Photo by Patrick Tomasso on Unsplash Scaling a biotech platform requires getting a group of people from different backgrounds and perspectives to understand a common vision and plan. But it can sometime be difficult to recognize where the differences and gaps are. So, how can you make sure you’re communicating all the things that youContinue reading “Structuring communication with stories”
Author Archives: Jesse Johnson
Communicating with Stories
Image by Gerhard G. from Pixabay Scaling a Biotech research platform requires getting many people from a wide range of backgrounds and mindsets to adopt a common vision and plan. The more variation and inconsistency about what your colleagues think they’re working towards, the harder it’s going to be to coordinate the work that willContinue reading “Communicating with Stories”
Distributed Metaphors
Photo by Omar Flores on Unsplash Scaling a biotech research platform requires combining a collection of different software systems and components into a single coherent whole, aka a Chimera Data Platform. To keep this system maintainable as it grows, it needs enough consistency to ensure that a small group of developers can quickly understand eachContinue reading “Distributed Metaphors”
The Blind Philosopher’s Database
Photo by Nam Anh on Unsplash Scaling a biotech research platform requires an organization to define and optimize the flow of data, which can be broken down into three questions: What tasks do we need data for (and what data do we need for these tasks)? 2. How will we collect/acquire/generate this data? 3. HowContinue reading “The Blind Philosopher’s Database”
Scaling Biotech: A Framework
Photo by Ashkan Forouzani on Unsplash Scaling a biotech research platform requires a data platform that enables a wide range of project and functional teams to efficiently and effectively coordinate and share data. Over the last few months, I’ve been writing about different aspects of this, circling around a mental model for making decisions aboutContinue reading “Scaling Biotech: A Framework”
Making Data Travel
Image by Gerhard G. from Pixabay Scaling a biotech research program requires coordinating the flow of data between teams, functions and scientific fields, from the people that generate it to the ones that use it. You may think of data as objective and universal. But in fact, its interpretation depends on the context in whichContinue reading “Making Data Travel”
The Experiment Cost Inflection Point
Photo by Oliver Roos on Unsplash Scaling a Biotech research program means managing and optimizing sequences of closely interrelated experiments, i.e. the Experiment Factory. A lot has been written about the value of creating short, inexpensive experiments to explore an idea. But is there ever value in making an experiment slower and more expensive? (MyContinue reading “The Experiment Cost Inflection Point”
The Experiment Factory
Image by Lou Blazquez from Pixabay For a biotech organization to scale its research program, it must balance the flexibility needed to explore a variety of biological hypotheses against the consistency needed to make a collection of observations into more than the sum of its parts. The balance between these opposing forces will shift overContinue reading “The Experiment Factory”
The Operational-Analytical Data Cycle
Photo by Miguel Orós on Unsplash For a biotech organization to effectively scale its research program, its data platform must enable all users to leverage as much data as possible within their decision making context – the levers that allow them to make decisions and take action. This is easier said than done, and oneContinue reading “The Operational-Analytical Data Cycle”
Designing a Chimera Data Platform
Image by Gordon Johnson from Pixabay One of the key roles of a software team at a Biotech organization is to enable the research program to scale without sacrificing flexibility and innovation. I’ll write more about this in upcoming posts, but today I want to explore how my understanding of the scope of this workContinue reading “Designing a Chimera Data Platform”
