Planning 2.0: Why knowledge-driven planning trumps traditional CPM | Dump Trucks Charlotte NC
Knowledge-driven planning can be broken down into three simple steps:
- Calibrate: ensure the 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
Calibrate through benchmarking
A singular benefit of knowledge-driven planning is that, unlike traditional CPM tools, it provides real-time guidance when developing a new plan from scratch and also when reviewing an existing plan during interactive planning sessions.
As a plan is built out, suggestions as to recommended durations, which activities should be included, logic between activities and even costs are given. This is achieved through an always-on artificial intelligence engine that sits behind the scenes.
This engine makes suggestions based on historical data from an organization’s knowledge library, taking into account the context of the type of work, as well as the scope involved. This represents a significant leap forward from traditional benchmarking techniques, which were largely ineffective because each project has unique characteristics that were difficult to compare.
And unlike traditional CPM tools, AI provides the means to assess realism in the planning process, ending the disconnect that emerges between those carrying the project knowledge and those responsible for putting together a plan during interactive planning sessions.
When establishing durations and sequence of work, the AI engine can make suggestions based on historical benchmarks, driving planning accuracy.
Validate through team member buy-in
Having a plan that has been calibrated by AI-guided insights is one thing, but does your team really believe it is achievable? This is where team member buy-in comes into play — we call this human intelligence.
Capturing expert opinion from multiple team members and then establishing a consensus is extremely powerful in determining if a team believes in the plan or not.
Taking this consensus view and comparing it to an AI benchmark-driven plan results in the best of both worlds — specifically:
- Assurance that what is built is realistic and aligns with historical benchmarks
- Validation that a project team has bought into the plan and stands behind it
Score your project plan realism
Having a means of measuring plan realism helps drive it toward the desired end goal. It provides insight as to whether a plan is good enough or whether it needs more columbus oh dump truck company to get it into a viable state.
To achieve this, knowledge-driven planning utilizes today’s leading software to score the realism of a given plan. Plans are scored using an index of zero to 10 that reflects how much of the defined scope is realistic. Of course, the higher the score, the more realistic the plan, and the better chance of achieving the desired outcome during execution.
Supplemental measures reveal whether there are missing details in certain areas of a plan and also how many gaps there are that could be used to improve the flow of work.
Additionally, the advanced software allows for a plan to be created quickly, leveraging an organization’s knowledge library and shortcuts the software provides or, alternatively, bringing in an existing plan from Primavera or Microsoft Project. Existing plans can also be imported directly into the knowledge library, so history, standards and benchmarks are housed in a single location.
Planning 2.0 drives project success
Knowledge-driven planning doesn’t replace CPM, it spurs it to evolve. Today’s scheduling tools can serve as a strategic, proactive guide throughout the planning process, rather than just a static, blank drawing board, marking a significant leap forward in traditional planning and scheduling.
For more information about InEight’s planning, scheduling and risk solutions, visit InEight.com.