Smart Incentives for Sustainable Sell-Through
Despina Borelidis
January 12, 2023
Full warehouses, full shelves, a top selection and a well-planned sell-through. Is that even possible? Entire industries have overproduced, and are still doing so. In the food industry – primarily in the baking trade – literally tons are produced for the trash. The fast fashion industry operates in a similar way.
Which business models lead out of misplanning? How can returns management be optimized? And what do companies need to keep in mind when using smart forecasts and merchandise management systems? A conversation with Dr. Tim Bauer, Director at enomyc.
The observation is right, both exist. Industries whose warehouses are currently full had to wait a long time for goods because of disrupted supply chains. But now the orders have been worked off, and the wave of goods is arriving. Everything is available again. It's just that nobody wants to buy it at the moment. That is why some warehouses are filled to the brim.
I observe it primarily in the food and fashion industries. This also strongly affects returns management. But let's start with the fashion industry, where the business model is in part designed around waste: products are made and priced in a way that deliberately implies: this garment will be worn only a little and then returned. In the worst case, it is even thrown away. Business models like this encourage wasteful behavior among consumers. They buy vast quantities of products they don't actually need.
This has fatal consequences: In 2020 alone, Europeans consumed an average of 15 kilograms of textiles per capita. That was reported by the EEA. At the same time, we threw 4.6 kg of textiles per person into the trash here in Germany.
And it is precisely against this background that business models of this kind must be rethought or evaluated. Because if you look at the entire raw material cycle, fast fashion satisfies the need for short-term available, inexpensive fashion until something else is en vogue. The strong trend toward e-commerce has intensified this development even further.
Right. In the fashion industry, it is common to work with 50 to 60 percent returns. So the waste also takes place in logistics here. Products are delivered and sent back – the business model already provides for that. Companies like Amazon and Zalando have strongly driven this uncomplicated, risk-free way of shopping and greatly intensified competition. In addition to the logistical waste, the question also arose of how returns are handled. There were, in some cases, major scandals in which returned goods were destroyed directly. For retailers, that was cheaper than offering B-grade goods. For this step to be worthwhile, however, articles must also have a certain value creation. After all, returns management requires investment.
Yes, in the current situation, efforts are already being made to optimize the return rate of 50 to 60 percent that is considered normal. Some online retailers are trying to educate their customers in this respect. For example, by offering only prepayment as a payment method. Or by passing the cost of returns on to them. In addition, for some time now – and in view of the possibilities offered by artificial intelligence, virtual reality and the metaverse – there have been entirely different solutions as well. For example, shop applications that provide exact determination of body measurements via 3D measurement. That way, consumers can choose the right garment for themselves from the outset. This would avoid them ordering several sizes, finding the right one only at the fitting at home, and returning the rest.
In terms of company areas, I clearly see sales and production as the primary decision-makers – each area on its own, but especially the interplay of both. On the one hand, the output is reported by sales to production. Sales defines which quantities are produced. In production itself, however, what matters is the way things are produced – that is, the production methods. If changed production methods are adopted, fewer resources can accordingly be used for the same output.
Take the use of energy: Can techniques such as heat recovery, for example, save energy? With regard to raw materials: Can the quantities used be evaluated? How could offcuts be avoided, for example? Plannability and timing also influence production methods, because sales often reports demand at relatively short notice. Production, by contrast, needs lead time. How can we act smarter here? Can relevant data and the subsequent analysis provide a basis for useful evaluations? There are very many good methods that are already being applied. Perhaps forecasts would be the right instrument?
Yes, there are promising business models – even in the food segment, where sales are known to be harder to plan. In certain niches, subscription models work well. I am thinking of concepts like the “Biokiste” (organic produce box). In larger supermarkets, the pre-order business model is suitable. It is well received when providers also offer their customers special added value at the same time. Suppose there are special discounts for pre-orders. The ordering process would be streamlined technologically, and the time saved would be immense. Customers would order goods via an app, be able to redeem their discounts, pay online and pick up the ready-packed order directly. Both models – subscription and pre-order – are part of sales optimization.
Ideally, products remain in the market permanently. The keyword here is repairability. It is how resource conservation is achieved. The European Commission has made a legislative proposal on this: under it, companies are to be required, from 2023, to provide repair options and standardized spare parts. The overarching goal is to curb waste and refuse – electronic waste, for example – and to make alternatives to buying new transparent. The proposal is largely accepted by the population, even explicitly wanted.
Exactly, then it would be possible to repair products relatively simply, or even to exchange them in modules. They would stay in circulation longer, longer in the market. An example from the high-tech sector: How could batteries for electric cars be designed so that they could later be reused in home technology? Or take the food industry, more precisely the baking trade: How could a scarce resource like fresh flour be replaced by old bread? So that a resource-conserving circular mindset emerges, returns are reused – and even an increase in quality can be achieved? Because old bread has the property of making bread more aromatic, juicier and longer-lasting fresh.
The truth is: for many companies this extra effort doesn't pay off in the end – or rather, doesn't pay off yet. And experience shows that many give up right away. But I am convinced that these new – or rather proven – approaches will gain a foothold. In the short to medium term, they will even represent competition in the market. That will certainly be interesting.
At the point when it suddenly becomes worthwhile again to make this extra effort. Because certain methods that were discarded in the past will pay off again. The fact is: the bulk of the market has so far been built on a certain short product lifespan. This stems, among other things, from the fact that there were always sufficient resources. But now we are dealing with resource scarcity. There is no longer reliable availability. Markets will have to learn to deal with their output, which is wanted that way by sales, and also with their way of producing. It becomes particularly interesting when rethinking becomes a cost advantage – even more: a competitive advantage that secures the company's survival. The earlier companies implement measures, the better. Not only when they are forced to.
To make good forecasts, looking at the past is essential. The basis for this is a well-set-up digital merchandise management system. On this basis, tools can be connected that take into account a large amount of data that enables a meaningful forecast. This includes seasonal particularities – such as a Christmas market near the supermarket – but also temporary events, for example a disruption in infrastructure, a construction site nearby or the like. In addition, the higher the turnover of products, the better the replenishment planning. That is admittedly laborious and complex – think of different variants of a product that sell differently and must therefore also be entered into the system that way. But it simply delivers more precisely fitting results. And these in turn form the basis for being able to act better in the future.
I observe that merchandise management systems in companies are often not fully implemented. The consequence is a lack of transparency: sales often does not know which intermediate products are in stock. Sell-through fails, which inevitably leads to spoilage and waste. For companies to use merchandise management systems smartly, first of all the data must be clean. It must be captured correctly and assessed accordingly. On that basis, meaningful forecasts can be created. Sounds logical, but is often neglected. It is this interface that makes it possible to derive suggestions for future action from empirical values, that is, data from the past.
For smaller specialized niche providers, the formula already works. They have high authentic potential and can score with the argument of a scarce good produced in limited quantities. For large mass-market providers, in my view it will only work when the entire market moves. But companies can already shape this development – and with it consumer behavior – positively now. How? By creating the incentives mentioned and tangible added value for their customers. In the end, that also shapes their own image as modern, responsible and forward-looking companies.
