Organizations often use a performance metrics system that only provides point to point comparisons. For example, the currently monthly profitability of a business might be compared to last month. Any movement that is not desirable often leads to a search for what happened.
This what-happened investigation can result in the treatment of common cause variability as though it were special cause. Wasteful firefighting often is a result of traditional metric report-outs and nothing positive happens relative to making a metric improve over time.
A 30,000-foot-level predictive reporting methodology addresses this traditional metric reporting format shortcoming. With 30,000-foot-level metric reporting, a predictive statement assessment is made. If a process output performance is stable and the futuristic response is undesirable, this metric desirable shortcoming pulls for the creation of a process improvement effort that enhances the measurement’s response.
Enterprise Performance Reporting System (EPRS) software provides a means to easily create 30,000-foot-level report outs. A statistical shift in the time-series portion of a 30,000-foot-level metric is an indicator that the process output changed, either to the betterment or degradation. When this happens a new predictive process statement can then be made using this software.
This predictive analytics models example non-normal data illustrates the benefits of 30,000-foot-level performance reporting in an Integrated Enterprise Excellence (IEE) Business Management System.
Predictive Analytics Models Example Non-normal Data: 30,000-foot-level Charting Read More »
Traditional p chart control limits formula calculations can lead to firefighting common cause variation as though it were special cause. This “false signal” issue can occur when common-cause process variation occurs between subgroups.
Issues and Resolution to p chart Control Limits Formula False Signals Read More »
An individuals chart that can provide a process capability statement too is a 30,000-foot-level metric report-out. At the enterprise level, 30,000-foot-level report-outs can be used in an Integrated Enterprise Excellence (IEE) Business Management System.
Individuals Chart Report that can also Provide a Process Capability Statement Read More »
A probability plot can be used to quantify process performance through a 30,000-foot-level report-out. In one chart, a 30,000-foot-level report can include a process stability assessment through an individuals chart(s) and a probability plot to make a predictive statement for process performance. This statistical foundation supports the broader discipline of predictive performance metrics, where organizations
Quantifying process improvement impact using a 30,000-foot-level chart is very beneficial for a Lean Six Sigma project or Kaizen event deployments. Quantifying Process Improvement and 30,000-foot-level Predictability Statements Note: Content of this webpage is from Chapters 12 and 13 of Integrated Enterprise Excellence Volume III – Improvement Project Execution: A Management and
Quantifying Process Improvement Read More »
A major issue with the c chart formula is that if a process has between subgroup variability that is common cause false special cause signals can often occur. This is an important concept that everyone who uses a c chart understand. A 30,000-foot-level metric tracking approach not only gets around this problem but also provides
Issues and Resolution to C Chart Formula Problems Read More »
This predictive analytics models example multiple samples in subgroup illustration will demonstrate the value of 30,000-foot-level reporting which is provided in the Integrated Enterprise Excellence (IEE) Business Management System.
This predictive analytics models example infrequent failures describe benefits of 30,000-foot-level reporting in an Integrated Enterprise Excellence (IEE) Business Management System.
Predictive Analytics Models Example Infrequent Failures: 30,000-foot-level Charting Read More »
Process capability problems and solutions to those issues is very important for an organization. Another way to state this need is resolving the process capability index issues of Cp, Cpk, Pp, and Ppk is essential so that organizations will take appropriate actions from their process capability reporting. The solution to this problem is easily
Process Capability Index: A Better Way Read More »
Transforming individuals control chart data is an important consideration to avoid common cause variability appearing as special cause events. The transformation of data (for situations that make physical sense) is easily accomplished in 30,000-foot-level tracking metric report-outs, which also can provide a predictive process capability statement — in one chart.
