Pyzdek Institute » constraint

Selecting Winning Projects

Thomas Pyzdek — Wed, 16 Sep 2009 20:55:46 +0000

Software helps select the best projects.

In a previous column I discussed how Six Sigma projects should be selected using the theory of constraints (TOC). After attempting to do so, most discover yet another constraint: money. In most organizations there are more opportunities for improvement than one can afford to pursue. If it isn’t money, some other resource will be in short supply, such as talent. And as if that weren’t bad enough, the task is further complicated by uncertainty of the payoff from the projects and their probability of success.

An exciting computer software product known as Crystal Ball Pro by Decisioneering makes it possible to select winning projects by factoring in all of the relevant factors. It does so by simulating various scenarios thousands of times, then choosing those that perform best.

For example, the research and development group of a major public utility has identified eight possible Six Sigma projects. A net present value analysis has computed:

The expected revenue for each project, if it’s successful

Its estimated probability of success

Its required initial investment

Using these figures, the finance manager has computed the expected return and the expected profit for each project. Unfortunately, the available budget is only $2 million, and selecting all projects would require a total initial investment of $2.8 million. Thus, the objective is to determine which projects will maximize the total expected profit while staying within the budget limitation. Complicating this decision is the fact that both the expected revenue and success rates are highly uncertain. Figure 1 shows a spreadsheet model for this problem.

Figure 1: Project Selection Spreadsheet

The decision variables in column H are binary; that is, they can only assume the values zero (do not fund the project) and one (fund the project.) The assumption variables are in the “Expected Revenue” and “Success Rate” columns. Crystal Ball Pro will use simulation to evaluate a range of values for these two columns. The total profit, shown in cell G19, is a forecast variable whose values depend on the assumption and decision variables. The idea is to find the combination of projects (determined by the decision variables) that maximize total profit, taking into account the variation in expected revenue and the probability of success.

The project selection spreadsheet isn’t quite good enough given that the number of possible sets of projects is too large to identify by trial-and-error. Crystal Ball Pro can help here too. It includes a
program, called OptQuest, which will perform a search to find the optimal package of projects (see Figure 2).

Figure 2: Progress Toward a Solution

The best solution OptQuest found (in a search that I limited to 10 minutes) is to fund all projects except 3 and 5 (see Figure 3). The expected net profit is $1.54 million. Note that the distribution of total profit includes a number of scenarios that would result in a net loss. This occurs because OptQuest was asked to find the solution that maximized expected (average) total profit, but it can limit searches to profitable software solutions too.

Figure 3: Results

Selecting Six Sigma Projects

Thomas Pyzdek — Thu, 06 Aug 2009 23:36:03 +0000

Sometimes just determining which projects to undertake isn’t enough.

Six Sigma is project-intensive. Large firms, such as General Electric, report completing as many as 7,000 Six Sigma projects in a single year. Even much smaller companies can complete several hundred projects per year. But this should come as no surprise, as projects are the means by which Six Sigma converts knowledge into bottom-line results.

However, not all Six Sigma projects produce bottom-line benefits; many produce only local improvements. In my June column I described how to use the theory of constraints (TOC) to decide where in the process to conduct Six Sigma projects. But we need to go even further. In addition to telling us where to conduct Six Sigma projects, knowing the process constraints also helps us determine what the focus of the project should be.

Six Sigma projects address three different areas of potential improvement: quality, cost and schedule. Critical characteristics in the product, process or service are identified using CTx notation: Critical-to-quality characteristics are designated CTQ; critical-to-cost, CTC; and critical-to-schedule, CTS. This classification scheme, combined with the TOC, can help focus Six Sigma projects by defining project deliverables in terms of their impact on one or more CTx characteristics.

Figure 1: A Simple Process with a Constraint

Consider the simple process in Figure 1. The process is producing a product for which there is a market demand of 20 units per week. However, the best this process can deliver is seven units per week because that’s the best step C can do.

Applying the TOC strategy described in another post, we know that Six Sigma projects that affect step C should be given priority, those affecting steps D and E second priority, and those affecting A and B third priority. This tells us where to focus our efforts. The CTx information can help us determine what to focus on.

Assume that you have three Six Sigma candidate projects all focusing on process step C, the constraint. The area addressed is correct, but which project should you pursue first? Assume that one project will improve quality, another cost, and another schedule. Does this new information help? Definitely! Table 1 shows how this information can be used.

Table 1: Throughput Priority of CTx Projects That Affect the Constraint

Projects in the same priority group are ranked according to their impact on throughput. The same thought process can be applied to process steps before and after the constraint. The results are shown in Table 2. (Note that Table 2 assumes that projects before the constraint don’t result in problems at the constraint.) Remember, impact should be measured in terms of throughput.

Knowing the project’s throughput priority will help you make better project selections among project candidates. Of course, the throughput priority is just one input into the project selection process; other factors–for example, integration with other projects, a regulatory requirement or a better payoff in the long-term–may lead to a different decision.

Table 2: Project Throughput Priority vs. Project Focus