Wie Modehändler mit Nachfrageprognosen verstärkt auf Nachhaltigkeit setzen können

How demand forecasting can improve sustainability along the value chain in fashion retail

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Before COVID-19 took over the headlines, one of the most prominent topics in the news was Greta Thunberg and her global fight against climate change. While its impact on human lives and the global economy has been dire, in many ways COVID-19 has been a blessing for nature: cancelled flights as international travel is banned, less commutes by car as people are forced to work from home and minimized activity from industrial sites and manufacturing plants have all resulted in a significant reduction of CO2 emissions. But this situation will not last forever, and as people’s lives return to normal and business picks up again, we must not forget that sustainability should be at the top of the agenda.

One sector that has a particularly “bad rep” when it comes to climate change is the fashion industry. Fashion industry expert Eileen Fisher – an American clothing designer and founder of the eponymous women’s clothing brand – even went so far as to claim that “The clothing industry is the second largest polluter in the world … second only to oil.” Whether or not this claim is entirely accurate remains disputed, but with its resource-intensive production processes and extensive global supply chains, fashion retailers certainly contribute significantly to CO2 emissions.

Fashion retailers must act now

They say the first step to implementing change is recognizing that there is a problem. It seems that fashion retailers have made this step. According to The State of Fashion 2020 report, written in partnership by McKinsey and Business of Fashion, a survey of fashion retailers reveals that one of the biggest challenges they face in 2020 is sustainability (granted, this was before the COVID-19 crisis). This stems in large part from shifting consumer preferences. As McKinsey puts it:

“The global fashion industry is extremely energy-consuming, polluting and wasteful. Despite some modest progress, fashion hasn’t yet taken its environmental responsibilities seriously enough. Fashion players need to swap platitudes and promotional noise for meaningful action and regulatory compliance while facing up to consumer demand for transformational change.”

Of course, in the past few years we have seen an increasing number of “sustainable” fashion brands enter the market, as well as major retail chains offering sustainable fashion lines – think H&M’s Conscious – but with sustainable fashion brands only accounting for a marginal percentage of overall fashion consumption, and only a minority of consumers being willing to pay higher prices for sustainable products (31% of Gen-Z and 12% of baby boomers), the question is how can major retail chains effectively improve sustainability across all their product lines?

When the fashion industry talks about sustainability, they often discuss in depth the raw materials being used in manufacturing, the resource-intensive production process, and the working conditions in production facilities. But there is another salient issue that we’d like to focus on: the huge amount of waste that comes from overproduction.

What happens to apparel that is produced but cannot be sold? While some merchandise is moved to off-price outlets, unfortunately a lot is also demolished. In 2017, the British luxury brand Burberry burned goods worth almost 37 million dollars in the name of preserving its brand appeal. Fast fashion giant H&M also reportedly burned 12 tons of brand-new unsold clothing annually between 2013 and 2017. Unsold clothes that aren’t burned, often end up in landfills where they take decades to degrade.

 

Demand forecasting to the rescue

H&M has come a long way since reports of the company burning unsold clothes made headlines. At the National Retail Federation’s Big Show in New York City in January 2020, Arti Zeighami, Head of Advanced Analytics and AI at H&M, took the stage to openly discuss the issue of sustainability in the fashion industry.

You may be wondering why someone with the job title “Head of Advanced Analytics and AI” would be invited to speak about sustainability. But according to Zeighami, the key to making supply chains more sustainable – in fashion and elsewhere – is artificial intelligence and predictive technology. Put simply, it’s all about “aligning demand and supply.” To align the two, accurate demand forecasts are needed.

Demand forecasting is the process of predicting future sales by using historical sales data. Machine learning algorithms use demand forecasting to make informed business decisions. As we will describe below, demand forecasting and AI technologies have the power to increase sustainability from production all the way to the point of sale.

  1. Production: By producing only what can be sold, retailers reduce the amount of raw materials and resources that go into production. This has the power to be hugely impactful, as the fashion industry produces 20% of the world’s water waste – a result of the manufacturing and crop growing process. Not to mention the toxic chemicals that are released in the production process.
  1. Distribution: Once the merchandise is produced – which typically takes place in developing countries – it must be distributed to stores and warehouses across the globe. The challenge is offering merchandise exactly when and where consumers are demanding it, i.e. having the right product in the right place at the right time. Precise demand forecasts and AI-based solutions can enable efficient warehouse planning and ensure that the most efficient transport routes between factories, warehouses and stores are taken – saving CO2 emissions in the process. Moreover, accurate anticipation of customer demand can minimize unnecessary stock transfers between stores. With the fashion industry emitting 10% of the world’s greenhouse gases, this too would have a huge impact on the industry’s carbon footprint.
  1. Sales: Once merchandise hits the sales floor it must be closely monitored. Is it selling off like hot cakes? Or is it sitting idle, taking up valuable shelf space? Are there unexpected changes in demand between store locations or sales channels? By relying on demand forecasts that are updated in real-time, retailers can swiftly and efficiently adjust to short-term shifts in demand by flexibly adjusting prices. For instance, offering a markdown at the right time in line with customer’s price acceptance can provide the boost in demand that is necessary to sell of slow-moving goods. Thus, intelligent price optimization ensures that retailers can clear out inventory by the end of its lifecycle, thereby minimizing waste.

Supply Chain Dive sums it up well, “With precisely honed demand forecasts, supply chains can use only the resources they need and no more. Without precise demand planning, the result is waste — a historical problem for the fashion industry.”

As stated, it’s all about aligning supply and demand. This means relying on accurate forecasts of consumer demand to efficiently allocate, replenish and transfer inventory as well as to optimize pricing throughout the season.

Demand forecasting is no easy feat, but it’s necessary to succeed in today’s complex retail world. Fashion retailers looking for predictive analytics capabilities need look no further: aifora is the leading provider of AI solutions for pricing and inventory management for fashion retailers.

Of course, even the best demand forecasting solution won’t get it perfectly right 100% of the time. But AI will get it right a lot more often than any human ever could. And when an unforeseeable event strikes, predictive analytics will help you get back on your feet faster.

Lastly, let’s not forget that the benefits of AI-driven pricing and inventory management go far beyond the positive environmental impact. Aifora’s solutions have provided leading European fashion retailers with 3-6 % increase in sales and a 2-8 % increase in profits. So, if not just for the environment, then do it for your bottom line.

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