The textile and clothing industry is currently facing many challenges. In 2016 and 2017, seven traditional German companies went bankrupt, including Basler, Wöhrl and Biba. Gerry Weber also filed for bankruptcy at the beginning of 2018, a fashion label that has been a staple of the German fashion industry for generations.
While these companies have been struggling with the costly expansion of their distribution network, sales in the textile industry shifted increasingly in the direction of online sales. Successful apparel companies including Puma, Adidas and Zalando, the last of which sells exclusively online, invested in a successful multi-channel strategy as well as an individualized customer approach to consistently improve and transform.
In 2019, successful marketing strategies and sales concepts are setting new business processes and models, and more efficient control and monitoring of the supply chain has become essential to reducing costs, optimizing processes and staying competitive via Process Mining technology.
Purchasing in clothing companies is gaining strategic importance. Working closely with Design, Product Development, Merchandise Management and Controlling, the value chain is increasingly proving to be a key interface in streamlining and coordinating the supply chain.
Because of this trend in retail, it is crucial in 2019 to reduce the complexity of the purchasing processes, and to achieve greater transparency and consistent understanding of the ongoing processes. Although most of the operational purchasing activities are already digital and automated, procurement processes go through a large number of areas of responsibility and IT systems.
According to a recent study by McKinsey, a system landscape that completely covers the process in all its facets is seen as a major driver of hope in purchasing. This type of system makes it possible to further advance the digitization of process management in the supply chain, and to minimize the complexity of the processes.
Process mining technology enables a cross-system evaluation of data in real time as well as the visualization of process chains. Information from IT systems such as product lifecycle management (PLM), supply chain management (SCM) and enterprise resource planning (ERP) are brought together to optimize the purchasing process in its entirety, and ultimately provide world-class customer service to fashion shoppers.
According to garment experts and the process mining community, it is possible for pioneer Process Mining companies like Celonis to identify promising application potential for the technology in the fashion industry specifically, as its features help overcome challenges that all apparel companies universally face.
Respondents identified data collection as the biggest challenge in using data-driven process analysis in apparel companies. Small and medium-sized clothing companies, in particular, rarely have standardized or historically-grown systems, which means that the expense of data modeling is much higher. In addition, e-mail and Excel are still frequently used in the processing of purchasing processes in clothing companies, which counteracts the end-to-end digitization of process management.
Process Mining brings about a completely new cross-system transparency that helps identify potential for automation, and further advance operational purchasing. Automation rates and manual changes in the system can be determined using recorded event logs already in their systems. Thus, according to the interview participants, processes are not only accelerated, but also more reliable in their execution.
While small and medium-sized apparel companies are actively promoting the expansion of their IT systems along the supply chain, large companies are already looking a step further in streamlining their purchasing processes. In addition to ERP systems, the experts reported on the successful use of supply chain management tools to obtain transactional data of suppliers between goods issue and goods receipt.
Monitoring purchasing processes along the supply chain is a beneficial investment for these companies who—until now—experience time delays or other deviations in the purchasing processes. These processes were usually not recognized in time, which is why decisions are often described as “intuitive” and “emotionally driven” in the fashion industry. Process mining technology provides a needed objective, fact-based basis for the buyer to react earlier—and more rationally—to changes in the supply chain.
In recent interviews conducted by Celonis, fashion industry experts reported having a constant demand for detailed comparisons of product groups, suppliers or seasonal collections in order to obtain a better overview of the development of stocks, returns and replenishments. In contrast to other sectors, the apparel industry does not order, but predicts sales volumes—especially for fashion and luxury goods.
Due to the granularity of the product types as well as the different planning cycles and sourcing strategies, it is often difficult to understand the complexity of procurement planning, which also extends over several areas of responsibility. Thus, process mining could take on the integral role of looking at shopping processes from a bird's-eye view, and identifying possible inefficiencies throughout each stage in a process flow.
According to the interviewees, a sustainably-improved supply chain development would result from the fact that inefficiencies are not only recognized, but that improvement measures can also be continuously measured. The measurement of process key figures in this way has so far been described as missing. With process mining, the monitoring of process indicators can be easily integrated and tracked in a timely manner.
Process mining has the potential to make revolutionary contributions to the future of consumer shopping and operational fluidity in the fashion industry. This AI-powered technology succeeds in providing a complete process perspective on the otherwise fragmented value chain. On the one hand, process mining overcomes the limitations of Business Intelligence (BI), and on the other, the subjectivity of traditional process analysis. With process mining already proven in many other industries, the use of technology in the fashion apparel industry could help to strengthen a market sector that is grappling with digital transformation on many fronts.
Maria holds a master’s degree in textile chain research, focusing on IT innovation in the textile and clothing industry. After successfully completing her bachelor thesis in the context of the course International Fashion Retail at Celonis Partner INFOMOTION on Process Mining, she will continue on the process mining team as a working student.
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