Stakeholder Data Benefits But what’s the point of collecting all this data? It does no good if we can’t find out the answers to what we need to know. Construction choices should include data professionals so the owner can answer questions like: • Is this barrier wall element in the right place, with the right amount of overlap to meet contract requirements and prevent “seepage windows,” which would undermine the usefulness of a cutoff wall? • Does grouting data suggest we need to split space to add extra grout holes in an area underneath our dam project to make an even more effective grout curtain? • What construction activities caused our instrument to react, and does that data have safety implications for our workers and our project? • How do we know the accuracy of a readout from a tool or instrument used on a project? • Are construction operations affecting other parts of the project that the contractor may not be aware of? • What has the long-term effect been of installing a cutoff wall at a location? But that’s just the owner’s concerns, you might think. What’s in it for the contractor? A lot! If you are managing projects with Excel spreadsheets, chances are you are wasting energy. Inefficient workflows cost time and money. Lots of copies of spreadsheets make it hard to know what data is correct in the long term. Which copy is the master? How many times are your employees writing down the same information, or copying it over into different reports? How do you deliver to the owners’ expectations if you don’t have your data well organized? Reconsidering Data Management I have worked on many data rich projects as a government representative for the Tennessee Department of Transportation for its statewide Rockfall Management System, and for U.S. Army Corps of Engineers’ projects such as the Wolf Creek Dam barrier wall and grouting and the Center Hill barrier wall in Nashville, and the Mosul Dam grouting project in Iraq. So I have a few ideas about this. Mostly, what is needed is the understanding that we are in this together — the owner and the contractor. Neither will succeed without the other. Some key lessons I have learned are: • • • • • • Never, never, never enter data more than once if avoidable. Every time you re-enter data or cut-and-paste data into yet another system, it wastes time and introduces errors. Instead, use import features in applications to move data around. • Both players need a data manager to manage the data flow, or it will manage you. This is where a data management plan comes into play. We need to think through what data we are getting, what data we are needing and how we need to share the data so that it’s the most useful for the owner and the contractor. We need to organize our stuff! • Write data management plans together after discussing important data sources. For example, boring logs are typically written by hand. Since we need to know about the geology of the subsurface, we likely need to have a plan for getting boring logs into a database — whether that is done by the owner or the contractor. • • Develop a database! database. Using it involves wasting a lot of labor hours and likely having data integrity problems. Excel is a great tool, but it is not a Data gathering and data analysis are not equivalent. must get good data and analyze it regularly for it to do us any good. Otherwise, it’s like buying groceries that you never eat. Data needs to be accessible at the “speed of relevance.” does no good to get critical data days, weeks or months late. Data analysis will reveal unknowns. can be surprising. It Some of these lessons Monitoring frequency matters! important information. If we sample too much, we clog our systems with unneeded data. Use software that has sharable data. importable and exportable in open or industry-standard formats so it doesn’t get “locked away.” We must get good data and analyze it regularly for it to do us any good. Otherwise, it’s like buying groceries that you never eat. Treat data as a shared asset and resource. to do a level of analysis that the contractor cannot anticipate, but all analyses are only as good as the data provided. The old computer saying has never been truer: Garbage In, Garbage Out. The owner may need If we sample too little, we miss Data needs to be And finally, never let the perfect be the enemy of the good. If you didn’t start a data management plan yesterday, why not today? This issue of Deep Foundations covers some great examples and ideas on how to push our industry forward, from project information management systems, to uses of GIS and remote sensing tools. We have so many tools we could have only dreamed about even 10 years ago. We can use these incredible new tools like 3D glasses and data analytics for visualization, but only if we get our data organized and into a database. We get 90 percent of the way there, just by reliably getting our data into a database. It’s time for us to jump forward into the tools of today to make sure we don’t get left behind. We 106 • DEEP FOUNDATIONS • MAY/JUNE 2020
