When we emphasize to clients that it is important to learn from past experience when executing new projects, it often comes across as stating the obvious. In theory it seems blatantly simple and something that should happen automatically, especially when asking management. The reply we often get is "Learning?!?, Yes that's something we do after every project... but we could do better." Most of the time when we start digging into the actual capabilities and the data collected, the reality of the matter is what they have is often not well formed and/or even usable.
If we take the PRINCE2 model as an example, project teams should learn from previous experience by seeking lessons, recording them and acting upon them throughout the life of the project, not just at the end but continuously. This is all stated in the manual!
Projects understandably involves a temporary organization for a finite timescale for a specific business purpose. A common characteristic is that the project includes an element of uniqueness such that it cannot be managed by existing line management or functional units. It is this element of uniqueness that makes projects challenging as the temporary team may not have experience of a project exactly like the one being undertaken.
In the PRINCE2 model, learning from experience permeates the method in the sense that previous or similar projects should be reviewed to see if lessons learned could be applied when starting a new project. If the project is a "first" for the people within the organization, then it is even more important to learn from others.
As the project progresses the learning should be continuous. Lessons, assumptions and forecasts should be included in all reports and reviews. The goal is to seek opportunities to implement improvements during the life of a project and continuously measure whether the project is on track or not.
As the project closes it should pass on lessons that should be acted on. All of these learnings can be in the form of soft measures like team spirit or job satisfaction but even more importantly should also include hard measurable metrics that proactively can be used for upcoming projects.
It is important to be able to store the metrics and apply them easily, because if they end up in a document or spreadsheet on a shared drive, no learning will be done and exactly the same mistakes will be made in the following projects.
I cannot stress enough how immense the benefits can be if this learning is collected and applied automatically to each and every project that is executed. It is often the siloed nature of any given company that effectively puts a barrier up for this to be done. But do not let that stop you!
The more structured the experiences are collected in the form of actionable metrics that easily can be applied, the more benefits can be reaped. Once satisfactory capturing of learning is achieved, organizations will be able to leverage this even further to create accurate forecasts and predictions for the outcomes of their projects thus boosting and optimizing value for them even further.
The truth is that most companies do not do this properly, even though they claim to. The companies that actually do this can most likely improve further on this, unless their maturity and models are already self learning and they have built the data foundation to support it.
The most important thing to realize is that it is never too late to start doing it and shared drives and systems across the organization will most likely contain "hidden treasures" of usable knowledge to leverage right away. It just needs to be acted upon.
Always learn from previous experience because can you really afford not to do it?
Do you want to see a demo of what Forecast has to offer, or if you have any questions related to this; then book a personal 30 min. slot with our success team. We're looking forward to hearing from you.