In a previous blog post, I talked about why society needs efficient customization.
Now I will describe why the promise of mass customization and configure-to-order has not yet been fulfilled.
The manufacturing industry is dominated by the mass production paradigm. It is based on the engineering of products and production systems that have a high degree of predictability. The interdependencies in the internal processes are highly complicated but can be managed for efficiency.
Mass production is complicated, but most of the real world is complex: the weather is an example of a complex system. Meteorologists understand the interdependencies that shape weather systems very well, but they will still never be able to predict the behavior accurately. What makes systems complex is the uncertainty of their interdependencies. We may know enough about the interdependencies to explain afterward why something happened, but not enough to predict accurately in advance. Small deviations propagate and escalate in ripple effects that have large unforeseen consequences. The only valid model of a complex system is the system itself.
Mass production is efficient, but customization is often more effective. It gets us what we need.
Unfortunately, customization makes the manufacturing business process complex. Even though the products and processes are in principle very similar to mass production, customization introduces uncertainty everywhere. Which customizations are possible? How do we produce them? And what will it cost?
Complex processes cannot be managed. If you try to control the outcome of a complex process, unpredicted consequences follow, which often makes the situation worse. Most people working in complex organizations have experienced this. Luckily the skillful staff in B2B manufacturing companies make workarounds to handle the predictably unpredictable deviations in the process. They make it work. But it is error-prone and inefficient, and no one has the overview to make informed decisions about the product range.
For several decades, B2B manufacturing companies have attempted to systematize the customization process. They design a product which has predefined customizable parameters. Each customer can select a standardized value for each parameter, and millions of combinations are possible, enough to closely match each customer’s specific needs. The selected configuration of parameter values is then made to order. This best practice is called Configure-to-Order, or variations thereof. It can be efficient in principle.
However, the customization parameters have interdependencies. When you change the value of one parameter, others have to change as well. One by one these interdependencies are relatively well understood, but there are many thousands of them, and they interact and influence each other indirectly. It becomes messy and difficult to determine which parameter value combinations are compatible and what the resulting product performance will be.
So, despite being systematic in principle, customization by Configure-to-Order remains complex due to the uncertain interdependencies.
The problem is perceived as an efficiency problem. The CPQ market has been growing since the mid-90s to increase the efficiency of quoting and pricing customizable products. However, the CPQ implementation projects do not address the underlying complexity. The CPQ systems become black boxes full of rule coding errors and ad-hoc limitations, and they require manual workarounds to integrate with other business processes.
In the next blog post, I will discuss how to eliminate the avoidable complexity of customization – how to fulfill the promise of systematic Configure-to-Order.