Manufacturers’ long-time dream—improving interaction with and knowledge of their consumers—is becoming reality, and technology and automation are playing a big role. But to what degree? As markets become fragmented and production becomes
increasingly demand-driven, what are the new skills, tools and technologies needed to compete?
To find answers, we should look to the past. The dominant manufacturing philosophy in recent years has been lean manufacturing—the elimination of waste at all stages of the manufacturing process with the goal of increasing profit.
Anything that is not producing value for the end-customer is considered waste…unnecessary cost. While the lean-manufacturing approach has obvious advantages (decreasing inventories, increasing quality), it can be too inflexible on markets that call for mass-customization.
Mass-customization, naturally, requires more human work, which can be uneconomical. With mass-customization, the planning and adoption of production processes and technologies becomes much harder for humans. But these processes are much easier for computers to organize and schedule, while keeping in consideration all parameters related to mass-customization.
This can shift the traditional manufacturing philosophy—the modern focus might be on what actually needs to be produced, rather than fine-tuning some separate part-production process or machine. Complementing this mindset is the idea that there is a digital
counterpart to the product being designed and manufactured. Not the CAD model of the product design, but the digital information related to each single piece. Each product is connected to data, which can be used for its production, warehousing and delivery, or even to collect feedback about its use. This makes it possible to understand the consumer needs in (near) real-time, instead of reacting to market studies and conducting time-consuming production planning and calibration processes.
The new assets in this new mass-customization arena are data, speed, and the capability to process and apply new knowledge. Computers generate the data, but processing that information into actionable insights requires engineers and factory workers with new skill sets. And speedily implementing this knowledge is critical for success in this era of mass-customization.
