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.
Impacting organizational culture is a long-term, never-ending endeavor. Many companies struggle with maintaining and sustaining cultural initiatives because their impact may not be felt for several years. Culture, as an organizational construct, is a subjective factor not directly measurable by any instrument, survey or metric. Yet, everyone is impacted by culture and can describe when it turns bad.
During the late 1970s, Judy Komaki and her behavioral psychologist colleagues used their methodology in a food manufacturing facility to improve the safety performance by focusing on reinforcing safe behaviors (Komaki, Barwick, & Scott, 1978). This was the birth of behavior-based safety (BBS).
To stay relevant, silence distracters and continue to help organizations eliminate death on the job, behavior-based safety (BBS) processes need to experience a “step-change.”
