Appendix FExperiences with Using a POLCA Simulation Game

Guest author: Hans Gerrese

Leanteam is a consulting firm formed in the 1990s with experience in assisting many companies in the Netherlands in implementing Lean. Around 2006, we noticed that the Lean concepts were no longer a good fit for the problems that our customers were encountering as a result of the market trend towards lower and lower volumes and higher variety. Specifically, we saw that companies in the high-mix, low-volume and custom (HMLVC) environment were struggling to apply many of the Lean tools. Using the internet, we began searching for some more relevant tools and came across POLCA as one of the tools developed as part of the Quick Response Manufacturing (QRM) strategy. Both POLCA and QRM were completely new to us. It also seemed at the time that they were new to Europe as a whole, and we did not have local resources knowledgeable on these subjects. However, POLCA seemed to fit what we were looking for, and so several of our principals decided to invest in some trips to the U.S. during 2006–2007, to attend workshops conducted by Professors Ananth Krishnamurthy and Rajan Suri at the Center for Quick Response Manufacturing, University of Wisconsin–Madison.

Challenges in Communicating the Right Message

We returned from our trips to the U.S. with some excitement about the potential for QRM and POLCA in the Netherlands. However, as we tried to roll out these concepts to our clients, we found a lack of appreciation of the need for lead time reduction. Managers had not heard about QRM and also had no understanding of how long lead times harmed their businesses, so they did not absorb the QRM message. Instead, when we made our presentations, they tried to compare QRM with Lean and so they looked for tools within QRM which they could use in their organization to complement their existing Lean programs. With the shift to HMLVC manufacturing, these companies were experiencing increasing problems of managing their orders and workload, and were looking for tools that could help them in taking back the control over their production. So, as they looked at the tools within QRM, they latched onto POLCA, since this system was seen as the tool that would help them resolve their planning and control problems. Thus it was that during our early efforts we received a lot of inquiries from manufacturing companies that wanted to implement POLCA in their organization.

As is usual with these kind of requests, as a consultant you first arrange a meeting with the customer to hear and see what their problems are. What we observed were disorganized shop floors with very high work-in-process (WIP), too many open orders on the shop floor, lots of rework, and people working hard, including a lot of overtime. But at the same time, a lot of the hard work included running around and chasing down jobs, and dealing with supervisors, who were changing priorities every hour but still yelling that jobs had to be done quickly. The end result was employees getting demoralized and losing interest in doing a good job. Our analysis was that the solution of this problem was not just implementing POLCA, or, as they saw it, a better “planning tool.” The root cause of the problems lay much deeper and the solutions required management to first create cells and simplify the work flow, and then to focus on lead time reduction as a goal, including such strategies as planning for spare capacity. POLCA could then help as a planning and control method to make the whole system function properly.

In summary, our observations showed that for many of these companies, implementing POLCA was not the first step. But to drive this point home, we had to teach these customers what POLCA was and when and how you could use it. This was not easy—we found it very difficult to explain just through presentations what POLCA really is, what it could offer, and particularly the prerequisites for implementing POLCA. Managers in these companies were only focused on “planning” and felt they just needed a good planning tool to solve their problems.

We decided that we needed a hands-on simulation game to demonstrate what POLCA was and how it worked. We felt that, through the game, participants would also understand the pre-conditions for implementing POLCA. As a starting point for our game, we looked at the POLCA game developed by the Center for Quick Response Manufacturing (see Appendix I), which we had experienced when we attended the workshop in 2006. This is a production game in which participants have to fabricate and assemble custom partitions with doors, windows, or both. The participants actually use thick and thin paper stock to simulate the various items being produced, along with scissors and scotch tape to do the fabrication and assembly operations. This game is played in two rounds, the first one using Kanban, and the second using POLCA, so the game also helps to point out the differences between these two systems, as well as the advantages of POLCA in HMLVC production.

Using our experience with this game as a base, we decided to develop our own game. Since a lot of the companies that we dealt with were already familiar with Lean and Kanban, it was important to maintain the goal in the U.S. game of demonstrating the difference between Kanban and POLCA. Beyond this, we developed our game with two additional goals. First, we wanted the game to involve a product that people could relate to in their everyday life, and second, we wanted to increase the impact of dynamical changes during the game. The reason for this latter goal was that in our initial explanations of POLCA, people were not clear about the added value of the POLCA cards, given that there was already an Authorization List with a sequence of dates for each cell. “Since the jobs are already sequenced at each cell,” people asked, “the team already knows its priorities, so why do we also need the POLCA cards?” Hence, we felt that our game should clearly show the benefits of having both the Authorization Dates and the POLCA cards. Later, we discovered one more goal for the game we had developed: it also ended up being very useful as part of the training for employees at companies that wanted to implement POLCA.

Details of Our POLCA Game

To satisfy the first of our additional goals for our POLCA game we decided that participants would build cars with Lego blocks—both cars and Lego blocks are very familiar to people! For the second goal, we decided on a large variety of cars. As will be seen from the figures below, there are six basic configurations of cars based on size (narrow/wide, regular/long, and so on), and in addition, each can be ordered with special options, including more features on the body and a spoiler in the rear. Altogether, this results in around 10 different cars that could be ordered. Figure F.1 shows examples of a standard and a special car.

image figf_1a.jpg
image figf_1b.jpg

Figure F.1Standard car with wide body (left) and a special car with a higher body and a spoiler (right).

The simulated car factory consists of seven assembly cells and one shipping cell (Figure F.2). There are two cells for assembling the base of the car, depending on the size. Here the participants put together the chassis and the axles. Next are three cells for the body assembly, again with different operations based on the car type. For example, bodies have to be made bigger with more Lego bricks, or spoilers have to be installed for the specials, and all body stations also have to mount the wheels. The third set of assembly cells attach the nose to the car. Finally, the cars are sent to the shipping area where they are staged for shipping on trucks. Since this is just a staging area, it is not included in the POLCA loops as no capacity signals are needed (see Chapter 5 for a discussion on this point). On the shipping date for any order, that car is removed from the staging area and put in another area, which represents that it has been shipped out on a truck.

image figf_2.jpg

Figure F.2Layout of the simulated factory.

As seen from Figure F.2, products have several possible routings. In particular, a given cell could have more than one upstream cell and more than one downstream cell. In addition, the assembly times vary significantly: some of the special options can take twice as long to assemble compared with a standard option at the same station. So, the variation in products, routings, and assembly times, combined with the demand variations (below), provide the high variability needed to demonstrate the strengths of the POLCA system.

We normally play the game with eight participants—one working at each cell—and one observer. The role of the observer is to watch over the whole operation, make notes about any remarkable situations, and also to observe and calculate the metrics described below.

The game is played in two rounds, and each round is for a month’s worth of orders. These orders have been prepared by us ahead of time to help illustrate the main dynamics of the game. In the first round, we use the Kanban system and in the second round we use POLCA. To make the game realistic with pressure on people to get products out in time, we have a Powerpoint animation in which people see the date, hear the start of the day by the sound of a rooster, and then they hear music, during which everyone is allowed to assemble. Just like in musical chairs, when the music stops they have to stop too! For each round, we record some key metrics, specifically the delivery performance, WIP, and finished goods (the amount of products in the staging area). In order to get multiple samples of the metrics, we have several “counting moments” during the game. At such moments, we stop and “freeze” the game, and record all the key metrics.

For the first round with the Kanban system we start with some initial products at each workstation. This is necessary because Kanban is a replenishment system (see Chapter 3 and Appendix C for more details). There are no Authorization Lists—cells make a new product if they receive a Kanban card from a downstream cell. The whole process starts with shipping as the first trigger. In the case of Kanban, there is a Kanban loop from shipping to the preceding cells. Every time a product is shipped, it generates a signal for the upstream cell, which then creates a signal for its upstream cell, and so on.

In the second round, we play the game with the POLCA system managing the production, so we have POLCA cards and Authorization Lists. Based on the possible routings between the cells, Figure F.3 shows that there are nine POLCA loops along with the corresponding two-colored cards. (Earlier we explained why there are no loops to Shipping.) The Authorization List for each cell is made in the usual way, by back-scheduling from the shipping dates (see Chapter 4), allowing for a one-day lead time at each cell. Also, in the POLCA situation we start with no initial WIP at all, as everything will be made based on the Decision Time rules.

image figf_3.jpg

Figure F.3Set of nine POLCA loops for the simulated factory along with color-coded cards for each loop.

Typical Outcomes from Playing the Game

In Figure F.4 we show the actual outcomes of one of our games, which is representative of the results that we have seen. Let’s start with the outcomes for the game using the Kanban system, on the top half of the figure. In the first column, you see the products (we have aggregated the car options into four main categories for the purposes of data-gathering). The next set of columns, under the general heading of “WIP,” show the WIP and finished goods (FG) numbers for three counting moments along with their totals. The last column shows the average of these totals (the shaded cells). The next set of data, below the above numbers, shows the delivery performance. Again, we have the data for the three counting moments—note that for the on-time delivery data this is the cumulative performance up to this moment—and then we have the cumulative performance at the end of the simulation (shaded cell).

image figf_4.jpg

Figure F.4Example of actual outcomes from a simulation game.

The lower half of the figure shows the same data for the game when the POLCA system is used. The results of these two phases are representative of what we see in our games, and summarized as follows:

Results with Kanban

Results with POLCA

Average WIP:

17

Average WIP:

12

Average Finished Goods:

4

Average Finished goods:

0

Delivery performance:

85%

Delivery performance:

98%

In general, what the participants see through experiencing our games is that in this high-variability situation, as compared with using Kanban, with POLCA the WIP is reduced, finished goods are unnecessary and reduced to zero, and the delivery performance improves to an almost-perfect number. The results are always almost the same every time we play this game: all the metrics in the second round with POLCA are much better than in the first round with Kanban.

An interesting side result is that people realize that the POLCA system reduces the stress during the game. If you are behind at a certain moment, the combination of the Authorization Dates and POLCA cards helps to resolve the backlog. So, people calm down and are more relaxed in their activities.

Results of the Game

The participants in our games have included a mix of people from all levels of the organization, including machine operators, supervisors, planners, managers, and even directors of companies. We have found that the strength of our simulation game is that POLCA can be taught to all levels of a company and that experiencing the operation of POLCA during the game is critical to understanding of POLCA.

To make the game more fun and give it a competitive character, we often play the game with two groups simultaneously. This makes each group alert right from the beginning, and of course they want to see if they can achieve better results. This provides a healthy stress level and makes the game more like real life. At the same time the game clearly demonstrates the limitations and benefits of each of the systems, since each team is trying to do its best, but must operate within the parameters of each system.

We have also found that the POLCA simulation game acts as a springboard for discussion of the prerequisites for successful POLCA implementation. After the game, discussions naturally focus on the importance of actions such as planning for spare capacity, creating the Authorization Lists, and minimizing component shortages, before moving ahead with the POLCA implementation. The feedback from our participants is always very positive and acknowledges that the game helped them to really understand how POLCA works and its benefits.

About the Author

Hans Gerrese is a senior consultant with 17 years of experience in implementing Lean and QRM in a wide variety of manufacturing companies. After completing his study at the automotive university, he started working at several first- and second-tier manufacturers in the automotive world. There, he came in contact with Lean and after a while decided to start his own consultancy firm in Lean manufacturing. After almost seven years, he came in contact with QRM and was one of the first people in Europe to implement QRM at his customers’ locations. More recently, his implementation work has been supplemented with training activities at an institute at which people are certified to three levels of QRM expertise.

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