Traditionally, brands have been dependent on Excel sheets for line planning. This method, though once effective, has become increasingly archaic. In today’s rapidly moving world, Excel line planning models can be years out of date with the market, leading to poor planning and line assortments.

Shein, a fast fashion app, uses real-time data and analytics to micro-target its customers’ preferences. By scouring the internet for emerging fashion trends, Shein manufactures small quantities of garments using its vast supplier network. This allows the app to offer thousands of new clothing options every day, reducing overproduction and overstocking, two major issues in the fashion industry. Shein’s innovative strategy shows how on-demand manufacturing can help address fashion’s biggest issues of overproduction and overconsumption.

The problem with these fast fashion brands is that they use all this data to drive production volume, rather than simply driving quality, revenue and engagement. This comes at the expense of our natural environment.

Fashion is the second most polluting industry (after aviation), responsible for about 10% of the world’s pollution and 20% of global water waste. Fast fashion brands rely on short consumption cycles and are disproportionately responsible for this.

Naturally, poor planning leads to overproduction. In any given season, 30% to 40% of clothing is overproduced, meaning these costs need to be factored into prices. Not factoring in changes in consumer preferences and tastes leads to an erosion of brand relevance.

Digital product creation has been a game-changer, drastically reducing the product development lifecycle to as short as a month for some items. The caveat? The need to recalibrate traditional product processes to optimize this acceleration. Some of the world’s leading companies have embraced this shift, reaping immense benefits from such advanced digital integration. Let’s dive into how they managed.