Six business goal setting template examples will illustrate the application and benefits of a 30,000-foot-level predictive performance reporting methodology. Organizations benefit when they use this form of reporting within their operational excellence deployment and overall business management system.
Executives are often presented a monthly summary of the current level of key performance indicators (KPIs) in their organizations. Often information from this goal setting theory approach is presented as a PowerPoint presentation where the last month’s data is reported with possibly some previous months. Red-yellow-green scorecards may be used to track against goal setting objectives; however, stoplight scorecarding has issues which will later be illustrated through the goal setting worksheet examples.
Traditional goal setting and track-reporting against these goals can:
- Divert much resource from other tasks that are important to the business.
- Provide only historical observations (i.e., no prediction statement).
- Variance to a goal that may have been arbitrarily set and does not have direct aligned to overall business needs.
- Are dated relative to the timeliness of the information presented.
Instead of using a stoplight goal setting theory approach to scorecards, organizations gain much benefit when they use a 30,000-foot-level reporting approach that provides, when appropriate, a prediction statement of what could be expected in the future if nothing changes. If there is process stability with 30,000-foot-level reporting and the response is undesirable, some form of structured process improvement efforts are needed.
The following real six business goal setting worksheet examples (used with permission) illustrate the benefits of 30,000-foot-level predictive performance metric reporting over a traditional format, where these metrics can be automatically updated so that anyone authorized can get ready access to the metrics through a click of the mouse using Enterprise Performance Reporting System (EPRS) software.
In the following real business goal setting workshop examples, red-yellow-green scorecards are shown to have issues that can be resolved through 30,000-foot-level reporting.
Business goal setting worksheet issues
Using a business goal setting worksheets like the one shown above is common. However, this form of reporting can lead to much firefighting where the process is not really improved. These issues are highlighted in the article Stoplight Scorecards Issues and Resolution.
Business goal setting worksheet examples improved
The question is how would one undertake the objective to have ?business goal setting worksheet examples improved?? One could respond to this question as:
- Examine the data from a process point of view.
- Create a predictive performance measurement statement for the process whenever possible.
The need for predictive metrics is supported by the article Gartner Says Organizations Using Predictive Business Performance Metrics Will Increase Their Profitability 20 Percent by 2017.
What will be described below is how six of these metrics could be reported in a predictive performance metric format. The approach that will be used for this reporting is 30,000-foot-level for the table-numbered metrics 4, 13, 15.1, 17, 17.1, and 18.
ABC Scrap Costs of Production: Business Goal Setting Worksheet Examples 1
A highlight from the table above scrap costs of production reporting one observes:
With this report-out formation, one is to take action to determine what specifically occurred when the goal was not met for a month; i.e., the color was red. One doesn’t know what action, if any, occurred by simply looking at this data. However, from this form of reporting one does statistically know:
- If the process was really improved with a transition from red to green.
- Know what might be expected in the future.
Let’s now examine this data using a 30,000-foot-level reporting for scrap costs as presented in these goal setting examples.
With 30,000-foot level reporting, one first notes that scrap costs is a continuous variable. The first assess is for process stability, while the next effort is provide a prediction statement when the process is stable. For this continuous-data situation, the 30,000-foot-level individuals control chart assesses stability, while a probability plot provides a prediction statement. With 30,000-foot-level reporting there is also a statement at the bottom of the report-out which provides a prediction statement, when appropriate.
From this 30,000-foot-level report-out, one has no reason to state that the process is not stable. Data from the recent region of stability can be considered a random sample of the future. This data are then plotted on a probability plot. If the data follow a straight line, the data are presumed to be from the distribution associated with the probability plot; i.e., normal in this case.
From this individuals control chart, one notes that no improvements occurred as the stoplight scorecarding had indicated. The probably plot indicates an expectation that about 27% of the months we should expect not to achieve our goal of 1.41 or less.
Let’s now consider this goal setting in business objective. When goal setting in business for this particular type of metric would it be better to set have Specific Measurable Actionable Relevant, and Time-based goal setting (i.e., SMART goal setting) based on the mean? If this were done, one would tend to give focus to the process and not what happened specifically during the latest time period.
With 30,000-foot-level performance metric, rather than report-out proportion non-compliant per month, one could report-out the expected mean with an 80% frequency of occurrence. For this particular situation, this methodology could provide a good baseline for setting business goals.
This form of reporting for this particular situation would be very desirable. From this form of reporting, one would begin to view that this metric as the result of variability in the process and that improvement activities are needed to reduce the scrap costs from the process. A Pareto chart of the types of failures that occurred in the recent region of stability could provide insight to what issues occur most frequently. This insight can be very beneficial to target areas of the process that might cause these defectives occurrences.
ABC Quality Cost Production ($/unit): Business Goal Setting Worksheet Examples 2
The line item from the business goal setting worksheet examples for this metric is
There is a lot of red in this goal setting example. Let’s now evaluate this metric from a 30,000-foot-level point of view.
This report-out indicates that there was a special-cause situation in the individuals chart that warrants investigation. However, one should not react to all the ups and downs of the metric in the statistically calculated upper and lower control limit regions (UCL and LCL), which are function of the collected data and its variability; i.e., not what desired. Note how this report-out provides a very different perspective about the process than the stoplight scorecard goal setting theory application.
One could stage the process at the special cause region to examine how the process is performing since that the special cause condition. One perhaps did this assessment after understanding the special cause occurrence and then made adjustments so this particular occurrence does not happen again. The result from this effort would be:
Using the value in the goal setting worksheets for the monthly goal, one could state that the process is now stable where about 55% of the months will not meet the monthly objective.
Again, since this goal is not really a specification, a median best-estimate report-out with 80% frequency of occurrence seems to be a better report-out method.
This chart seems to be a good baseline to act as a goal setting tool from which SMART goal setting can occur. Again, with this approach would be given to improve the process as opposed to reacting to all the ups and downs in the common-cause stability region.
Customer Defects (ppm): Business Goal Setting Worksheet Examples 3
For customer defects in this business goal setting worksheet examples, a goal of 1000 parts per million (PPM) was given.
There is much red in this business goal setting worksheet line item.
Since the data from this example are pass/fail attribute data, a probability plot should not be created for the 30,000-foot-level report-out. A 30,000-foot-level attribute assessment for this data would be:
The gap in the plot occurred because the raw data set had a missing datum point.
The estimated performance for this chart was determined from the centerline of the chart. One can see that the process is producing about 4327 ppm units, where there was a goal of 1000 ppm. However, note how the value of zero is within the UCL and LCL limits? When this occurs, one should examine what is getting measured. If the metric is bounded by zero, this indicates that a data transformation may be necessary to establish stability and quantify predictability; however, a transformation should make physical sense.
For this data, an outside assessment indicated that a log transformation was appropriate. The result of this effort is the following:
When one has a transformation, they have no need to address the transformed units on the y-axis since when the process is stable a performance metric statement will be made at the bottom of the chart. The reader should note that even though there was additional complexity when creating the chart, the interpretation of the graphical output is similar to previous outputs and easy to understand.
The question one could ask is whether the above goal setting in business process application is for the overall process mean or individual months. For this type situation, a statement of how well the process is performing would be best, understanding that some months could have a higher reporting and others a lower one.
Total Unclean sales orders%: Business Goal Setting Worksheet Examples 4
The goal for this metric is 8. For this metric from the goal setting spreadsheet examples, there are many red points.
An attribute 30,000-foot-level predictive performance metric for this metric from the business goal setting worksheet examples would be:
The same discussion points that were made in the last data-plot situation can again be made for this plot. This plot could also be transformed because of the zero boundary; however, this was not done since the zero value is within the UCL and LCL limits.
This process indicates stability and that if the predicted response is undesirable a systematic process improvement effort is needed.
Avoidable Unclean Sales Orders -%: Business Goal Setting Worksheet Examples 5
Five was the result of the organization’s business goal setting effort for this metric. There are many red occurrences in this goal setting template response:
A 30,000-foot-level attribute report-out for this data set is:
One could have undertaken using a transformation for this report-out; however, this was not done since the zero value is barely inside the LCL. Similar to previous report-outs this process response is stable and has common-cause variation that, if considered unacceptable, would result in these metric enhancement needs pulling for a process improvement effort.
First Pass Yield (FPY) %: Business Goal Setting Worksheet Examples 6
The goal for first pass yield (FPY) is 96%. From this business goal setting worksheet examples illustration, we note:
This goal setting theory for reporting methodology indicates that everything appears to be in good order. Let’s now examine the data in a 30,000-foot-level report-out format:
From this goal setting in business report-out, the process appears stable with an estimated first pass yield of 96.7%. One should note that for a percentage response and if 100% is within the control limits, one should consider changing the response from percent acceptable to percent non-acceptable, where an appropriate transformation would be selected.
For this situation, the goal of 96% FPY was achieved; however, one might ask whether this was a SMART goal that benefited for the business as a whole. If a higher yield would seem to be beneficial, improvement efforts would then be appropriate.
In summary for these business goal setting work sheet examples, the following observations should be considered:
- In all the above comparison plots, a different decision was made about the process relative to actions or non-actions for the output formats. In five out of the six shown goal setting worksheet issues, there was a switching between green and red where the 30,000-foot-level reporting indicated that these transitions were from common-cause variability. Stoplight scorecarding can lead to unhealthy if not destructive behaviors that can cost an organization a lot of money. Organizations gain much from viewing the output of their process at the 30,000-foot-level.
- There is a tendency for reporting annually, as the charts above did; however, one should not be bounded by the calendar when creating 30,000 foot-level reporting. Several years of data could provide much more insight than a short calendar-year plot.
- Organizations need to look at their metrics collective to determine what metrics need focus so process improvement efforts benefit the enterprise as a whole would be given to these areas of the business. Organizations do not have enough resources to do a significant amount of improvement for everything. The above 30,000-foot-level approach for metric tracking throughout the organization can lead to improved SMART goal setting.
- An organization can have their metrics automatically reported at the 30,000-foot-level using EPRS software . Updates could be made daily. Those who have authorization and Internet access could get up to date information about their predictive performance metrics, where there is an alignment to an organization’s IEE value chain.
- The dynamics of status meetings can change to the better when an organization’s value chain and its associated 30,000-foot-level metrics are referenced during the meeting instead of giving a sole focus to the issues of the day.
The interpretation of 30,000-foot-level charts is not difficult once someone get familiar with the basic reporting methodology. However, there is a level of knowledge required to create 30,000-foot-level charts. Training options include:
- On-line 30,000-foot-level training provides guidance for creating these charts.
- These concepts of 30,000-foot-level reporting are also covered in Smarter Solutions’ Lean Six Sigma training.
- The charting techniques of 30,000-foot-level reporting are include in chapter 12 and 13 of Integrated Enterprise Excellence, Volume III .
More business goal setting worksheet examples can be found at:
A summary of other dashboard conversions to 30,000-foot-level performance reporting illustrations are available in the article Transitioning Frequently used Dashboards to Predictive Metric Reporting Examples.
Contact Us to set up a time to discuss with Forrest Breyfogle how your organization might gain much from an Integrated Enterprise Excellence (IEE) Business Process Management System implementation and 30,000-foot-level predictive performance reporting.