Updated: Jul 19
January 24, 2020
By John F. Conway
The purpose of this article is to drive the awareness of the art of the possible, a FAIR data and process environment for Chemical and Materials companies. Of course, it's applicable to all R&D organizations. But I am purposely singling out these two industry verticals. It’s a starting point for a set of crucial conversations, feedback, and ideas that can help drive excellence through captured scientific intuition (ideation, creativity), process optimization and harmonization, along with a dynamic, but FAIR, data and process environment. It is really about applying the Four Pillars of R&D Digitalization so that Materials and Chemical companies reach their destinations along their Journey!
So, why are many materials, specialty chemicals, and energy companies behind (5-15 years) when it comes to R&D digitalization? Do they(you) think they(you) are behind? Has it been OK to be behind?
I have made some observations over the past 15 years as a consultant, as a vendor and as a Head of R&D IT. Discovery, development, and manufacturing sciences are not easy and can be very complicated. I am not underestimating the challenges ahead, only pointing out that the longer companies wait the harder it will be to compete and be efficient.
One observation I have noticed is that where there are large volumes of materials or chemicals produced, there seems to be a lack of digital practices. Is it because (and of course I am oversimplifying to make a point) it’s “easy” to punch a hole in the ground and get billions of dollars of revenue? Or create tons of a specialty chemical from a plant site and the perceived efficiency gains are minimal? Is it simply just a lack of understanding or investment from corporate management? What is it?
Some feedback I have received is that “we don’t have the money pharma has”. I actually think that this is a poor excuse. I think many times it is actually a poor data/process and technology culture that has driven much of these decisions. There is so much room for improvement from a data and process culture perspective. With the right culture, then the strategy and finally governance an electronic or digital lab environment up-lift doesn’t have to break the bank.
The critical and interesting part of this is these scientific data environments for these companies are most conducive to an in-silico first approach. The efficiency gains realized could be in the order of 40-50 percent or about 10-20 billion dollars according to my calculations. Luckily, the opportunity exists to help some companies start this journey and learn from others' mistakes.
In the past, the forward thinkers in this space consulted with pharma companies and spent large amounts of money in HTE (high throughput experimentation) and other pharma-like data and process approach. The problem was they got many of the exact failed outcomes pharma did!! It was at that moment and obvious to me that they didn’t have a technology problem. They had a culture problem, which was preventing the data and processes from being recognized as an asset.
Another valuable lesson learned is change management. Change management is at the heart of making a successful transformation. Many if not most projects failed because of improper change management. The term transformation means everyone changes, not just the worker bees, or management, but everyone from the CEO to the new hire. It’s a true mind and culture shift. Culture eats strategy, period.
The transformation from a change management and adoption perspective will take some time, but the good news is that tools and strategies exist to help our clients and partners leapfrog some of this wait. Several scientific software vendors have built trans-industry solutions, ensuring a FAIR data and process environment with secure, instantaneous access to SaaS technology. No more waiting 6 months to get a server provisioned. The vision I and others had 5 years ago described in the white paper “The Virtual Biotech" is here and you don’t have to spend tens of millions of dollars upfront to get a scientifically aware platform ecosystem.
With a FAIR Data and Process environment you now have a Model-Quality Data (MQD) environment that will drive your much needed and applicable in-silico approach to research. In other words, you are working SMARTER not forced to work much harder at things that are mundane and not groundbreaking. Imagine 40% efficiency gains. Imagine reusing billions of dollars worth of IP and data and knowledge to make better and more informed decisions. If you’re a corporate executive and truly understand what I am saying here, then you should be ready to act! Yes, there is a platform ecosystem that’s not going to break your bank and that will save you millions and help you transform your company. You will have data and processes as an asset culture, and capture your employee's knowledge and know-how. It’s here, and the ability to get larger ROIs is in site!