In this edition of the PrescienceAdvantage® Tips & Tricks, our friends from BASIS are back to discuss how to create more realistic plans and explain how BASIS integrates with other scheduling tools, including Oracle Primavera P6. BASIS creator, Dr Dan Patterson, will introduce the concept of Knowledge-Driven Planning and explain how you can leverage BASIS to calibrate your plans against expert knowledge in real time.
Benchmarking means a lot of things to a lot of people – not to me! Traditional benchmarking involves taking your schedule and running comparisons against it. You might be comparing costs or comparing changes since your last schedule update. Traditional benchmarking is very useful for sure, but arguably not true benchmarking, given you are doing nothing more than a simple comparison, rather than truly undergoing informed validation and guidance.
Organisations have had the ability to compare plans for years and have traditionally called that benchmarking. This static process has been largely ineffective because each project has unique characteristics, and in the past, this has made it difficult to compare one plan to another or to a standard. For example, a hospital build project for a structure with 250 beds requires more scope than a hospital build with 100 beds.
Additionally, one of the major shortfalls of CPM tools is that it’s still a bit of a minefield when it comes to building a sound schedule – they simply don’t offer useful guidance. For many years, my mantra was “no constraints and no open ends in any schedule, period.” Well, let’s just say, I’ve
evolved a bit in recent years. While I still believe in establishing a structurally sound plan, there are instances where the use of frowned-upon planning entities such as constraints (e.g., contractual windows) and even some open-ended logic (e.g., reporting milestones) is perfectly okay. What I am driving at here is that there isn’t sufficient guidance given when building a CPM plan. Sure, we have simple mathematical checks such as the 14-point assessment and so forth, but they do nothing for driving realism. This is where Artificial Intelligence can play a huge role in project planning today (more on this in a bit).
So, what I am driving towards is holistic planning guidance through the use of intelligent suggestions from the planning tool itself. Intelligent suggestions are backed up and supported by contextually relevant historical standards or benchmarks. “Don’t tell me my duration needs to be 45 days unless you can give me a reason why.” Suggestions need to be given with knowledge of context – context is key. When benchmarking a duration or a cost, or making a suggestion regarding sequence of work, having context of the quantities involved, or the location of the project, or the current market conditions is the difference between the suggestion being useful and completely worthless.
Interactive Planning Session
To help overcome this “every man for himself” nature of CPM planning, many organizations have adopted Interactive Planning Reviews. These sessions involve getting the project team together in a room to build a plan, identify project risk factors, and generally try and drive towards some degree of consensus. There are even so-called “Interactive Planning Tools” to try and facilitate these sessions, although many still prefer to use whiteboards and sticky notes!
There are multiple challenges with these interactive planning sessions. Firstly, they tend to be long and tedious, taking the entire project team way from their day job. Secondly, they don’t lend themselves to being consensus-driven or dare I say it – an open democracy. All too often, the loudest, most senior team member’s opinion sticks. Thirdly, those that carry the inherent knowledge as to how to execute a project typically aren’t CPM schedulers. They are construction managers, engineers, or discipline leads. There is a disconnect between those carrying the project knowledge and those responsible for putting a plan together.
How Does Knowledge-Driven Planning Overcome These Shortfalls?
To make this simple, I will break down the concept and reality of Knowledge-Driven Planning into three simple steps:
- Calibrate: ensure your durations, costs, risks, and logic in your plan are relevant to what you are actually going to build during execution
- Validate: get buy-in from your team that what you have planned is indeed achievable
- Score: quantify the realism of your plan
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