When that catchy slogan started back in 1976, it was mainly focused on the impact of waste and gaining additional traction of recycling to further conservation efforts. Now, we are still dealing with those impacts on an environmental level, but that is for another blog post. Have you thought about taking these same concepts, and applying them to your capture, shared analysis and future use of data?
Has there been inconsistency on how many different methods you are using to capture data? Pen and paper. Excel spreadsheets. Project Management Solutions. Reality Capture Methods. The Superintendents notes on their cell phone? Multiple methods of capture can be great – if they are synced, and speak to each other in a cohesive manner. Also, there is the accuracy you may risk by completing data capture manually, as opposed to automated methods such as with manpower statistics.
Capturing many data points can add additional visibility when the information may have been considered invisible. But, reducing the methods of how you capture through hardware that is built to be passively capturing data without interfering with the day-to-day operations, can prevent multiple sources of information being input into disparate systems incorrectly. So, capture a lot, with minimal systems or methods, can drive cohesion and accuracy across the project.
There is a saying that goes measure twice, cut once. Well, flip that for data capture and usage. Capture once. Use 1,000 times. By automating data capture so that single data points captured at a moment in time, are used in multiple functions can help different causes and provide additional accuracy. Pushing data into your PM system from your workforce visibility trackers, then is read by your ERP system for payment processing for contractors. If you take one instance, and make that data work over multiple functions, you gain efficiency for your entire workforce by eliminating duplication of data entry efforts.
Recycling isn’t just for paper and plastic. A lot can be learned from historical organized data that empowers future project and business decisions. How much labor is needed to hit schedule deadlines? Which trades on the critical path of a project have a history of performing ahead of schedule, or have made up time quickly? Where have we been billed additional manpower hours and can we account for that in the future? The answers to these questions and so many more can be found in historical data capture from projects that can make future business decisions easier and more meaningful.
These enhanced understandings can lead to project savings in budget, schedule and frustrations when planning for the future. Reducing your methods of data capture, reusing data across job functions and needs, and recycle data for historical learnings to make future success gains can be a force towards a successful project.
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