Project professionals need to compile data sets and benchmarking information for many reasons—planning, troubleshooting, even satisfying government reporting requirements—but how that data is treated could undermine even the most ambitious efforts. Keep reading to see if your Project Team is making any of these common mistakes.
Waiting too long to understand which metrics you need to gather. It’s difficult to collect the right information (and enough of it) if you’re starting late in the game. Instead, devote time early in the process to understanding how much and what sort of data you’ll need. You can then put resources, such as data collection hardware or software, in place.
Not planning for the storage needs of your data. This is especially common with large data sets, where Project Teams underestimate the type or quantity of storage required to hold all their information. Assuming you can put everything on a small flash drive might leave you scrambling for terabytes of storage at the last minute, and could cause you to lose data during the transition from a too-small storage system to something more appropriate.
Collecting data without detailed plans for its analysis. Gathering information is great, but if your Project Team doesn’t anticipate the resources needed to analyze new data and do something useful with it, it’s just time and money down the drain. If your team isn’t equipped for comprehensive data analysis, consider contracting with an outside specialist to ensure you’re maximizing the return on your data gathering investment.
Omitting data quality oversight. Once data starts dumping into your storage system or collection platform, you can’t assume things will continue without a hitch. It’s important to regularly monitor the data stream coming in for potential errors or glitches, and the database itself should be checked periodically to ensure nothing has been corrupted mid-project.