Many in the industry are aware of the BioPhorum Digital Plant Maturity Model first published in 2016 and updated in 2018. This model is helpful in assessing the current maturity level of a manufacturing plant and providing a common language as well as the next mileposts for IT and digital transformation teams to work towards on an organization’s journey to Pharma 4.0 and the realization of the adaptive plant.
During the 2019 journey in the newly formed Xavier University AI in Operations Team (AIO), which I have the honor of serving on, we recognized that while the BioPhorum model is excellent at driving IT discussions, members and non-members agreed that there is more to digital maturity than digital aspects. So together, with collaboration that included the FDA, we started to envision what this model might look like specific to artificial intelligence (AI) maturity, knowing that more than the digital technology innovations would be included. We set out to release our vision at the Xavier AI Summit in August of 2020, and this vision came in the form of the AI Maturity Model Poster, which was made freely available.
The first important thing to understand when looking at the Xavier model, is that pharma companies need to already have some level of digital maturity. Consider a level 3 maturity in the BioPhorum Digital Plant Maturity Model as our starting point for our journey in the Xavier University model. The Xavier model takes into account tools and techniques like the digitization level across the company, analytics capabilities, and IT capabilities. It progresses through the maturity of data management like data quality, volume, source, structure, accuracy, and accessibility. The model continues by looking at governance and organizational factors like the ability to influence executive insights and strategic direction, Good Data Science Practices, technical capabilities and how to align to organizational goals, and how proficient teams are with AI-based tactics. Finally, the model culminates with culture and helps organizations analyze communication practices, procedures, and trust required to embrace change. The Xavier model facilitates discussions in organizations because the role of AI is a culture topic, a quality topic, a data management topic, a governance topic, and a C-suite topic.
Another crucial aspect to understand is that not all companies need to aspire to be at the top level. Organizations evaluate where they are and where they would like to be based on their goals.
The hardest part of AI acceptance is overcoming the status quo. If a company is reluctant to innovate, they cannot adopt AI. Innovation means the desire to evolve, to leave your comfort zone. If an organization does not have this culture, then AI projects will fail.
Need help figuring out where to start? Aizon’s AI Consulting Services can help you plan your path.
By Toni Manzano, Chief Science Officer for Aizon
Reference: AI Maturity Model Poster by Xavier University AI in Operations Team, August 2020
