Digitalization: Are We Seeing Results?

Upon reflection, I've noticed a consistent gap between the grand vision and the actual results achieved. There are several reasons for this, but today I'd like to highlight some fundamental questions we may ask ourselves for an efficient and effective digitalization journey, or what I prefer to call the data strategy and its execution:

1. Are consistent and common principles defined for all functional areas and projects? For example: Do we have mandatory standards for data, interfaces, and architecture to enable openness, interoperability, and flexible replacements of solutions? Do we have set data centricity as an overarching principle with all its consequences?
2. Do we have reliable blueprints for data integration architectures, that work consistently across functions and at an enterprise scale?
3. Is digitalization not only understood but also consistently executed across functions, with a focus on business value rather than just IT or technology?
4. Do we have a common data language that allows knowledge from different areas to be shared in a clear and machine-readable way, also for the use of advanced AI technologies?
   
5. Does our data strategy include a "FAIR Data Strategy"
   
6. Does our conception include practical and proven implementation experience? Do we prioritize data-centricity when selecting and building solutions?
7. Does our company's data office have the necessary cross-functional presence and influence?
8. Are we managing and leading the change? Ultimately, people drive the change, and they need to be emotionally invested and take responsibility.
9. Are managers and employees involved in a way that they understand and agree with the goal and the journey? Do we have a common goal?
10. In my experience, the speed of digitalization is often hindered by the lack of precise answers to these questions. For instance, having a clear picture of the common goal creates connection and orientation. As Seneca once wisely said: "If you don't know the direction, no wind is right for you."
11. We also need a common language within our organization. When different functions use different terminologies or have different interpretations of the same terms, it creates fractures. This not only hampers organizational efficiency but also affects collaboration, data integration and systems interoperability.

How Connectivity Shapes the Future of Digitalization

In the previous section, we discussed the fundamental questions and challenges in digitalization journeys. Now, let's dive deeper into the importance of connectivity and standards in achieving successful digitalization.

Connectivity is key in the digital age. However, many organizations still face difficulties with proprietary interfaces, limited access to systems and data, and organizational silos. It's puzzling to encounter such obstacles in a time of digitalization, where data centricity and data assets should be at the forefront.

To overcome these challenges, open standards and cross functional collaborations on data enable seamless innovation. The future of business operates like an organism, with cells working together, creating new cells, and discarding what is no longer useful. We can only achieve this through common principles, a result driven collaboration, and an interoperability based on standards. Teams need a shared direction aimed at benefit and business value.

In the pharmaceutical industry, the Allotrope Data Standard for laboratory data and the IMDP Ontology have been introduced to leverage seamless innovation, to fulfill regulatory requirements and to enhance patient safety.

Setting the foundation for the digital laboratory

The Allotrope Data Standard enables the systems interoperability and harmonization of data across the diverse instrument landscape in pharma laboratories. This sets a foundation for the digital lab, which will finally lead to faster and more informed decision-making, to automation and efficiency gains and to the acceleration of drug discovery.

In addition, scientist will be able to analyze and interpret large volumes of complex data more efficient. They can gain new insights and leverage the capabilities of Artificial Intelligence. With the connection between digital laboratories and clinical data, scientists will gain deeper insights into disease mechanisms, identify novel drug targets and develop personalize treatment approaches for patients easier and faster.

Enabling collaboration and interoperability within the pharmaceutical industry

The IMDP Ontology is a project, initiated by the Pistoia Alliance, and involves major pharmaceutical companies. The goal is to enable seamless interoperability and harmonized collaboration within the pharmaceutical industry.

Ontologies in general enable the precise description of terminology and data concepts in an unambiguous manner. While the term "ontology" may sound technical or complicated, it is a concept that Google has successfully utilized since its inception. Google's use of ontologies has allowed it to better understand the semantic meaning of search queries and provide relevant information. Similarly, in the pharmaceutical industry, ontologies can ensure that all stakeholders, from different areas, organizations, and regulatory bodies, can speak their own language while still understanding each other.

The Power of Ontologies in Shaping Our Future

Ontologies may sound technical or complicated, causing some people to tune out. Coming back to the Google example before: By leveraging ontologies, Google can better understand the semantic meaning of search queries and provide relevant information. For example, when someone searches for "apples," Google can recognize that the query may encompass different types of apples, recipes using apples, or the health benefits of apples.

Drawing inspiration from this, we can imagine the potential of ontologies in the pharmaceutical industry. Based on the IDMP ontology, all stakeholders in the industry, including individuals from different areas, organizations, and regulatory bodies, can speak their own language when discussing products or new substances while still understanding each other. This fosters collaboration and effective communication across the industry.

Now, let's consider the added value of Large Language Models (LLMs) such as ChatGPT, which are widely discussed today. Ontologies enable us to pour the knowledge found in people's heads into systems and make it machine-readable. This concept of "interoperability by design" allows us to use LLMs more efficiently and effectively with our own data. It's worth asking ourselves how we can leverage LLMs to enhance our work and decision-making processes.

The Allotrope data standard and the IDMP ontology are maybe small, but important contributions to driving more innovation, accelerating processes, and ensuring patient safety.

I understand that some of these points may seem technical or specific, perhaps even considered “details” from a management perspective. However, I firmly believe that if we want to understand and shape the future, we need to grasp the connections between (technological) innovation, leadership, and development. This understanding should extend to our personal growth, collaborative efforts, and organizational strategies having the big picture in mind, but acting one-step at a time. Perhaps 4 principles can help as guard rails in these increasingly fast-paced times: Focusing on Results as the direction, continuous self-improvement based on building trust and taking responsibility.

What is your current focus in shaping the future? Whatever it might be, no matter the many tasks and responsibilities we have, each step we take matters and gets us closer to the goal.