The lessons learned process in project delivery remains a difficult challenge, as noted by Stoney (2021). Despite several reports from organisations like the National Audit Office and Public Accounts Committee, organisational learning from projects remains rare, and even when it does occur, it often fails to achieve the intended results. For instance, Projecting Success collated ~20,000 lessons learned and concluded that most organisations are unable to demonstrate that lessons are being learned.

The current lessons learned process is fundamentally broken, as the same mistakes are being repeated, making it challenging to leverage our collective experience. However, we can reimagine the lessons learned process and improve how we collect and curate our data, allowing us to leverage our experience downstream. We must move beyond spreadsheet-driven approaches to lessons learned and start using machine learning to prompt us on what lies ahead, the potential impact, and provide advice on courses of action.

Our objective should be to create a project satnav that can advise us on where potential delays may arise or how we can accelerate the project's progress. We must also change our approach to learning from projects since it's illogical for humans to learn everything about everything. Instead, we need to leverage our collective experience, codified in data, which holds the key to improving our project delivery outcomes.

To reimagine the lessons learned process, we need to collect, curate, and integrate our data. Although we often manage data in silos, it is interconnected and mutually dependent. A change approval, for instance, affects resourcing, cost, schedule, and more. We can create an asset that works for everyone by collecting and pooling data in a data trust.

By using a data-first approach that leverages the years of knowledge accrued, we can identify potential dangers or opportunities. We can also leverage our shared experience to understand what worked and what didn't. By encoding data and narrative, we can deduce how likely something is to arise on our project and gain insights into causality.

We need to close the loop between risks, issues, variance events, and lessons, ensuring that we connect and leverage the data. This approach allows us to separate out how we capture and leverage our collective experience from root cause analysis, reflective practice, personal vs. team vs. organization vs. large-scale learning, the avoidable from the unpredictable Black Swans, hard evidence from conjecture, and the generic from the specific. We can gain insights based on relevance and context and have evidence to anchor our assessments of impact and probability.

By applying advanced project data analytics and AI, we can reimagine the lessons learned process and improve our project delivery outcomes. We can collect and curate data, leverage our collective experience, and close the loop between risks, issues, variance events, and lessons. Through these efforts, we can change the game and unlock our superpowers.

Martin Paver & Jake Williams are leading the work on the Visions for 2025. Martin is the Founder and CEO of Projecting Success and former Chair of the Project Data Analytics Task Force. Jake is a Product Manager at Projecting Success. Please check out the LinkedIn post on this topic.

In collaboration with

access Visions for 2025