Tag: product mix
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Variation is valuable
Advances in interconnection technologies are driving an increasingly demand-driven market. Customers are learning to expect to get what they want, when they want it, how they want it. And they tell you in each and every interaction they have with your company, or not. In a demand-driven world, increasing product variation and complexity in your business model is inevitable. Left untended, your business can become a tangled web of counterproductive business strategies with a dense portfolio of product families comprising thousands, even millions, of variants.
However, make no mistake, variation is valuable. To deny complexity or view the long tail of product variation as a management failure is to deny diversity of the world in which we make our living. Eliminate complexity in your product offer and you will find yourself competing with boatloads of product from China, India or any of a number of low-wage production markets.
The “keep it simple” principle is the root of good management. However, as Oliver Wendell Holmes, Jr. has observed, “I would not give a fig for the simplicity this side of complexity, but I would give my life for the simplicity on the other side of complexity,” it matters which form of simplicity you choose. The wrong simple answer is to try to focus on the 20% of product variants that make up 80% of your revenue, the head of the ubiquitous Pareto distribution, and find ways to minimize or eliminate the so-called unprofitable remaining 80% of product variants that lurk in the tail. Hello commodity, goodbye margins. The right simple answer is to deliver Intelligent Variation based on the voice of the customer shouting through the many interactions they have with you each and every day.
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Extending the product configuration to gain insight
One of the most important components in choice complexity is the product configuration itself, the mixture of product options that give a product its unique signature. Obviously the typical product orderable options are needed to analyze the complexity of a product, but other more abstract options can offer surprising insights into product and customer behaviors.
A typical car configuration has options such as sedan, V6 engine, automatic, blue, cloth, AM/FM/CD, sunroof. But more abstract items can be recorded along with these to offer more insight. Sales type can be recorded to analyze what types of product configurations sell better in promotional sales events as opposed to normal sales transactions. An attribute to record an extended factory warranty option may provide new ideas for packaging options together with additional warranty services that customers are moving towards.
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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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Product management to fit?
I often hear clients say, “We’ve been told by management that we should only have a standard and premium model.” Then product teams are tasked to fit the line to that limitation, while no product analysis was done to support the decision.
While reduction in configurations is important, how it is achieved is just as important. Using a quantitative approach earlier in this decision-making cycle can help the management team make an informed decision. Maybe a reduction to two models is just too aggressive; adding one additional model might be the difference in having proper market coverage. Examination of customer buying trends and patterns should be the first indicator for product direction. Determining product strategy based on market needs as opposed to retrofitting the product to an idea could lead to more effective product lines for both the manufacturer and consumer.
Stop product complexity at the door
In any manufacturing company that builds configurable products, there is a lot of discussion around what product complexity is. What’s interesting is that when times are good and there are lots of sales, the discussion is usually around how to simplify or streamline with the goal to sell more product even faster, that complexity is keeping sales from going even higher. In bad times, the discussion typically moves to how complexity is causing undue stress on the supply chain, creating problems with parts forecasting, quality and finished goods inventory.
Rarely do these discussions end with participants really agreeing about exactly what complexity is or how to reduce it. Solutions are attempted with internal projects like SKU reduction and part number reduction initiatives driven by Six Sigma teams that mean well and do good work, but usually are chasing the tail of the complexity dog, rather than leashing it for good and guiding it to higher profits, lower forecasting errors, even shorter sales cycles.
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Key Concepts To understanding Product Variety
1. Product
A product is something offered for sale to customers. This is deliberately vague, because we want to encompass services as well as tangible products. Most of our discussion and examples involve manufactured products, but our framework also applies to services with many variants like insurance policies and cell phone calling plans.
2. Instance
An instance of a product is a specific unit of the product: the car that Joe buys, which has a specific VIN (Vehicle Identification Number).
3. Configurable Product
A configurable product is a product where the instances are not all identical. No. 2 pencils are not configurable. Computers, cars, tractors, refrigerators and cell phones are configurable.
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.
Is quality really important?
Seems like it’s almost fashionable to kick the three U.S. automakers these days, and I rarely hear people mention U.S. built as one of their first choices. Yet people almost always cite reliability as one of their most important criteria for buying a vehicle.
The most recent J.D. Power and Associates rankings show that 2 of the top 5 highest-ranked brands for vehicle dependability are from U.S. automakers. Two other U.S. brands had top rankings in other vehicle segments. It seems that many foreign makers have a perception of quality that is based on past success or marketing. Manufacturing of products in the U.S. has seen a steady rise in quality over the past 10-15 years; the perception in the marketplace should keep pace. If nothing else, the data points out that buyers should consider U.S. brands and not jump to conclusions on outdated results.
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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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