Tag: proliferation
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What does the stairway to complexity tell us?
If a product is too complex, where is the complexity coming from? Which features are causing the explosion in the number of build combinations? The stairway to complexity tells us where to look.
The stairway to complexity shows how the number of unique configurations drops as features are removed. Here is another stairway for a backhoe with 30 features.
The number of build combinations drops from 934 down to 1 as we remove the features. Behind the graph is the actual list of features in the order they were removed. In the table below, the features are ranked from 1 to 30, corresponding to the steps in the graph.
If we want to simplify our product, this ranking of the features tells us where to start. The greatest contributor to complexity is the Buckets, of which there are 34 different kinds. The number of build combinations would drop from 934 to 838 if we didn’t have to worry about Buckets.
Is the ordering of the features in the stairway the same as the ordering by number of options? The first feature in the stairway is certainly the one with the most options (34). But Tran_Control has the second largest number of options (9), and doesn’t appear in the stairway until step 15. So there is more going on than just the number of options.
The amount of complexity introduced by a feature depends not just on the number of options, but on the relative popularity of the different options. Having two options that are split 50% to 50% is much worse than if they are split 90% to 10%. (See earlier post: Entropy of a coin toss.)
Introducing a new feature only increases product complexity if it splits existing configurations that would otherwise be the same. One manufacturer insisted that his product was so complex because it was produced for many different countries. But the number of unique build combinations was exactly the same whether the Country feature was included or not.
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The quality connection
Recently I wrote about quality rankings for automotive manufacturers and the perception of these rankings in the market. While the marketing teams at these companies must shoulder the burden to convince consumers about their products’ quality, there is a very real connection between product quality and configuration management.
In many industries where products have grown over time with constant additions of new features and flexibility to allow customers to build to order, the level of complexity is staggering. Often the number of configurations sold on an annual basis is surprisingly close to the total units sold for that same period. This “snowflake” situation is one of the worst possible scenarios in product complexity as each unit has its own signature. Obviously, the production of these products also requires flexibility in manufacturing. This may result in reduced use of automation, and often it leads to units being reconfigured where components installed during one step are either removed or modified in a later step due to a unique situation.
These one-off manufacturing processes open the door for product quality issues due to fewer controls during production. Put simply, if I can reduce the number of different things that must be done during production I should be able to do those things better.
So product management teams have direct input on product quality via product complexity. Managing the product option mix to reduce the overall number of configurations can promote the increased quality that all manufacturers are looking for.
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How many choice combinations does your product have? That depends.
Possible combinations
This is a question with several answers. The easiest answer is the least useful. The number of possible build combinations, or unique configurations, is easily computed by multiplying the number of options for each feature. For example, if your product has feature A with 3 options, feature B with 2 options and feature C with 4 options, then there are 24 (3 x 2 x 4) possible build combinations.
These numbers grow very rapidly. If you have 5 features, each with 4 options, there are about 1,000 build combinations (exactly 1,024). With 10 such features, the number of combinations is about 1 million (1,048,576), and with 15 features it is over 1 billion (1,073,741,824).
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When the tide goes out, it exposes products that were under water
The number of companies with complexity reduction initiatives has skyrocketed. Unlike five years ago, these are serious initiatives with management sponsorship and timelines.
A good friend of mine, who is a salesperson at a Caterpillar dealership, told me that when times are good he can sell any machine. When the times are bad, the bad stuff just sits around exposed.
Companies have proliferated their product offerings – there are almost infinite variations of everything that they offer. The rationale is that they will make one more sale because of that variation. But as product variations grow, the cost structure grows very fast as well, and the probability of finding that one customer who wants the new variation is quite slim. This results in excess inventory across the supply chain. And when the economic tide goes out, it exposes the cost of those product variations.
The companies with complexity reduction initiatives recognize that during good times and bad, managing product variants makes good business sense. Companies are now starting to implement metrics to measure product complexity because we all know that what gets measured gets managed! Product complexity metrics quickly expose underwater products.
The comment by my friend at Caterpillar reminded me of a trip I took to the Bay of Fundy. It is amazing how much is exposed when the tide really goes out, just like in this economy. The good news is that when the tide turns, the bad product lines it once covered will be significantly fewer, resulting in healthier and more competitive companies.
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Optimization is the big win – but getting started is key
When I started studying complexity and realized the huge adverse impact it was having on companies, I was determined to “find it and get rid of it.” There are many places where that formula will lead to big improvements in everything – profits, service, quality and more. More and more companies are discovering how to do this. In some cases it is pretty simple. Just having the courage of their convictions that it will make things better is all that stands in the way of eliminating complexity.
Well, I found that is not completely true – at least not all the time. There are some situations where what seems to be a simple complexity elimination process turns out to be quite a bit more… complex! The real issue is not just complexity reduction. It is “optimization” of complexity. Get rid of the wasteful part and structure processes to use the right level of complexity.
The Root Cause of Product Complexity!
Emcien defines product complexity as simply the ability to predict what the next order coming into the company will be.
Think about it: If you only made product configuration A, you have 100% confidence in knowing that the next order in the door will be configuration A (assuming you get an order in the door at all, not a total given in this economy). But if you have configurations A and B, it’s harder to know and with A, B and C, it’s even harder, and so on. When you have thousands of configurations, predicting the next one is very difficult.
It’s not just the number of configurations that’s important but also how they’re distributed. If I have 10 configurations but 90% of my orders are for config A, then it’s still safe to predict that the next order is config A. But having 10 configs that have each been ordered 10% of the time is extremely complex!
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