Don McDowell, Director of Enterprise Sales at Albert Invent, brings 15+ years experience helping companies in the Chemistry and Materials Science industry leverage technology in the lab. Don shares his insights on how organizations can harness technology—including AI and Machine Learning—to boost productivity and achieve better outcomes throughout the R&D process.
Over the past decade, nearly every aspect of business in the Chemistry and Materials Science industry has been profoundly reshaped by digital transformation; however, one area has often lagged: R&D. It’s not due to a lack of need. R&D organizations have numerous pain points and bottlenecks due to disconnected, outdated, and manual processes. In fact, more and more companies are recognizing that embracing digitalization in R&D and integrating technology into their lab workflows may be the only way they will be able to remain competitive and relevant in this fast-moving marketplace.
In this post, Don McDowell, Albert’s Director of Enterprise Sales, shares his insights into the wealth of benefits Chemistry and Materials Science R&D organizations can realize by fully embracing digital transformation and why companies’ digital transformations may be saving the best for last with R&D.
5 Reasons Why R&D May Be the Most Rewarding Part of Your Company’s Digital Transformation
1. It will dramatically accelerate your innovation cycle and time to market.
Traditional R&D methodologies often involve a lot of educated guesswork, time-consuming hunts for information on past experiments and materials, and a ton of manual data analysis. This results in significant lost time and wasted energy. It also leads to a lot of dead ends that could have been avoided. Digitalization eliminates many of these struggles (and more) by enabling automation, data-driven decision-making, and predictive modeling to help scientists determine the best experimental design ahead of time—leading to faster and more efficient innovation.
For example, a huge frustration for R&D teams is when they spend a lot of time on discovering and developing a formula, only to find out much later that it includes hazardous materials that customers won’t be able to approve in a key market. With Albert, we integrate the regulatory information from the very beginning, so R&D teams will know whether a formula will meet regulatory requirements before they even begin.
Similarly, did you know at many companies it can take three-to-six weeks to produce Safety Data Sheets (SDSs) in advance of shipping samples to customers? This is a huge and extremely annoying delay that companies can avoid using Albert, which can produce accurate SDSs in mere seconds.
Here’s one more example for you. By leveraging Albert’s digital R&D platform, a company was able to find a formula to upgrade an adhesive for a large electronics company in a matter of seconds by typing in some property requirements and searching historical data from previous experiments. The winning formula had been tested for a different project years before but failed to meet that project’s requirements. As a result, the company was able to win the customer’s business and launch the product within 12 months—more than two times faster than the company’s fastest innovation cycle in the past (24 months).
2. It will uncover insights and connections the human brain can’t.
Yes, we’re talking about artificial intelligence (AI) here. As AI is transforming all other parts of life, it has enormous potential to transform R&D as well. The human brain is a powerful instrument, but not nearly as powerful as AI, which can recognize patterns and connections that are well beyond what’s within human reach. Not only can AI-powered algorithms analyze vast amounts of data and identify patterns among seemingly unrelated variables, but they can also propose innovative solutions to complex problems. Integrating AI into R&D allows companies to uncover valuable insights that might have otherwise remained hidden.
For example, many of our customers leverage Albert Insights as they formulate to help predict which formulations have the greatest chance of success before they even approach the bench. Harnessing AI and machine learning (ML), Albert Insights will automatically produce several different formulas and predict what each formula will do for a certain property the scientist is trying to achieve so they can begin their experiment with an extraordinary head start.
3. Collaboration will be much easier than ever before.
Aside from AI, nothing sparks innovation better than when two or more different perspectives come together to solve a problem. Collaboration is the key to new insights, but it is often a challenge for R&D organizations. Two scientists could be sitting next to each other in the lab every day and not have any idea what failures the other learned from. This lack of open collaboration is even more compounded when R&D teams cross borders. Digital tools and cloud-based platforms can make communication so much easier by putting everyone’s work in a centrally accessible location and by empowering teams to seamlessly pull in resources to support faster experimentation cycles. In this way, experts from different locations and disciplines can openly learn from each other and collaborate more effectively.
An example of the benefits of digital collaboration was on the heels of the COVID lockdown when a Shanghai-based team could not go into the lab. Using Albert, the Shanghai-based team could easily send tasks to colleagues in Spain, who could then follow the comprehensive processes outlined in Albert, do the experiment, and keep the Shanghai team updated every step of the way. Because of Albert, the team could continue their laboratory work and minimize the impact of the pandemic.
Another example, a high-profile one, of Albert’s ability to accelerate collaborative innovation is in how the platform helped select the best possible material for COVID-19 nasal swabs by instantly reviewing over 16,000 formulations and helping experts from two different organizations swiftly corroborate design. It helped produce millions of swabs in the battle against COVID-19 with a speed that could not have been achieved with traditional methods.
4. You will reduce overhead costs and unnecessary waste.
Did you know that most labs have more than 40% of their samples unopened due to over-ordering products that are in stock? It’s true. To avoid not having the necessary materials when they need them, many labs keep unnecessary chemicals and materials at every location, which is costly for disposal and creates unnecessary hazards in the lab. This is just one example of many where digitizing the lab processes can help to reduce overhead costs. For example, R&D teams are using Albert’s inventory management module to view current inventory items and quantities across multiple locations and labs, from the next building over to half a world away, eliminating the cost of over-ordering or delays in sourcing and sending raw materials from third-party vendors. Better resource allocation is another example of streamlining overhead costs as well. With R&D systems built for the end-to-end lab process, teams have the opportunity to delegate tasks to teams in different laboratories where resources or instruments may be more in line or available to meet project goals and timelines.
5. You will be able to protect your most precious intellectual property (IP).
Aside from their people, many companies would argue their most precious asset—besides their people—is their R&D IP. They want to know that this information will be safe, not only from outside threats but also from being accidentally lost or tampered with as scientists go about their work or if they leave the company. However, when this information is stored in siloed systems or even worse, in paper notebooks, it is highly vulnerable to being lost or compromised. By digitizing R&D processes in a secure integrated system, the risks lower dramatically.
IP security and protection were always an integral part of the design of Albert from the very first days. We went to painstaking lengths to safeguard our customer’s data in three different ways—when the data is at rest and being stored, when the data is in motion and being transferred, and when the data is in use and being processed.
- Each of our customers’ data is physically isolated and managed in their own cloud accounts and then encrypted using their own encryption key to encrypt and decrypt all data.
- We also use keyless deployment, which is a real standout security feature that Albert offers its customers. Keyless deployment deploys applications without embedding sensitive credentials or encryption keys directly into the codebase, making it more challenging for malicious actors to gain unauthorized access to critical information.
- And, finally, because Albert is built API-first, we can offer our customers an audit trail, which means if, for example, someone accidentally modified a formula in the system, we can go back and look at the history to access the formula data before the modification.
As you consider different options for digitizing your R&D, remember that digital transformation in R&D should go far beyond the adoption of software and tools; it should involve an end-to-end platform that integrates data from every part of the Chemistry and Materials Science R&D process. It should also involve a fundamental shift in how your organization approaches innovation. Born in the Chemistry and Materials Science R&D space, Albert can help you with both. We know what it takes to make a system that scientists, innovators, and business leaders will love. We also know that R&D data is much different than other enterprise data and accounted for that in our infrastructure, so no data is left behind. And, most importantly, we know how to partner with R&D organizations, so they get the absolute most from Albert’s powerful system.
While digital transformation is changing the game for all business functions, we truly believe R&D stands to gain the most. Not only can digitalized R&D dramatically accelerate your company’s time to market and improve the productivity and efficiency of your labs, but it can also open the door to innovation possibilities that never would have been discovered in the analog world. The value of that level of discovery can’t be quantified, especially today as the Chemistry and Materials Science industry works to tackle some pretty formidable and complex innovation challenges. With data, digital, and AI on your side, anything is possible.