Creating precise labor standards is a task that requires a lot of precision in order to benefit your organization. As you seek to create these standards, here are a few mistakes to avoid.
Being fooled by variants in data
It’s good to measure your processes as precisely and specifically as possible, but it’s also important to eliminate pieces of data that will inaccurately skew your results. Say one employee took a lunch break at the wrong time or someone was ill and working slower than usual — a good time study software will help you to identify which of your results should qualify as “outliers,” and be eliminated from your data set, so that your results can be as accurate as possible before integrating them to your work standards database.
Conducting the study
Through the software’s mobile app, conducting the study could not be easier. The hard work and user errors of stopwatches are gone — the application records times to 1/100th of a second! Simply open the app, conduct the time study, and then transfer the data (through the app) back to your computer, to move on to the analysis stage of the study. Using a software not only takes the user error out of your studies, but it also improves the objectivity and consistency of the data collected when it is conducted by multiple parties.
Analyze the study
Once you have all of the raw data about your industry’s efficiency, the most important step in such a study is an effective and fruitful analysis of that data. Using a software like UMT Plus takes the guesswork out of analysis with a strong analytical module that gives you the tools to analyze your data completely and effectively: view reports and graphics instantly, and share these results.
As you seek to craft appropriate labor standards or to improve the processes and operations within your industry, a combination of a work measurement software and a labor standards database is a great choice to ensure simplicity and accuracy at every step, from setting up the study to managing your whole organization’s work standards.