Case study: Helping to change patient lives with actionable insights from Pfizer's Data Analyst Academy

In January 2021, Pfizer launched its UK Data Academy in partnership with Cambridge Spark with the aim of developing key data skills and capability across its UK workforce. The Pfizer UK Data Academy consists of skills development programmes suited to every level and covering essential skills such as Data Literacy, Data Analysis as well as Data Science and AI, utilising government funding through the UK’s apprenticeship scheme.

Pfizer has been discovering better ways to prevent and treat diseases for 170 years. Their response to the Covid pandemic in 2020 led to the development of the COVID-19 vaccination. Just one, in a long line of Pfizer breakthroughs and developments that change lives. Pfizer’s collaborations with healthcare providers, academia and policy makers are fundamental to bringing new medicines to patients; and their ongoing commitment to the learning and development of their staff plays a key role in achieving this.

Four teams with different backgrounds at Pfizer and only 4 months into their Data Analyst apprenticeship, took part in a hackathon where they worked on datasets relating to live experiments and projects including Diabetes, flu infections and Covid-19. The teams included project managers, analytical chemists, scientists, manufacturing technicians and customer contact centre representatives. They all rely on data to perform their day-to-day jobs and are passionate about improving their approach to data analytics, visualisation skills and finding new ways to present large volumes of data in more meaningful ways.

Data Analyst apprentices spent 2 days in a Hackathon which is a key part of the Data Academy. Using Python based tools and techniques they were able to share real business insights with Pfizer that contributed immediately to improving people’s lives.”

Pfizer Academy Team Leader

The hackathon gives apprentices the opportunity to explore the data being captured across the organisation and compare different data processing and analysis techniques. At Pfizer, the goal was to use Python to identify and classify data, making recommendations about labelling and common formats for collaborative research and analysis at scale across the entire organisation.

Working in teams of three, the apprentices were given 493,147 rows of metadata (that's 312 MB+) and two days to conduct their analysis. They used Python code to understand how data could improve organisational workflows and identified metrics to improve manager reports. They also used the tools and techniques from sandbox environments to make an assessment of performance levels across different Pfizer departments. 

Productivity studies allow project managers to make decisions about resource allocation. They include ‘all departments’ versus ‘some departments', and 'departments versus people' to find the performance indication compared with the previous year's average. That way, the right projects can be prioritised and deprioritised.

Pfizer Academy Team Leader

Pfizer maintains a year-round focus on productivity. This includes data analysis of clinical drug trials, approvals and quality. As the quality of productivity and manufacturing improves, profits grow which leads to new product development so the data analyst apprentices were given productivity values to work with. These included the number of lab-based projects live or completed, the number of people working on experiments and the time taken for an individual to produce lab work independently of a team.

The Level 4 Data Analyst apprenticeship has a strong focus on work-based learning. Success coaches provide 1:1 support to help integrate knowledge into the workplace so the principles of data analysis can be applied in an immediate and practical way. 

“We worked with large datasets for insights about projects that could be prioritised or deprioritised. We knew which tools would automate data analysis processes and safeguard against human error. In a pharmaceutical company, false results that lead to incorrect conclusions can impact lives so the techniques we practiced in our workshops were immediately transferable to the workplace.”

Data Scientist Hackathon Team Member

The apprentices used Python to understand the extent to which Covid-19 may have impacted productivity. Analysis of ‘experiment ID by user’, allowed teams to calculate the time needed to train a scientist. This involved the analysis of the time spent shadowing others in the lab, versus the time to perform multiple lab experiments as an individual. They also calculated the average time in days to complete experiments and which departments were ‘lab heavy’ or more productive than others.

Team members employed the full range of skills learnt during their apprenticeships to tackle hackathon datasets and received extremely positive feedback from Pfizer senior leaders who were invited to watch the final presentations. The teams took a Jupyter Notebook back to their departments to replicate what they'd worked on and commercial considerations were also identified as a key outcome.

The hackathon, for Pfizer was about upskilling the workforce to generate a direct impact on the business.

Cambridge Spark are currently enrolling for the next cohort of the Level 4 Data Analyst Apprenticeship. Get in touch with the team using the form below to find out how we can help your organisation build data analytics capability.