Predictive planning: Work on the plan, not in It | Dump Trucks Charlotte NC
Think about it: You don’t have to do things like manually check your Word document for spelling errors, explicitly type an entire recipient’s email address, or calculate the miles of a trip every time, do you? That’s because today’s computers can store and, more importantly, recall knowledge.
With this technology so readily available, why, then, do traditional project planning tools provide next to no guidance to a planner when building a project schedule? For the past 20 years, project planning tools have been reactive – waiting for you to enter data – instead of proactively offering suggestions and helping users input meaningful data. Suggestions could include durations, guidance on whether the sequence of columbus oh dump truck company is correct, warnings about erroneous building blocks such as open-ended tasks, and so forth.
Fortunately, this much needed overhaul of project planning is already underway with the emergence of predictive planning.
With predictive text, the computer is anticipating what you want to type based on what you’ve already input – for example, when your smartphone makes suggestions to help you compose a text. Planning tools should be able to do the same thing. As you build out your plan and define activities, the planning software should at least be able to make suggestions. You can use the good suggestions, and provide the planning tool with feedback on the bad ones. Then, it can “learn” from its mistakes in the same way our smartphones get trained to ignore certain words or use specific spellings. It can calibrate how often its suggestions are correct and adjust accordingly. The more interaction between the planner and the tool, the smarter that tool becomes.
To be effective, predictive planning needs to be able to:
- Capture and store sufficient historical data that can be used to establish trends or benchmarks
- Search this data storage and extract relevant patterns and make accurate suggestions
Planning organizations pride themselves on hiring the smartest, savviest planners, yet do little to try to capture and retain that expertise and knowledge. It’s not difficult to take historical as-built plans (that, of course, have that expertise embedded into them), or corporate standards and benchmarks, and develop a knowledge library. If an organization can establish a knowledge library and reuse the information in it, predictive planning is easily accomplished.
Making Sound Suggestions
For a computer or software tool to accurately predict an outcome (or with respect to predictive planning, make a suggestion to the planner), it first needs to understand the context. In the case of building a project plan, knowing the size, scope and type of project is an essential first step in giving the software some suggestive guidance. When planning, you are trying to predict a future outcome as accurately as possible. That prediction is based on context and historical analogies.
A New Era of Augmented Intelligence
In recent years, computing technologies have enabled the likes of neural networks and expert systems to return more accurate and sensible predictions. This approach today falls under the term artificial intelligence. In reality, though, I believe our approach to planning should really be more along the lines of augmented intelligence, where computer-generated suggestions can be reviewed and adjusted by internal teams. We can never replace the expertise of a planner. However, we should be bold enough to embrace the fact that computers are smart enough now to assist them during the planning process, offering informed suggestions and providing guidance.
The Evolution is Already Underway
Today, when building a project plan, advanced software such as InEight’s planning, scheduling and risk solutions deliver this capability, proactively making suggestions on durations as you create your plan. You’re provided with guidance on standard rates and costs based on the scope of work, and commonly encountered risks, issues and opportunities are highlighted based on the type and location of a project, and even the contractor who’s working on it.
You’re also afforded a much-needed reality check, as plan realism is driven through human consensus. Capturing team members’ suggestions, as well as those of the software, ensures you can continue to leverage your team’s expertise — which all leads to a validated plan.
I believe we are in the early stages of a much-needed revamp and step change in the science of project planning. Today’s leading software tools can further enable a planner to focus on building an achievable plan. After all, working on the plan not in the plan is a much better use of a planner’s valuable time.
To learn more about InEight’s planning, scheduling and risk solutions, visit InEight.com.