Tracking Performance over Time

Tracking performance over time can be accomplished using either one of two methods which are Run Charts or Control Charts.  Both methods use time as the baseline and the performance measure as the measurement that is tracked over time.  The major differences in the methods relate to the measures of demarcation on the charts.  Run Charts have a center line that represents the mid point of the measurement that is being tracked.  Control Charts have a center line that represents the average of the measurement that is being tracked and lines above and below the centerline that are estimates of 3 standard deviations about the average of the measurements.

In both of the charts time is the X axis.  The data is plotted in succession over time.  The charts can be segmented by specific time periods such as setting the baseline and after improvements have been implemented.  You will easily see the before and after results.  We can measure the difference between the before average and the after average to calculate the magnitude of the improvement.

Tracking of performance is also a control for maintaining the gains from the improvements.    The Run Chart or the Control Chart provides a method to continuously evaluate performance and point out when corrective actions should be taken or when the process should be left alone.

Whenever we contemplate improving a process the baseline for the critical performance metric(s) must be established before any corrective actions are taken.  By doing this you will always be able to evaluate the impact of the improvements by measuring from the baseline to the future state of process performance.  In the rare case where the corrective action doesn’t work the tracking charts will point that out quickly so an alternative action can be taken.  I am sure that you can remember when a great idea just did not work so it is always best to track performance to validate the actual impact of our improvement efforts.

Performance Measurement

Measuring performance is the key for driving dramatic improvements in any organization.  Choosing the right performance measures, or metrics, is essential to hone the focus of improvement project teams.

The key to honing the focus for the project team is to select measurements that are relevant to the level of the organization that is being impacted by the improvement project.  If the team is working on improvements at the work cell, or production line level within the organization having measurements that resonate with the Corporate Level of the organization won’t make much sense.  The measures must be selected that are appropriate for the level of the organization where the improvements are being made.

Examples of performance measures and the level within the organization follow:

Corporate Level

• Return on Net Assets
• Market Share
• Total Stockholder Return
• Capacity Utilization
• Economic Value Added

Division Level

• Customer Loyalty
• Target Cost Attainment
• Market Share by Division
• Order Fulfillment Cycle Time

Business Unit Level

• Business Unit Revenue
• Business Unit Margin
• Quality Cost
• Process Efficiency
• Staffing Plan Attainment

Work Cell / Production Line

• Cycle Time
• Process Yield
• Employee Satisfaction
• Outgoing Quality

A rating scale can be used to help with selecting the Key Performance Metric, or the CTQ (Critical to Quality) Metric, that will drive the improvement at the given level within the organization.  The rating scale follows:

Rating Scale for Performance Measures

Relevance

1. Not at all linked to strategic objectives
2. Poorly linked to strategic objectives
3. Indirectly linked to strategic objectives
4. Strongly linked to strategic objectives
5. Directly linked to strategic objectives

Usefulness

1. Too detailed to provide useful information
2. Rarely provides useful information
3. Occasionally provides useful information
4. Usually provides useful information
5. Constantly provided useful information

Understandability

1. Very complex, hard to understand
2. Understandable with study
3. Neutral
4. Fairly easy to understand
5. Very easy to understand

Availability of Data

1. Would be very difficult to obtain
2. Will have to be measured manually
3. Can be obtained by combining information on different reports
4. Can be easily derived from information on existing reports
5. Currently available from existing reports

Overall Average Score

1. Extremely poor indicator / motivator
2. Poor indicator / motivator
3. Average indicator / motivator
4. Good indicator / motivator
5. Excellent indicator / motivator

The metric with the highest overall score should be used to drive, monitor, and maintain the gains form the improvement efforts.  Choosing the right performance measures is the key for driving dramatic improvements in any organization.