If you are a reliability engineer or work in maintenance, then you know how important – and how difficult – it can be to get accurate and high quality data. Can data collectors be “pushed” into collecting high quality data or would being “pulled” be more effective? This paper finds that managers should be careful of the degree to which “push” factors, such as managerial pressure and technological input control, are relied upon.
Roger Molina, Melinda Hodkiewicz, Elisa Adrisola and I looked at data quality in a water utility. Roger carried out this study for his postgraduate Honours degree and interviewed 20 data collectors. We combined this with a quantitative survey of 109 data collectors in a sequential, mixed-method design. You can see the citation by clicking here; or access a preprint version below.
What did we find?
These results have very important practical implications: External controls should be used with caution.
If most employees have low self-concordance (that is, they don’t see collecting data as personally relevant) then the money invested in improving the technology to control the input process should result in overall increases in the quality of data collected. On the other hand, if most employees do see data quality as important then the benefits will not arise and it is unlikely to be worth the money invested.
More important is the use of manager and supervisor pressure. In many industries, the traditional approach is to use monitoring and managerial sanctions to change behavior. As we have shown, however, this can have significant negative effects for those who might be intrinsically motivated. Rather than an habitual reaction towards sanctioning employees, greater training of supervisors to help them differentiate those who are motivated by self-concordance and those who are motivated by external controls should help in this regard.
This research suggests that alternatives need to be provided to the straightforward use of external, “push” factors. We are not suggesting that managers and supervisors do not monitor their employees and we are certainly not suggesting that technology not be used for input control. However, we propose that they not be the first port of call, nor relied upon completely.
An alternative approach might be one which uses two stages to change the behavior of the data collector. To begin, the organization could aim to increase the self-concordance of the employees. In the second stage, those who were still not collecting high quality data and whose self-concordance was not increased could be monitored more closely and reinforced accordingly by managers.
How do you increase self-concordance? Click here for more details on self-concordance. One suggestion is to make operators aware of how data quality ultimately makes their own work easier through more efficient maintenance routines. Another is to invest in leadership training that focuses on motivating and inspiring the operators as that has also been shown to increase self-concordance.