For as long as we can remember, when it comes to predicting future business trends, numerical data has been king
Not any more! Artificial intelligence (AI) has turned the concept of gathering as much numerical data as possible and developing the most sophisticated algorithms to digest it … on its head.
Instead of being focused on figures, the whole idea revolves around it being trend- or word-led. Rather than gathering vast amounts of historical data to predict the future, AI can monitor changing trends and habits in real-time to give a more accurate, wider reaching view of what’s to come for pharmaceutical firms.
This includes monitoring what’s being said across social media and other print and digital media. In this way, AI is much more reactive to ever-evolving global conversations and can turn this into actionable insights for businesses to develop more intelligent strategies.
AI has the potential to help the industry — which is dictated by long lead times and ever-changing population dynamics — to become much more efficient in its reaction to emerging diseases and outbreaks.
Using a theoretical example, AI could pick up that a large number of people in London are complaining of flu-like symptoms on social media.
This may predict an imminent large-scale outbreak, so would allow the local authorities and other associated bodies to react quickly to what may become an epidemic. It would allow the problem to be dealt with much sooner than traditional data-based systems permit.
As supply chains go, those within the pharmaceutical industry are high risk. Numerous variable factors, including weather, politics and geography, can significantly affect the production of life or death products.
It’s because of this that the most intelligent systems are required to limit risk. The availability of organic ingredients can be heavily dependent on global weather patterns, and the predictive nature of AI is key to helping identify such patterns as soon as they emerge, forewarning manufacturers and suppliers at the earliest possible time.
Ultimately, we’re talking about factors that are out of our control … but if we can optimise monitoring practices and responsiveness, we then have the chance of protecting our supply chains.
With an average of 10–11 years spent developing new drugs, AI could also help to reduce the lengthy lead times currently experienced for pharmaceutical products coming to market. AI permits much more sophisticated computational comparisons, the ability to search for different scientific markers and greater accuracy with the analysis of probability.
This could allow trials to be conducted much more efficiently, saving time and money. On top of helping to aid the production of drugs that are already developed, there is huge potential for AI to fuel innovation when it comes to formulating new drugs.
This is especially exciting when you consider the problem of evermore resistant forms of common diseases and the prospect of being able to keep up with these mutating variations much easier. In such well-controlled manufacturing environments, AI can also support more sophisticated monitoring of what is entering and leaving the lab, minimising contamination risk.
As with most new technology, a lack of understanding is currently limiting the uptake of AI and, subsequently, the realisation of its potential benefits. Reticence always stems from fear of the unknown, so there is a huge educational initiative required to help key decision makers and stakeholders wrap their heads around what they are dealing with.
Of course, there’s also the matter of numbers. Procurement decisions have long been made based on historical data rather than trends; and, of course, this appeals to CFOs. A more trend/word-centric approach can be more difficult for such people to get on board with; however, this can be solved by education and demystifying a topic that is actually quite straightforward.
For the pharmaceutical industry to realise the full benefits of AI and its application to the supply chain, board members and other key decision makers must make it a priority area for training.
It is also up to procurement consultants to recommend the best approach for each business, based on its unique pressures and needs. Once everyone is less scared of AI, we have a much better chance of making real progress with the technology.
Its applications will certainly vary according to the company in question, but there is no doubt that AI is the future of operating exponentially more efficient and more intelligent supply chain systems.