Turning data into a strategic asset is a top priority for many companies across industries. Data (in the form of digitization, analytics, and automation) is especially important to businesses in the mass customization space. Stan Davis, in his 1987 strategy manifesto, “Future Perfect,” coined the term mass customization to describe “generating an infinite variety of goods and services uniquely tailored to customers.” In the consumer space, this could be a product like a photo-book filled with family pictures, or a customized calendar marked with birthdays. For businesses, it might be a banner for a grand opening, or a piece of apparel embroidered with a corporate logo.
Mass Customization: Breaking the Curve
In traditional markets for customized products, each individual production lot entails significant fixed costs. Extensive time and energy are spent specifying and communicating the many minute details required to accurately create the product, negotiations on price and delivery terms are made on a one-by-one basis, machines are set up to produce the items, and the transportation required to deliver it is contracted on an individual basis.
Unless these high set-up costs can be amortized over a long production run, each unit will be very expensive. There is a seemingly iron-clad curve of cost and volume, anchored on one side by mass-production (standardized, high volume, low cost per unit) and on the other by custom manufacturing (bespoke, low volume, high cost per unit).
Mass customization seeks to “break the curve” and produce goods and services that meet individual customers’ needs with efficiency similar to mass production. It does this by systematically sorting high volumes of small orders into homogeneous streams that can be fulfilled in a cost effective way by specialized manufacturing lines.
This enables lower costs, faster speed, more personal relevance, eliminates waste created by high minimum order quantities, and provides more product choice. Recognizing the patterns (what orders should be grouped together) is what enables a successful mass customization business to produce many unique orders in a cost-efficient way.
Data and Mass Customization
Automating manufacturing and logistics is critical to achieve the efficiency of mass customization. All of the essential details of production (e.g. products, customizations, delivery options, suppliers, etc.) that were previously negotiated order-by-order need standardized, structured digital representations and all that data needs to be governed, managed and shared across a network of numerous independent fulfillers.
In order to make production efficient, automation and ML are deployed to optimize decisions about where, when, and on what equipment to produce a product. Streaming analytics can be used to production and provide fast feedback to different actors in the process: for example, between customer care and a production facility.
Data is also an essential element of the product customization process. Creating a product like a promotional brochure requires walking a customer (who may not know much about printing) through a complex set of design decisions. Mass customization businesses often use technology to democratize design and make it as easy as possible to create a customized product that looks great. Machine learning can play an important role here; for example by enhancing customer images with resolutions too low for print, or predicting whether text in a given size and color will be legible on a particular product.
There is a natural tension between the need to systematize and create a design experience that is easy, and the need to give users more control over the product. The same approach that provides welcome reassurance to a customer without any design experience may be too limiting for customers with a more sophisticated knowledge of design. Mass customization businesses need to leverage data to deeply understand their customers in order to accurately predict the degree of customization help that a customer will need and provide it in time. Building this rich customer profile has the added benefit of enabling highly personalized and compelling e-commerce experiences that make transactions smooth for customers.
The mass customization approach is transforming the market for customizable goods by making uniquely-tailored products broadly accessible, with a wide variety of benefits to both producers and consumers.
Data and analytics, automation, and machine learning are essential components of mass customization, and we anticipate that technology advances in these areas will only accelerate this transformation in years to come.
(The author Christopher Bova is Senior Director, Technology at Cimpress and the views expressed in this article are his own)