The APICS Dictionary, 15th Edition, defines the bullwhip effect as
“An extreme change in the supply position upstream in a supply chain generated by a small change in demand downstream in the supply chain. Inventory can quickly move from being back ordered to being excess. This is caused by the serial nature of communicating orders up the chain with the inherent transportation delays of moving product down the chain. The bullwhip effect can be eliminated by synchronizing the supply chain.”
One way of synchronizing a supply chain can be VMI, other collaborative models work equally well as well. The key is to make the supply chain as transparent, across multiple levels, as possible. And keep the cooperation running during daily operations. The last bit is most likely the most challenging one for supply chains out there right now.
The Beer Game
Definitions are fine, definitions with examples are better. And the best way to illustrate the bullwhip effect is the “Beer Game”. This simple game simulates are four to five stage supply chain for one product. There are no bills of materials, lead times between stages is always one period. This supply chain is as simple as it gets. And it is the most impressive way to show what the bullwhip effect is, how it happens and how it can be mitigated.
When I run this game at training events, I use two rounds. Each round is played for somewhere between 15 and 20 periods, depending on time. Also, every team has the same conditions, primary demand, me as the trainer serves as the end-customer, is the same for everyone. As are the starting conditions. Results, so, are tremendously different between teams. Before come to that, how is the game played? And what lessons can be learned from it?
The first round is designed to represent a supply chain without any collaborative models in place. The only information to be exchanged are:
- Ordered quantity
- Delivered quantity
- Order period
- Delivery period, always order period +1
No exchange of information is allowed besides that. All teams have the goal to minimize costs, inventory costs money, missed deliveries cost more. I don’t fluctuate primary demand by more than 10%, over all played periods I stay around 5% fluctuation based on average demand over the last three periods. If it would be a forecast, we would all be happy, wouldn’t we?
In absolute numbers, the game started with a primary demand of 5, I never went above 7 and averaged out between 5 and 6 after roughly 10 periods. Based on these numbers, our little four stage supply chain should run rather smoothly, shouldn’t it?
You might have guessed already, it didn’t. I saw everything, from order sizes up to 100 (!) units, even higher inventory levels and backlogs up to 120 (!) units after only 20 periods. And I am still waiting for a team that manages to stabilize during round one. All also wait for a team that has less than 4 periods of short deliveries, most teams do run completely dry once.
The background of teams had nor real impact. I had teams completely made p of seasoned supply chain people, teams with no supply chain background whatsoever and everything in between. If there was a difference in the first round, it was that supply chain people sometimes tended to stock up more. We all got burned in our lives by stock outs, I assume.
The question every participant of these sessions asked is “Why does this happen?”. So, why does it?
Reasons for the Bullwhip Effect
Usually, the game runs well and smooth. Until the first time one of my orders cannot be fulfilled completely. From that point onwards, the supply chain cannot be saved anymore. Regardless of group, things started to spiral out of control. Sometimes faster, sometimes it took a while. Ultimately, things ended up the same. High backorders, huge inventories, out-of-proportion order sizes and exploding costs. Not mention non existing customer satisfaction.
But why does a simple stock out situation result in this? Lack of communication and human behavior. Let’s have a look at these two reasons separately.
The whole point of the game is to put the participants under pressure. And as soon as the first problems arise, people want to get rid of that pressure. So they over compensate, order sizes increase more than what would be needed to fulfill the backlog, buffer stocks are built up, just in case. And this effect happens at every step of the supply chain. We have all seen this happen in real life. Either during shopping, the days before holidays are a very good example. Or in our professional lives, every time we wondered why customers ordered strange volumes, this effect was probably the reason.
Lack of Communication
The main constraint of the game is communication. Participants are not allowed to communicate with each other, or exchange any information, other than exchanging orders on forms. These forms include the ordered quantity, the order period and the quantity delivered in period +1. That’s it, no details on inventories, backlogs, no forecast or anything else. The result is a complete lack of transparency of what’s going on. Sounds familiar, doesn’t it?
The fun part of the game are the comments, so. After the first couple of rounds, every time someone burst out with “How much?!?!? But WHY?”, laughter is guaranteed. And this happens at least once during the order cycle. Did I mention that I can be a mean trainer during round one?
The Beer Game is played twice, each time for around 15 to 20 periods. The first session plays out as described above. The second one removes all limitation regarding communication. And this last bit is the solution. As soon as my orders are exchanged, stock and backlog numbers shared, participants come up with all kind of plans. Ideas ranged from pre-defined order sizes to forecasts to simply shouting out my order sizes across the table. And they all work.
In real life, these solution have names like Kanban, Just-in-Time, VMI and forecasting.
I have played this game with people new to supply chain management and seasoned professionals. I had mixed groups. When putting teams together, out of simple curiosity I put together teams of seasoned Supply Chain people, people with no SCM background an mixed teams. I had the seasoned people at every level of the four-level supply chain. Guess what? It didn’t make a difference in the first round. In the second round, teams with SCM experienced team members usually fared better. In the first round, without any information and transparency, all the knowledge and experience didn’t help.
It didn’t even help when you knew the game and the rules. I learned that every time I was a participant and not the trainer. I knew the starting situation, I knew the rules. I had the background and real life experience. It didn’t matter in the first round.
What does this tell us? That communication and transparency are the key. As soon as information is flowing freely between parties, plans can be formulated. People stop optimizing for themselves, instead the end customer becomes the focus. Collaboration, so, works best when the team has one part who takes the lead. But even without a leading party, also called the Channel Master, results improve by orders of magnitude.
Real supply chains are much more complex, manufacturing companies already have more than four manufacturing levels in-house. There are more suppliers, more parts involved. Lead-times vary an can be way longer than one order and delivery cycle. And still, collaboration models work. They reduce inventories and costs. And they improve supply chain performance.
If you are interested in VMI in general, you can read the posts here:
And if you are interested in the Beer Game, just reach out to me! Be safe, take care and remember that COVID-19 affects us all