no one saw the permitting process taking 6 months to complete.
You’ll also notice that there are areas where there is partial overlap and this is typically where most product teams exist in the beginning, at least in the chemicals space, and becoming more aware of your deficiencies can help lead to more successful product launches, more customers, and ultimately better returns for your shareholders.
Overlap 1
This is where a lot of legacy businesses exist in their efforts to develop new products for new customers and to drive growth. The technical talent and the infrastructure needed to support new inventions are typically linked closely enough to where any “new” shouldn’t be too new. You might be hear keywords such as, “utilizing existing assets,” or “let’s keep this in-house,” when new projects are being discussed. These limitations and constraints are often hard both in going past them leads to failure and developing within them is difficult. This is why most innovation appears to be incremental in the large established chemical companies or innovation might actually be technical service.
Overlap 2
Overlap 2 is where you theoretically have a willing market to buy your product and your technology supports it, but you don’t have manufacturing capacity AND/OR you don’t have a supply chain that can support your product. I think this where most venture capital funded companies are situated and I think the underlying assumption here is the following:
Our technology is [insert synbio, enzymatic catalysis here, or whatever] and there are a lot of benefits from a climate change and efficiency perspective. It provides similar or better value to our potential customers. We just need to figure out how to both sell and build the manufacturing capacity for our products and validate them with our customers. All that stands between us, and success is capital.
This is the trickiest place to exist because in some cases those assumptions about capital being the solution is true as long as the founders/operators fully understand their business and supply chain. Founders often know their technology and their market better than their investors, but the supply chain and infrastructure needed to get them there is usually the big “don’t know what you don’t know.”
It’s tricky because there these unknowns come back to making costs difficult to figure out. If you don’t know your costs, you don’t know your profits. This overlap partially assumes you have a product that a customer has trialed at the lab scale and is interested in buying (product-market fit). If you are here, I’d advise you to figure out the following as soon as possible as they impact your cost structure and ultimately your profitability and return to your shareholders (non-exhaustive list):
Customer pricing*
Supplier pricing*
Shipping of raw materials and finished goods*
Deciding on using a contract manufacturer
Building your plant**
Permitting with the requisite regulatory body and local government**
Figuring out packaging and customer requirements
*The pricing can change every few months and this can cut both ways.
**Timelines for building a plant can be pushed due to delays in permitting or delays in parts needed to build your plant (e.g., a pump is backordered or some random part critical for everything else is 4 weeks backordered).
The assumption that $100 million dollar will solve the supply chain/manufacturing issues of start-up in the chemicals space is naive at best and borderline fraudulent at its worst. Prior knowledge of operations will be helpful here. The key is not running out of money before you can solve all your problems.
Overlap 3
This is where you know you have an ability to manufacture something and a willing market who will buy your product, but you just don’t have the technology to bring it to market. This is where most PhD scientists want to be their whole careers. This area is where developing the science of something is fun because going from lab to pilot to manufacturing at scale and commercialization can be done in <5 years.
This overlap area is typical for specialty chemical development or custom polymers. This usually looks like a customer approaching a manufacturer and outlining some high-level needs, what they might be willing to pay for it, and their expected volume if they can successfully commercialize a product.
Chemical companies or manufacturers use all of this customer information on how to prioritize their targets and opportunities (T&O). What this all translates to is not enough technical resources being staffed to as many T&Os as possible (within reason). If you can leverage some sort of accessible computational system, an AI model that was developed in-house, or even a laboratory information management system to assist your technical team in moving faster those early investments that feel extravagant can eventually pay dividends. As projects progress uncovering what opportunities look more realistic and then dedicating resources to bringing that revenue home.
The Lucky Zone
Even if you can get all your infrastructure, technical ability, and willing customers to converge a bit of luck can really pave the way for commercial success. Luck can manifest itself in a myriad of ways, but here are some instances where I’ve gotten lucky in the past:
Samples arrived at a field trial on time and correctly labeled and the field trial started on time and the value seen in the lab translated into the field.
Manufacturing trial went smoothly with no issues, started on time and finished early.
Customers formulated with samples in their lab and found the same value in testing as had been hypothesized during my own development.
Alternate supplier pricing came in significantly lower than expected and their raw material exceeded expectations during testing.
Your marketing team’s information was correct the first time.
The instances that I’ve felt that I’ve been lucky in the past was because things that were mostly outside of my control went in my favor. I’ve seen/heard of plenty of instances where the opposite has happened and months or a year of work ends up getting taken out by some bad pricing from a supplier or value not be seen in the application testing. Success is not guaranteed even when you’ve got everything going your way and a sometimes you just need a bit of luck.