When it comes to fashion, consumers can be a fickle lot. That can make things difficult for clothing manufacturers and retailers who are always trying to stay ahead of the latest trends, but still remain profitable.
Now a graduate student in engineering and her professor have developed a model that will help people in that industry – or any industry, for that matter, with a lot of turnover in its product line – figure out how much product variability it can introduce before it becomes a losing proposition.
“Customers like it, but as product variety increases, so do costs,” said Marzieh Mehrjoo, a PhD student in Industrial and Manufacturing Systems Engineering who studies under the tutelage of associate professor Zbigniew Pasek. “But in the fashion industry, variety affects the entire supply chain, from raw materials to the factory, from the designers to distribution centres to retail outlets. So we’ve tried to look at all the processes in between.”
Along with Dr. Pasek, Mehrjoo recently co-authored a paper on the subject of how product variety impacts the supply chain in the “fast fashion” industry, the results of which she presented at the International Academy for Production Engineering conference going on at the university’s Ed Lumley Centre for Engineering Innovation this week. More than 200 engineers and industry representatives from 21 countries are here to attend the conference.
Using computer software called Vensim DSS, the pair ran a simulation using a “system dynamics” methodology, a modelling approach typically used for long term and dynamic management problems. The simulation covered 365 days, and had a set number of units in stock for both the manufacturer and the retailer, in a scenario where the manufacturing capacity was 28,800 units per time period.
By increasing the number of apparel types, the colors and sizes in the model, they were able to show that increasing variety will lead to increase in revenue for the manufacturer up to a certain level, but that the manufacturing costs increase after they reach production capacity, since unsatisfied demand is increasing, which leads to higher backlogged costs.
“It demonstrates that there’s an optimum point to which you can introduce product variability,” explained Pasek, who noted that those operating conditions don’t remain optimal for long due to the volatility of various factors.
The pair was inspired to study the topic by companies like Zara and H&M who have achieved dominant positions in global apparel markets. Zara changes over about three quarters of its product line every three to four weeks, Mehrjoo said.
“We wanted to understand what it takes to make such a business model profitable, as it definitely is vulnerable to higher risks affecting global supply chains,” Pasek said.
The model is generic enough, Mehrjoo said, that industry professionals could plug in specific data from their own supply chains to determine at what point increased product variability becomes a financial burden for them.