Process Measurements (See also Section 9). In deciding what aspects of the process to measure,
we look for guidance to the process mission and to our list of customer needs. Process measures
based on customer needs provide a way of measuring process effectiveness. For example, if
the customer requires delivery of an order within 24 hours of order placement, we incorporate into
our order-fulfillment process a measure such as “time elapsed between receipt of order and delivery
of order,” and a system for collecting, processing, summarizing, and reporting information
from the data generated. The statistic reported to the executive owner will be one such as “percent
of orders delivered within 24 hours,” a statistic which summarizes on-time performance. The team
will also need data on which to base analysis and correction of problems and continuous improvement
of the process. For this purpose, the team needs data from which they can compute such
descriptive statistics as distribution of delivery times by product type, and so on. The uses to which
the data will be put must be thought through carefully at the time of process design to minimize
the redesign of the measures and measurement systems.
Process measures based on cost, cycle time, labor productivity, process yield, and the like are
measures of process efficiency. Suppose that a goal for our order-fulfillment process is to reduce
order-picking errors to one error per thousand order lines. Managing to that goal requires identification
of order-picking errors in relation to the number of order lines picked. For order-picking errors
that are inadvertent—that is, when they happen, the picker is unaware of them—measuring them
requires a separate inspection to identify errors. In a random audit on a sample of picked orders, an
inspector identifies errors and records them. As with delivery-time measurement, the team must
think through all the uses it will make of these measurements. For a report of estimated error rate,
the data needed are: number of errors and number of order lines inspected. To improve process performance
in this category, the data must help the team identify error sources and determine root
cause. For that to occur, each error must be associated with time of day, shift, product type, size of
package, etc., so that the data can be stratified to test various theories of root cause.
While not a measurement category, process adaptability is an important consideration for process
owners and teams. Adaptability will be discussed later in this section.
Process measurements must be linked to business performance. If certain key processes must run
exceptionally well to ensure organization success, it follows that collective success of the key processes
is good for the organization’s performance. Process owners must take care to select process measures
that are strongly correlated with traditional business indicators, such as revenue, profit, ROI, earnings
per share, productivity per employee, and so on. In high-level business plan reviews, managers are
motivated and rewarded for maintaining this linkage between process and organization performance
measures because of the two values which PQM supports: organization success is good, and process
management is the way we will achieve organization success.
Figure 6.7 shows some typical process measurements and the traditional business indicators with
which they are linked. To illustrate, “percent of sales quota achieved” is a traditional business indicator
relating to the business objective of improving revenue. The special-contract management
process has a major impact on the indicator, since more than 30 percent of U.S. revenue comes from
that process. Therefore, the contract close rate (ratio of the value of firm contracts to the total value
of proposals submitted) of the special-contract management process is linked to percent of sales
quota and other traditional revenue measures, and is therefore a measure of great importance to management.
Measurement points appear on the process flow diagram.
Control Points. Process measurement is also a part of the control mechanisms established to maintain
planned performance in the new process. To control the process requires that each of a few
selected process variables be the control subjects of a feedback control loop. Typically, there will be
five to six control points at the macroprocess level for variables associated with: external output,
external input, key intermediate products, and other high-leverage process points.
The control points in the special-contract management process are represented graphically in
Figure 6.8. Feedback loop design and other issues surrounding process control are covered in detail
in Section 4, The Quality Control Process.