Applying Academic Research Principles in the Private Sector

Alex Fischer

Hi, my name is Alex, and just over a year ago, I left academia to join the start-up world as a health researcher and data scientist for Aviro Health. I didn’t swap a tweed blazer for a black turtleneck, but I’ve moved from spreadsheets to Miro boards, and I now plan in 2-week sprints instead of 3–5-year funding cycles.


So why make such a drastic career change? To be honest, it wasn’t all that drastic. I am still doing the same work; writing proposals, collecting and analyzing data, then using the results to tell a story, I’m just doing it on different tiers. Last year, we created a thorough M&E plan, and with each new project, we map our indicators based on three tiers of impact pathways:

1. Health impact indicator pathways

2. Hypotheses indicator pathways

3. Optimisation pathways 


In academia, I lived in pathways 1 and 2. These are robust, multi-year studies, with a large, diverse sample size, across several implementation sites, to show a statistically significant difference in outcomes, usually between an intervention group and a control group. This kind of project requires ethical approval, and multiple stakeholders collaborating to implement the study, then the dissemination of results to the scientific community through peer-reviewed journals.


I am proud to say that I still get to work on these projects with Aviro; just last week, we were published in the Southern African Journal of HIV Medicine for a project we did with Johns Hopkins University and the Aurum Institute. With our intervention, research showed that digitally supported HIV self-testing increases facility-based HIV testing capacity in Ekurhuleni, South Africa (more on that in the next post!).


What I am really excited to talk about, however, is what we do with pathway number three; optimization. This is the big difference between academic and private research, as now I also get to analyze real-time data to identify trends that we can use to improve user uptake and retention. These analyses are quick n dirty, with small sample sizes, and no statistical significance, but they can be done in a matter of hours, and the results can be actioned on by our team in a matter of days! This allows for speedy proof-of-concept testing that may not be robust enough for us to submit to a journal, but it’s enough for us to identify what’s working and double-down. These are the stories that I’m most excited to share.


When I joined a growing team of 10 last year, we didn’t have a scrum master or in-house UI/UX designer yet, but our founders saw the need to bring in a researcher. Why? Because research is a way to tell stories, and as a start-up, we have a lot of great stories to tell! I will be using this blog to share some of our stories that don’t necessarily meet the format of a peer-reviewed journal, but they do push the scientific needle ever so slightly forward.

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