Lessons learned are a critical part of organisational self-improvement. If an organisation doesn’t understand its failings, it’s doomed to relive them. Understanding where things have gone wrong or misstepped is, therefore, crucial for any business to develop and grow – particularly those that work on a project-by-project basis.
In this guide, we explore the concept of lessons learned in project management, its purpose and benefits, the types of lessons companies can encounter, and an encompassing framework you can use to improve your approach.
We’ll also examine how generative artificial intelligence is fast becoming a transformative tool for project managers, allowing them to understand and act on lessons learned in an instant.
Learn how we helped Network Rail organise, understand, and act on its vast lessons-learned library prior to a critical £44 billion investment period.
What Are Lessons Learned?
Lessons learned are documented insights and knowledge gained from past project experiences. By understanding how projects unfolded, including their successes, failures, incidents, errors, and the resulting learnings, project managers can create reports used to guide their actions in future projects, ultimately making them more effective and successful. As such, it’s an important aspect of knowledge management.
Lessons learned is a people-focused practice that brings together all the staff on a project to collate and then distil their experiences—it’s a collective endeavour everyone should be responsible for. It’s best conducted at the end of each project phase to ensure all relevant lessons are captured. Reviewing relevant lessons learned should also be a key part of project planning.
When integrated into every project, lessons learned have the potential to transform how a project manager, team, department, or business operates. It can improve the speed and quality of delivery, avoid costly mistakes, and upskill staff, boosting return on investment in the process.
What Are The Benefits Of Lessons Learned?
Lessons learned are a massive help for your project teams and the wider organisation for a whole host of reasons:
Better Decision-Making
The most important goal of lessons learned is improving the efficacy of future decision-making. A greater understanding of how previous projects unfolded lets project managers guide their teams more effectively.
If a previous project required less time than required, for instance, managers can reduce the time available for similar future projects, enabling team efficiencies.
Avoiding Mistakes
Most projects will experience difficulties of some kind or another. By logging these, understanding why they occurred and their impacts, and ensuring they are accounted for in the future, projects can proceed more smoothly.
If a previous project overran due to poor team communication, for example, a lesson learned would be to implement more regular catch-ups or promote the use of communication platforms.
Improved Efficiency and Performance
Lessons learned let organisations hone their process and approach. By helping your teams work more effectively, projects will progress more efficiently and ultimately have a greater positive impact.
Better Adaptation and Resilience
In fast-paced, project-based working environments, teams regularly need to adapt to change: scope, timelines, feedback and so forth. With a bank of relevant lessons learned at your disposal, you can adapt your approach quickly, confident you’re making the correct split decisions.
Creating a Culture of Improvement
If a business wants to grow and develop, it needs to engage in a process of continual improvement. Culture is foundational to this.
Staff need to feel that they can share their experiences, that their input is valued, and that it has a positive impact. If they do and this becomes a key aspect of the working culture, then the sharing and use of lessons learned will become self-perpetuating.
Greater Innovation
By taking time to understand what went well, staff can apply learnings to different situations and project types. By becoming aware of pitfalls and why they happen, they can find better ways of working in the future. The result is a continual process of creative innovation that touches and improves all aspects of projects.
Lessons Learned: Categories And Examples
So, what constitutes a lesson learned? There are plenty of categories to look out for spanning all aspects of projects.
Time
Time-based lessons learned typically involve scheduling issues and a lack of understanding of a project’s critical path. Missed deadlines, staff overtime, a lack of contingencies, and dependency-related bottlenecks can all have an impact.
Cost
It is critical to accurately estimate a project’s cost, put funds aside for contingencies, and review spending regularly throughout the process. Funding shortfalls, a lack of cost monitoring, or overly ambitious budgeting can lead to these lessons.
Scope
Projects must have clearly defined objectives that all stakeholders agree on. They must also be backed by a change control process that only allows approved changes to alter the scope mid-project. Failure to do this can lead to projects becoming over budget and behind schedule.
Technical
Every project depends on several technical inputs, whether that’s tools, software, or systems. Failure to account for these can result in lessons learned about the constraints and benefits of different tools and software or the need to better integrate and provide training on new systems prior to the start of new projects.
Quality
Quality checks and processes like end-user testing are crucial in guaranteeing the project is up to standard. Failure to do so can lead to lessons learned regarding customer support issues, poor usability, and project delays.
Risk
Risk management needs to be accounted for throughout the project. If risks aren’t adequately identified in the planning stages, they can lead to issues later down the line. Risk mitigation plans are required, too – if they’re not in place, problems can have a much greater negative impact than they otherwise would have.
Communication
Project managers need to have a communication plan throughout the project lest it overrun or veer off course. Throughout the process, it’s also important to document progress, decisions, and changes. If these aren’t accounted for, lessons can materialise due to a lack of continuity and clarity, leading to similar problems.
Resource Management
Lessons learned around resource management include accounting for the right skills within a team or department, which can lead to either underperformance or project scopes not being as great as they could have been. Improper allocation of resources is also a common learning – failure to accurately assign resources can lead to burnout, staff turnover, or result of underallocation.
Stakeholder Management
Project lessons around stakeholder management might include a lack of engagement leading to poor buy-in. Communication is also key – a lack of frequent and clear communication can lead to frustration or misaligned expectations.
Compliance
Lessons learned can include compliance, standards and regulatory factors, including not meeting key regulations, an inability to keep up with changing policies, or a failure to match company standards.
What Process Framework Is Best For Conducting Lessons Learned?
When properly harnessed, lessons learned can be game-changing. But whether you’re new to the concept or are a seasoned project professional wanting to hone your approach, what is the best process framework to use? A five-step process is a great place to start.
Step 1: Identify
This first stage involves capturing lessons learned so they are ready to be processed and used in future projects. Make sure to account for the following:
- Reflection: Get your team to regularly reflect on their experiences during the project, noting down thoughts and opinions in between the more structured identification activities below.
- Surveys: Send out lessons learned surveys to stakeholders after significant project phases to harvest feedback while it’s front of mind.
- Team discussions: As a team, discuss how the project went: positives, negatives, and improvements. These discussions should ideally be facilitated by someone who isn’t the project manager to encourage honesty.
- One-to-one interviews: Talk to team members and stakeholders one-on-one about their experiences. These conversations may glean more honest feedback than surveys and roundtable discussions.
Using the lessons learned categories listed earlier in the article is a great way to structure surveys and sessions. In them ask simple and powerful questions: what went wrong, what went right, what needs to be improved, and how.
Step 2: Document
For lessons learned to be effective, they need to be documented so they can be sharable and used to benefit future projects. Throughout the lifecycle of the project, as identification tasks have been conducted, collate and log the feedback, including:
- The specific lesson
- The category of project
- The category of lesson
- The project the lesson originated from
- Keywords related to the lesson and project
- Who raised it
- When it was raised
- How significant an issue it was on a scale of 1-5.
With the above framework, actions can be prioritised, and lessons learned can be quickly and easily retrieved during the planning phase of future projects. Custom generative AI tools can be a time-saving tool here, organising feedback in a clear report format.
Step 3: Analyse
Once you’ve logged them, take time to understand the lessons learned so you can use them to improve your process and approach. What were the most significant problems? Why did they occur? What could be done to rectify them? Once analysed, you should have an idea of the greatest opportunities for improvements, which you can then assign as actions to the relevant stakeholders. Ensure the resulting report includes the following:
- A top-level summary of lessons learned (findings and recommendations)
- An executive report providing findings and recommendations in brief (helpful for decision-makers)
- Detailed findings
- Detailed recommendations
- Relevant project metrics (to show the impact of the lessons learned).
Armed with your findings and recommendations, you can then present them to stakeholders and your project team.
Whether you’re planning, midway through, or have finished a project, this process needn’t be manual or long-winded. With an intelligent AI agent, you can take the power of a large language model (such as Open AI’s GPT model) and tailor it to the task at hand.
When put to work on lessons learned analysis, users can ask intelligent agents questions through a chat functionality. In an instant, the agent scans through huge volumes of data, interprets and interrogates it, and then provides accurate insights or broader summaries to the user, saving significant amounts of time and effort.
Step 4: Store
Lessons learned must be stored in an organised library that is easily accessible to users. If it isn’t, the effort of interacting with the system will put off users and lessons will be ignored.
AI can also assist in storing and organising lessons-learned documentation. Integrated with your systems, intelligent agents can categorise and store logs in the right place and retrieve the relevant insights for users without them needing to enter the library. AI can provide
Step 5: Retrieve
An ongoing final step, retrieval of lessons learned, is a critical part of the project planning process.
Whether manually accessing a library of documentation or interrogating data en masse using an intelligent agent, search for reports relevant to the upcoming project. Take time to understand the pitfalls and successes of previous projects, and thread these into your plan to level up your approach.
Can Generative Ai Improve Lessons Learned?
Generative AI is a key focus area for all manner of organisations, with its use cases particularly beneficial for those that work on a project-by-project basis. No less is this true than lessons learned; the technology has the potential to improve the process from start to finish:
Data Analysis and Insights
- Recognise patterns: AI can analyse past project data to identify patterns and trends, helping teams understand what strategies worked well and what didn’t.
- Identify root causes: Generative AI can help uncover the underlying reasons for project successes or failures by bringing together several project metrics and outcomes.
Automated Documentation
- Generate reports: AI can automatically generate comprehensive lessons learned reports based on project data, feedback, and outcomes, reducing the manual effort required to produce them.
- Knowledge management: By organising and categorising lessons learned in a database, AI can ensure that valuable insights are easily accessible for future projects.
Continuous Learning
- Feedback loops: Generative AI can facilitate real-time feedback, allowing teams to continuously update lessons learned as new information and insights become available.
- Personalised recommendations: AI can suggest best practices or lessons relevant to specific project types or contexts, improving the applicability of insights.
Scenario Simulation
- What-if analysis: AI can simulate different project scenarios based on historical data, helping teams visualise potential outcomes and make informed decisions.
- Risk assessment: Generative AI can identify and assess risks by analysing past project challenges, enabling proactive measures in future projects.
Enhanced Collaboration
- Collaborative Platforms: AI can facilitate better collaboration among project teams by summarising discussions, highlighting key takeaways, and ensuring that lessons learned are communicated effectively.
- Sentiment Analysis: By analysing team communications, AI can gauge team morale and engagement, providing insights into the human factors that affect project success.
Integration with Project Management Tools
- Seamless Workflow: AI can be integrated into existing project management tools to automate the collection of lessons learned during project execution, making the process less intrusive.
- Real-Time Updates: AI can provide real-time updates on lessons learned and related best practices as teams work on projects, ensuring that insights are applied immediately.
By leveraging generative AI in these ways, project managers can foster a culture of continuous improvement, making lessons learned a more integral and efficient part of the project lifecycle.
Oakland’s AI consultants have helped several organisations implement smarter, faster, lessons learned. With our help, you can take the legwork out of collating, analysing and retrieving lessons learned and put them to work across your organisation. Get in touch today or learn how we approach AI.
