Alteryx > Case Studies > Anthony Nolan's Data Transformation Journey with Alteryx for Life-Saving Outcomes

Anthony Nolan's Data Transformation Journey with Alteryx for Life-Saving Outcomes

Technology Category

Infrastructure as a Service (IaaS) - Cloud Computing
Platform as a Service (PaaS) - Application Development Platforms

Applicable Industries

Equipment & Machinery
Oil & Gas

Applicable Functions

Quality Assurance

Use Cases

Experimentation Automation
Time Sensitive Networking

Services

Testing & Certification

About The Customer

Founded in 1974, Anthony Nolan is a British cancer charity that saves the lives of people with blood cancer by matching them with stem cell donors. The organization is on a mission to accelerate the donor registration process and use data insights to strengthen their work. In the UK, approximately five people start looking for a matching donor every day; that equates to more than 2,000 people needing bone marrow or stem cell transplants annually. The organization was dealing with disparate data elements from their data lake to onboard potential lifesaving donors onto the stem cell register. This process was time-consuming and relied heavily on Excel, taking hours each month.

The Challenge

Anthony Nolan, a British cancer charity, was faced with the challenge of accelerating the donor registration process and using data insights to strengthen their work. The organization was dealing with disparate data elements from their data lake to onboard potential lifesaving donors onto the stem cell register. This process was time-consuming and relied heavily on Excel, taking hours each month. The organization was also dealing with growing datasets and ensuring regulatory compliance. The original team of four business analysts at Anthony Nolan were working in an environment lacking in data quality management and governance, which made it almost impossible to derive actionable insights. They were divorced from the data sources and lacked analytic tools such as stats packages and visualization tools. They could produce very little reporting and no true insight.

The Solution

Anthony Nolan implemented the Alteryx Analytic Process Automation Platform™ as part of a digital transformation drive. The Alteryx Analytics APA Platform was introduced to the organization when a spare Alteryx Designer license became available. The subsequent deployment of Alteryx Server has been part of a 5-year data strategy framework which was spearheaded with three key directives: Governance, Data management, and Insight for action. Alteryx gave the organization the ability to pull huge datasets from disparate sources and very quickly aggregate to achieve instant meaning. The organization also used Alteryx Analytic Process Automation to categorize donors on the register in a fraction of the time with consistently accurate results. This efficiency gain allowed the analysts to generate a much fuller picture of the rate at which stem cells are donated. The organization also used Alteryx to perform business-critical processes such as data quality checks and allowed automated alerts to be sent to the relevant business owner when a problem was identified.

Operational Impact

The implementation of Alteryx has led to significant operational improvements at Anthony Nolan. The organization has been able to automate the assembly of disparate data, driving efficiencies in donor onboarding. The analysts are now able to pull huge datasets from disparate sources and very quickly aggregate to achieve instant meaning. This has led to the illumination of insights that were previously inaccessible. The organization has also been able to automate the categorization of donors on the register, leading to consistently accurate results and a fuller picture of the rate at which stem cells are donated. This information has helped to launch targeted interventions by category and expose age groups to focus on for specific campaigns. The organization has also been able to automate business-critical processes such as data quality checks, leading to swift remediation and prevention of continuous investment of funds into legacy systems.

Quantitative Benefit