In a recent poll we asked EHS professionals: what is your biggest barrier to collecting accurate EHS data? The clear winner was “cultural barriers to data entry” followed by “training of data collectors” which received 39% and 30% of the vote respectively. Culture is a word that is commonly used in the EHS industry and building a safety culture is often a focus of EHS professionals.
So, what is data accuracy? Data accuracy is one of the “six dimensions” of data quality and it can be defined as the “degree to which the data correctly describes the ‘real world’ objects being described.” This definition makes it easy to see how poor data accuracy could greatly impact your ability to use your data effectively.
Many companies starting their data analytics journey make the mistake of skipping the data cleaning process all together. None of us want to see how the sausage is made, we just want the bratwurst to magically appear. But as we have seen over, and over, insightful analytics cannot be achieved with poor data quality.
Manufacturing leaders know that people and processes are most productive when safety, compliance and operational objectives align. Some people used to fear that focusing too much on environment, health and safety would undermine productivity.
A recent survey of manufacturing executives indicates many respondents (67 percent) are pressing ahead with plans to invest in data analytics even as they pare back spending in other areas to combat tough business conditions.