The project is finally done, months late and millions over budget. Your beleaguered team staggers into a lessons-learned session, brave-faced and primed for battle. Some question the point of the exercise. Everybody’s memory is fuzzy. Fingers start pointing.
Even the most principled professionals will be sorely tempted to broadcast the great successes while camouflaging the failures; nobody wants their bad decisions dissected and laid out for all to see. There’s not a lot of time to provide context. The consultant dutifully writes everything down and is out the door.
It’s all written up, keywords are duly attached, and the lessons are filed away in a document, spreadsheet or database. Companies that follow best practices might integrate the most critical of these lessons into standard operating practices. The rest will be boxed away, out of sight and out of mind, read by only the most enterprising and keyword-savvy of your team members.
Everyone else will get busy reinventing the wheel.
It’s not clear why companies stick with this cumbersome and inefficient process when the benefits of better knowledge management are so abundantly clear. The US Army Corps of Engineers has reported that for every $1 invested in the collection and application of lessons learned, the Corps saved $120 in project costs. Over seven years, the application of just 29 lessons saved a staggering $53 million — to say nothing of saved time.
In an era when transactional costs consume 40% of the average capital project budget and billion-dollar cost overruns are not unheard of, it’s time to start learning from our mistakes.
A powerful new way to manage knowledge
Most companies think about lessons learned as a one-off, post-project event. It’s time to reframe the practice for the 21st century. Today, learning from successes and failures is an undertaking that requires sophisticated, applied knowledge management. In short: We need to start talking about building a knowledge base.
Your knowledge base will contain all of the lessons your company has already learned, which will have to be added manually in the beginning. However, with the help of new technology, the lessons you’re learning right now will be captured in real-time, while the work is taking place. This removes fuzzy memories, finger-pointing, and self-preservation from the equation, leading to a more neutral and fact-based repository of knowledge.
This kind of automated data collection also addresses a critical problem with current practices: the absence of context. Too often, the standard lessons learned exercise focuses only on what went right or what went wrong, and rarely ever delves into the project conditions surrounding success or failure. Incentivizing information capture in the moment ensures that important contextual details are both remembered and shared.
Lessons shared at the moment your team needs them
Finally, powerful new algorithms driven by artificial intelligence can make sure that critical lessons are automatically presented to your team members at the precise moment where the learnings are best applied.
To understand how this works, think about the advertisements that follow you around the Internet. One Saturday afternoon, you spend an hour shopping for a new car on the Internet, and for the next few days the ads for that very car pop up everywhere you go online. The same technology that seems creepy online can save millions of dollars in the workplace.
For example, imagine a U.S.-based project manager is in the middle of scoping a unique, highly technical work package. She receives an alert about a similar work package executed in Mozambique the previous year, which went $2 million over budget. With a single click, the project manager is taken to a summary of the learnings from Mozambique, which can then be applied to the current project. That’s meaningful knowledge management.
Notably, the project manager doesn’t have to remember to search for relevant lessons learned, she doesn’t have to search through files, navigate to a separate computer program, or think up keywords that will surface information relevant to her work. Using big data and machine learning, the platform she’s working in considers the work package she’s scoping and intelligently suggests learnings that are relevant to the work she’s doing.
Equally important, the project manager who executed the work package on the project in Mozambique didn’t have to attend a day-long session during which he had to remember and recount the $2 million boondoggle. The technology captured the entire report while he was working, in real-time. It was then reviewed by a governance committee, stripped of confidential information and entered into the knowledge base, complete with fulsome context and cost impacts.
Lessons learned won’t just apply to highly technical work packages. The consistent application of modern knowledge management practices will make worksites safer, improve the quality of construction, and reduce the number of technical errors.
It’s long past time that we stop reinventing the wheel, and start learning from our mistakes. Let’s get started.
