The objective of this chapter is to identify key operational measures that may be used to study process flows. They are linked together using Little's law. We then present a series of examples that show how process flow analysis may be used to study performance. The objective is to study current performance as well as identify target areas for improvement. We also link the operational measures of performance to financial measures.
In a class of 100 minutes we start by discussing the importance of building a time based capability in today's competitive environment. We then establish Little's law to set up other operational measures - namely inventory and throughput that impact flow time. Several examples from the chapter are discussed to make this relationship clear. We then link these operational measures to financial measures to identify what form improvements may take. We then discuss the Kellogg CRU Rental case to demonstrate how such an analysis may be used to identify key areas for improvement. 3.2 Additional Suggested Readings
We assign a short case as supplemental reading for the analysis of process flows. The case is used to do a thorough analysis of flows and identify key drivers of cost and revenue in a process. This understanding is then used to identify actions that improve performance. * “CRU Computer Rentals”. Kellogg Case. Author: Sunil Chopra. Available from: http://www.kellogg.northwestern.edu/cases/index.htm. Suggested assignment questions are contained in the case.
3.3 Solutions to the Chapter Questions
Discussion Question 3.1
The opposite of looking at average is looking at a specific flow unit’s flow time, and the inventory status and instantaneous flow rate at a specific point in time. Because flow times change from flow unit to flow unit, it is better to look at the average over all flow units during a period of time. Similar for inventory and throughput.
Discussion Question 3.2
In practice, one often tracks inventory status periodically (each day, week, or month). Flow rate is typically also tracked periodically (even more frequently than inventory status because it directly relates to sales). It then is easy to calculate the average of those numbers to obtain average inventory and throughput during a period.
In contrast, few companies track the flow time of each flow unit, which must be done to calculate the average flow time (over all flow units during a given period).
Discussion Question 3.3
First, draw a process flow chart.
Second, calculate all operational flows: throughput, inventory, and flow time for each activity. Third, calculate the financial flow associated with each activity. If the activity incurs a cost (or earns a revenue), the cost or revenue rate is simply the throughput times the unit cost or revenue. If the inventory incurs a holding cost, the inventory cost rate is simply the average inventory times the unit holding cost. Fourth, summing all revenue rates and deducting all cost rates yields the profit rate, directly broken down in terms of the relevant throughputs and inventory numbers. The latter thus are the minimal set of operational measures to predict financial performance.
Discussion Question 3.4
For the department of tax regulations we have
Average inventory I = 588 projects,
Throughput R = 300 projects/yr (we assume a stable system). Thus,
Average flow time T = I / R = 588 / 300 = 1.96 yr.
This is larger than six months. So we should disagree with the department head's statement.
Discussion Question 3.5
If GM and Toyota have same turns, and we know that
turns = 1/flow time = 1/T,
it follows that their average flow times are the same. We also know that Toyota's throughput is twice that of GM. Thus, from I=RT
it follows that Toyota has twice the inventory of GM. Thus, the statements are inconsistent, both companies have the same flowtime but Toyota has higher...