Case:
This firm was experiencing a sales cycle that was approximately 8 months long. The growth goal was to reduce the sales cycle by approximately 40%. They were all wondering how to emulate changes in the real world when they had been challenged to close the project in less than six months.

Course of action:
The Six Sigma team built a process model that represented the real world sales operation. They then made systematic improvements and tested the outcomes on the computer.

Results:
As a result of the model the team has been able to meet and surpass the goal of cutting the sales cycle by 36%.

Case:
This consumer products company decided to focus on helping their clients (primarily large corporations) enhance their visual media and reduce the time it took to develop the visual aspects of packaging, brochures, billboards, sales displays, etc. Reducing cycle time and enhancing visual technology processes became their central goal.

Course of action:
To accomplish this objective, the Six Sigma team decided they needed computer mapping/flowcharting tools and modeling to determine critical workflow bottlenecks and improve cycle time. Such a massive undertaking required high end technology. The team decided to use simulation modeling to help them evaluate and fine-tune the data and results.

Results:
Results from simulation modeling showed two activities as bottleneck areas. Running the model with new times showed the job cycle dropping by 22 days (from 155 to 133 days). However, activity utilization stayed above 95% (a good sign!). Process engineering using new technology, which would cut at least ten days from the two activities, was recommended to the customer.

Case:
The process of obtaining a patent crossed so many organizational boundaries that certain, unusual patent cases set up a chain of events which could exceed the statutory bar. Not being able to see the entire process interact made it difficult to spot potential problems.

Course of action:
The Six Sigma team collected information about the entire intellectual property process and constructed a process map to do simulation modeling. This allowed Them to model their current process and evaluate how implementing changes to it would affect the system over time.

Results:
The process map allowed the intellectual property department and management to see the problems and the solutions. As a result, they will increase the frequency of the patent board meetings and outsource patent searches and other time consuming legal processes. These changes will shorten the time required to process each invention disclosure and patent application significantly. Unusual process flows that could cause them to lose a patent or invention were identified and corrected.

Case:
In one financial services Six Sigma project in the southern United States, a customer segment of“40-and-over” individuals with incomes in excess of $80,000 identified requirements of more “human” contact, flexible hours and accurate answers to first time questions.

Course of action:
The organization analyzed their current process and found there were gaps in availability of resources at specific times and they often provided inaccurate answers to their customers. The team assigned to the project was able to examine a process, assess defect levels and validate proposed corrections, proving the results were both correct and sustainable.

Results:
The revised process adjusted schedules and led to new training modules that prepared representatives to provide correct responses the first time. Customer satisfaction and hence retention increased 55%.

Case:
Another financial services group identified a need for fast response to credit applications.

Course of action:
The Six Sigma team evaluated the existing application review process and outlined every opportunity to compress cycle time. They developed a revised process and tested the operation to verify that delivery of service met customers’ expectations.

Results:
Not only was the business able to meet the need; they actually exceeded the routine expectation and established a marketable advantage that increased overall revenue by > 20%.

Case:
A major US company was having difficulty with its cash conversion cycle time.

Course of action:
A baseline of the process was performed from order input through collection. The baseline showed that due to the complexity of the process there were many process and organizational locations where problems could and did occur. There was no short list of solutions that would eliminate the errors negatively impacting cash conversion. Furthermore, the feedback loops, which could have reduced the number of repeated errors were cumbersome, which prevented learning and improving from occurring. There was a relatively high turnover rate and the complexity of the process made training a lengthy and expensive process. The following changes were made to improve the cash conversion cycle time:

• Redesign the organization into customer support teams, with each required function being represented on each team
• Mistake proof critical processes
• Co-locate the team members into autonomous groups
• Develop goals and metrics to evaluate the customer team performance and focus the team on the overall process.
• Provide a progressive training platform for associates.

Results:
The new process allows for teams to become familiar with their unique customers’ requirements and to improve the existing process with a continuous and short feedback loop. Metrics allow them to focus on the critical few versus the trivial many aspects of their process. 

Case:
A supplier to a major US manufacturer made the decision to stop providing critical components. As a result several programs are at jeopardy as they require the use of this supplied component. The supplier made the decision because the equipment was 30-40 years old, yields had traditionally run at 60% and the margins were low. There were no other suppliers found that would produce these critical components. The manufacturer was forced to buy the exiting equipment and produce the components. The goal was to produce the parts, for which there was no existing knowledge, and to improve the yield if possible. It was also a foregone conclusion that new equipment would have to be purchased.

Course of action:
A baseline of the extrusion process was performed and a vast list of potential factors was identified during Process Mapping. It was also determined, through Measurement System Studies that the measurement systems were not capable of measuring the parts. The measurement systems were improved and several screening designed experiments (DOEs) were conducted. Results showed a few key factors to be important. Follow-up optimization experiments were run. In addition, some of the input devices that were not working on the equipment were repaired. The process was producing 100% yield within 3 months on existing part numbers. The next step was to produce parts that had not been previously produced. The first parts off of the new die met the desired specification, although slightly off target. Based on the process knowledge gained from the previous experiments one of the critical factors was adjusted. Within one shift the new parts were being produced to specification and on target. Finally the purchase order for new equipment was cancelled.

Results:
Total cost savings: $3,000,000. Time to completion: 3 - 4 months.

Case:
A major US corporation identifies a cash flow problem. Further analysis reveals that inventory levels are high and turns are below most major competitors. In addition a technology change and a proliferation of models amplify the issue.

Course of action:
A baseline of the existing order fulfillment process is conducted. It quickly highlights some key leverage points in the order fulfillment process. Furthermore it becomes apparent that much of the current inventory is present due to internally generated variation versus customer driven order variation. As a result the following changes are made to accomplish the goals.

• Implementation of a Pull System for the order fulfillment process. This pull system spans from supplier through manufacturing, logistics to the customer. The previous order fulfillment process was managed via an MRPII system.
• Determination of inventory levels using economic and statistical methods in an integrated approach.
• Implementation of appropriate inventory management models to minimize cost given various real world conditions in the supply chain (flow production, batch production, remanufactured parts inflow etc.).
• Revision of the planning process to support the order fulfillment process.
• Training of analysts to determine the appropriateness of forecast models.
• Reduction of internally generated variation

Results:

Inventory reduction post full implementation: > $20,000,000