- determining whether enough observations are being collected for the sample size;
- Identifying if significantly different data are observed between days or shifts; and
- making adjustments to the study process if inconsistent data are received from observers.
Figure 1 shows an example of such a summary of observation data.
Additionally, the data can be grouped to summarize support and delay activities by area of the plant (Figure 2).
The compiled data allow us to assess and report results by loss categories and use this in cause-and-effect analyses to identify improvement opportunities and address loss percentage levels in each subcategory. The data summaries calculate direct activity percentages and break down observations by indirect subcategories for reporting and improvement planning. Figure 3 illustrates a typical format for presenting these data.
This summary gives management detailed information across a wide range of parameters, such as type of craft personnel, area of plant, and daily and hourly activity levels. We suggest that management share this information with the workforce and together outline strategies for improvement based on factual data instead of estimates, suppositions or hunches. Indeed, it is our experience that workforces respond to opportunities more proactively once there is hard evidence to substantiate potential benefits. Sharing such data tends to encourage participation in the process of data analysis and improvement planning, which assists in sustaining any implemented changes.
A powerful tool
Direct utilization or direct activity is the single element that most drives craft productivity determination. So, companies will benefit from taking a more rigorous approach to assessing it, gaining a better understanding of the opportunities and potential for optimizing labor productivity. A statistically valid LAA is the best method for calculating direct utilization and quantifying delays and losses. The measurement of activity in terms of direct, delay and support elements provides an excellent approach to identify and categorize utilization levels and to target and prioritize improvement efforts in the various support- and delay-activity loss categories. These categories can then be re-calculated in subsequent LAA studies to track improvement .
My experience in working with clients indicates that most organizations do not use a rigorous approach for determining direct utilization. However, those organizations that implement such approaches derive significant value and often schedule follow-up efforts to assess gains following focused improvement efforts. Such organizations typically apply benchmarking and best-practice approaches to drive toward best-in-class performance. Hopefully, your organization can use LAA in its quest to achieve optimum productivity performance.
Timothy J. Finigan is Senior Director Performance Technology for Fluor, Greenville, S. C. E-mail him at Tim.Finigan@fluor.com.