Should we worry about the Data-Action Gap?
The process mining community have been reflecting on why it is so difficult to drive change even when presented with compelling insights to take action. Where we landed is the idea of there being a "Data-Action Gap". This gap refers to the disparity between the accumulation of data and the effective utilisation of that data to drive meaningful actions or changes - a well-known challenge for many.
In the NHS, the Data-Action Gap is a pressing issue that undermines the potential for improvements, elective recovery, and productivity gains. While there is an abundance of data and a significant focus on reporting activity through descriptive analytics, there is a noticeable shortfall in the systematic use of diagnostic analytical techniques to drive meaningful change.
The gap arises from a failure to use this data effectively for actionable insights. While the NHS has the necessary data for transformative decisions, it is often entangled in operational metrics rather than strategically leveraging this information. Addressing this gap is essential for the NHS to shift from merely outlining issues to using analytics to actually diagnose and resolving them.
We have identified nine different elements of the Data-Action gap within the NHS:
Analytics-Inexperienced Leadership
What happens: Leaders not utilising high-quality data and insights routinely
Impact: Poor focus on priorities, Poor delivery of vision and ambition
Lack of Expertise
What happens: Inadequate skills in improvement, data management, or analytics strategy
Impact: Failure to optimise, limited access to data, poor resource allocation
Resource Constraints
What happens: Inadequate manpower, budget, or time to execute change
Impact: Delayed resource, over-worked and demoralised staff
Weak Analytics
What happens: Insight is not hypotheses-driven, diagnostic or actionable
Impact: Decision paralysis, missed opportunities
Lack of Data Trust
What happens: Doubt over the quality or reliability of data
Impact: Inaction, missed opportunities
Organisational Silos
What happens: Fragmented insights due to departmental isolation
Impact: Reduced pace of change, in-fighting and conflicts
Misaligned Objectives
What happens: Conflicting goals among departments and teams
Impact: Counterproductive actions, frustration
Short-Term Focus
What happens: Over-emphasis on immediate returns
Impact: Long-term gains sacrificed, unsustainable improvements
Cultural Resistance
What happens: Aversion to change or adopt new data driven methods
Impact: Failure to evolve or progress, reduced potential to scale
Some may say the NHS should be looking more at predictive and prescriptive analytics, but without firm foundations, this approach carries a much higher risk. The development that tools like ChatGPT are going to bring will fundamentally change the way we all approach analytics. This makes it all the more crucial to get the 'soft' issues such as leadership, organisational culture, and expertise right now.
Solidifying these aspects will prepare the NHS for the more advanced analytical methods that are fast becoming a reality.
We are working hard to understand these issues and would welcome your input. Our aim is to devise tools, techniques and approaches that will help rapidly bridge the gap and accelerate the use of data to drive meaningful actions or changes.
Matthew is the co-founder of Logan Tod & Co and a member of the AnalystX community. He has been pioneering the use of process mining in the NHS and coaching NHS users to get them started.
Photo by Suad Kamardeen on Unsplash