Walk into any casino, and the logic is undeniable: given a large enough sample size, the house always wins. Jackpots are paid out, big hands are won, but this does not matter. Casinos always trust the maths. They trust the data; and they always come out on top. In the highly regulated world of Pharma Quality, we are still operating in a landscape of manual entry and fragmented processes, trying to drive decisions while comparing apples to oranges. We aren’t just missing the trees for the forest – we’re missing the data for the noise. To move from reactivity to proactivity, and ultimately to agenticity, we have to stop fearing the machine and start harnessing the data. After all, in a time of rapid change, standing still is the most dangerous bet you can make.
How you perceive the world is dictated by a combination of past experiences and the wiring of your brain. An artist sees a landscape in colour and emotion; a lawyer sees it in policy and protocol; an engineer sees functionality and mechanics. Me? I see the world in numbers, patterns, and data. Working at the intersection of technology and digital transformation has opened my eyes to a startling paradox. In the highly regulated world of Pharmaceutical Quality, we operate under the strictest methodologies on earth, yet we are still drowning in manual entry and fragmented processes. We are trying to drive million-dollar decisions while comparing apples to oranges. We aren’t just missing the trees for the forest – we are missing the data for the noise. Zooming out from project intricacies I can see the opportunity for standardisation and the chance to let data drive decisions in an attempt to move from reactivity to proactivity and maybe in the future even agenticity. I think I have just invented that word.
AI has dominated the world news the past couple of months, with its speed of development and disruptive capabilities. Whilst I have seen this lead to job security fears and lack of autonomous, critical thinking, I think it also opens up an alternative pathway where it can be harnessed to transform business process and critically, decision-making. All you have to do is step foot into a casino to understand that given a large enough sample size, maths always wins. Afterall, casinos would not exist if they did not trust the numbers. Films like Moneyball have also shown how data can be used to build a successful sports teams, even though the human element is inherently more unpredictable.
I work in the world of Quality within the pharmaceutical industry and I have seen how manual data entry and mis-aligned processes introduces variations and inconsistencies. What you end up with is a very large, unharmonized set of results from which it is very difficult to identify trends and therefore fix them. Whilst very manual and mis-aligned processes between different sites works, you are often left being reactive when something goes wrong. You end up trying to compare apples with oranges and cannot see the tress within the forest. This does not set you up for success in a digital world. The approach is outdated and you are not using technology to its full potential.
Mindset change does not happen overnight and a full scale digital transformation takes time and is complex. Afterall, no one likes change. Organizational size and starting point can also make the task seem extremely difficult, if not impossible at times. Companies that aspire to data-driven decisions, don’t just require digital transformation, but also business transformation. For me though, the benefit of having a unified, digital system which allows the data to drive decisions is worth the time effort, as the future efficiency gains are immense. In the world of quality, accuracy and efficiency not only leads to cost savings, it more importantly leads to patient outcome, allowing critical medicines to reach the consumer faster and more safely. As Charles Darwin once said, “it is not the strongest of the species that survive, it is the one that is most adaptable to change”. I think that time to change has never been more prominent.
I am also a thinker and can see a world of industry harmonization. Given all companies are adhering to the same set of rules and guidelines, why can the end outcome be so different? Does it have to be different? To me, the process differences arise from legacy ways of working that are accepted and maintained as that is the status quo. It was working before so why change now given the time and effort this will require. However, an aligned industry allows data to drive decisions and comparisons to be made. This is good for the industry. It sets a benchmark from which comparisons can be made, driving everyone to be quicker and more accurate. In the world of quality, process is not about gaining a performance advantages over competitors, it is about keeping consumers safe. Therefore, why can’t the industry work together to be more efficient and more accurate as it will mutually benefit all parties. I know this seems like a pipedream, but all change starts with an idea.
The path to industry standardization starts with a simpler, standardized process across an organization and eventually (hopefully) across an industry. The right data allows the right decisions to be made. Standardization allows apples to be compared to apples so any inferences or decisions made are targeted and accurate. They will likely address the root cause of the problem. This approach is the same for any scientific experiment. The more variables you can control and the more reproducible your method, the better and more accurate your end results will be. You can assess if it is your independent variable that is causing an effect. Industry harmonization also allows benchmarking and pulse reports to be generated. This allows companies to identify how they compare to others, which in turn will drive changes that hopefully lead to efficiency gains. Transparency leads to competition which leads to innovation, which drives efficiency and eventually a mutual benefit for everyone. This is the proactive capabilities digital data can provide across an organization or an industry.
To me, the final step in the data driven journey is agenticity. AI. Everyone’s favourite buzzword. AI is a truly revolutionary capability which if harnessed correctly can re-shape an industry. Data driven proactivity is most often achieved by analysing the result, the end product. This of course takes time to reach and there is still plenty of human involvement in the process which introduces potential data errors or inaccuracies. Where AI is truly unique is it can be involved throughout the whole journey. It can tell you if data appears inaccurate, or is not aligned with what others have done previously. It can assess the data in real time to provide actionable insights which otherwise would take a long time to collect and analyse. It can introduce real-time compliance, reducing the time needed for quality control checks and human intervention. It can identify bottlenecks before they happen and suggesting corrective actions based on an entire database which it is constantly analysing and monitoring. A task which would be nearly impossible for a human to do. You can innately build compliance into a system, reducing manual involvement. In the world of quality, this is like having a real-time in-system auditor which would be huge for the industry as it would reduce regulatory findings and the time taken to prepare for such inspections. Achieving agenticity will require trust in the system and process. Trust in the AI and its output. Whilst this technological capability might not ready yet, given the speed of development, it will not be far away. The biggest change and barrier to entry will be human mindset.
Agenticity cannot be achieved without a unified, data driven system. This will take time, effort, and a large scale shift in mindset. Maybe even industry harmonization. To me though, it is the future and importantly the winners of the change are everyone. Everyone benefits. “In a time of rapid change, standing still is the most dangerous course of action.” – Brian Tracy.
