More data
for more users
means more

Because data-based decisions are better decisions, Boehringer Ingelheim is establishing a data ecosystem called “dataland.” It will help all employees make data-driven decisions and improve the overall effectiveness of the organization. The uses so far are already demonstrating the system’s value.

Whether it’s recommending products or moving unwanted emails to a spam folder, algorithms are part of everyday life — and not only online but also in many areas of the analog world. Consider, for example, the amount of digital data generated and recorded at every stage of the modern industrial process — whether in production, communication, customer contact, accounting or research. Algorithms analyze this data to yield new insights — detecting patterns and making connections that a human brain would never identify because of the sheer volume of information involved.

“Technology gives us a better understanding of which processes have an impact on the company’s performance, and how,” explains Ferran Urgeles, Program Manager of the dataland initiative at Boehringer Ingelheim. The goal: better decisions in every business area and every step of operations, from research to production, sales and beyond. “This will let us unleash the full potential of dataland that will provide insights we would have never discovered otherwise.”

And of course, the ultimate aim for Boehringer, Mr. Urgeles says, is “to help us develop medicines faster and more reliably.”

A secure, accessible data ecosystem

The dataland ecosystem is driven by a digital platform that collates data from every area of the company and makes it immediately available for uses like simulations and data analyses in a manner that is easy to comprehend.

“All of the data in the dataland ecosystem is put through data security and compliance checks and is protected using cutting-edge security measures,” Mr. Urgeles says. The ecosystem, which has been up and running at Boehringer Ingelheim since the end of 2022, revolves around practical use cases. This bottom-up approach ensures that the platform contains features and functions relevant on a day-to-day basis.

A simplification of the inner works of the highly complex strategic initiative BI dataland

The end-to-end data ecosystem?

Data Sources

After knowing what to build, boxes which contain the necessary bricks have to be identified first.

Raw Data

Second, all boxes are emptied, and the contained bricks collected in a single place as a „raw“ pile.

Cleansed Data

Some bricks are broken or don’t fit to the others. By „cleansing“ the pile, these are removed.

Curated Data

To speed up the building process the bricks are „curated“, this means to sort them by size, color and usage.

Pre-assembled Data

Building can be further simplified and sped up by „pre-assembling“ first pieces that are needed for final assembly.

Data Simulation & Analytics

Finally, the pre-built pieces and bricks are used to assemble and finalize the planned building.

“The biggest challenge is not so much the huge amount of data available,’’ Mr. Urgeles says. “It's about how it is structured so that it can be used easily by anyone in the company.”

But a data ecosystem cannot work on its own, no matter how well organized or comprehensive it is. “Our employees need to have the right skills to interpret the data,” says Brigitte Fuhr, Head of Boehringer Ingelheim’s Central Data Science Department. “That’s why proper training is so important.”

To achieve this end, Boehringer Ingelheim set up the “Data Science Academy.” “The academy provides training for users of any experience level – from veteran data scientists to people just getting started,” explains Mrs. Fuhr.

A data-driven approach to customer engagement

Timmo Andersen,
Head of Human Pharma Regions at Boehringer Ingelheim

Next Best Action (NBA) AICER of Human Pharma Regions is the first dataland application to go live, developed to support sales and marketing. More than 250 sales employees in Spain are already using the program to find the best approach to customer engagement and retention.

The program draws in data from a variety of sources and uses data science functions to optimize the calling plans of the employees. NBA has already boosted Boehringer Ingelheim’s performance, according to Timmo Andersen, Head of Human Pharma Regions at Boehringer Ingelheim.

“Our customer conversion rate is up by almost two percent since the application went live,’’ Mr. Andersen says, “while the sales growth rate has gone up by 20 percent. That is equivalent to a net present value of 11 million euros, and even more importantly gives a lot of customers a next level of optimized customer engagement.”

Data-driven improvements to processes, Mr. Andersen adds, “allow us to collaborate on customer engagement based on insights — not on opinions.”

Selecting sites for clinical studies

Dr. Lorna Hart,
Global Lead of Clinical Feasibility and Head of the Pegasus project

One of the biggest strengths of dataland is the way it pulls data from across the company to find new connections. Take the dataland application “Pegasus Site Identification.” It identifies the best possible sites for a clinical trial, by analyzing performance metrics of the countries under consideration and simulating patient enrollment for better planning of trial timelines.

“This application makes it a lot easier for us to identify the most suitable countries and investigators for our studies, and will speed up the process significantly,” explains Dr. Lorna Hart, Global Lead of Clinical Feasibility and Head of the Pegasus project.

And dataland has many more possible applications to offer when it comes to clinical trials. Once a study is underway, it’s important to find the best possible way to present and view the data that it generates. An application called the “Clinical Development Cockpit” is designed to do just that.

Speeding up personalized medicine development

George Okafo,
Global Director of the Healthcare Data and Analytics Unit at Boehringer Ingelheim

Accelerating and improving product development, while reducing risks, is one of the biggest challenges for the pharmaceuticals sector. Having access to high-quality data, and the ability to evaluate it, is crucial to meeting this challenge.

Biobanks, for instance, contain huge amounts of valuable data. A biobank is a digital database of actual patient information — anonymized, of course — about the properties of materials such as tissue samples and other data gleaned from electronic health records. Until now, Boehringer Ingelheim has been unable to fully exploit these external data sources in a streamlined and integrated manner. Dataland provides this capability in ways that will enable the company to accelerate the process of developing new medicines in a more personalized manner.

George Okafo is the Global Director of the Healthcare Data and Analytics Unit (part of global Computational Biology and Digital Sciences) at Boehringer Ingelheim. He and his team are developing the user-friendly “Healthcare Data Analytics and Disease Translational Accelerator” platform to make the data held in biobanks available to everyone at Boehringer Ingelheim. It goes live later this year.

“These insights,” Mr. Okafo says, “will help us develop personalized medicines and make sure that they reach patients faster than before.