The current market circumstances enable companies to seek to implement innovative solutions to retain their competitive advantage. The retail businesses which sell clothing items and accessories have an extensive assortment of modern technological products to choose from. As research indicates, the fashion industry is experiencing a rise in the number of technological advances which facilitate the internal processes of enterprises (Dubrova, 2021). Such developments force companies to adopt new methods of operating in a rapidly changing environment.
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The fastest-growing sphere of today’s fashion business is e-commerce, since more people every year switch to online shopping from the traditional brick-and-mortar one. Studies demonstrate that more than eighty percent of executives of retail companies say that in 2021, digital presence will be their top priority (Unglesbee, 2021). The main problem of the business in this case study lies in the lack of infrastructure, which could allow the store to effectively sell products online and gather data on the customers’ activity to make informed decisions. As a result, the business requires to identify two technological solutions which would help it gather information on customers’ preferences and distill it into concrete pieces of evidence based on which the managers will be able to build their strategy.
Thus, data is the major factor related to the business’s problem, the one which can positively impact operations and yield better financial and customer-service results. Essentially, the information a company collects about its clients facilitates the decision-making process and provides it with a fuller understanding of the needs of its clientele. Yet, large arrays of data are particularly challenging to interpret without the assistance of technology. Therefore, to resolve the problem of the lack of infrastructure to collect and assess clients’ information, the company needs to integrate business analytics and business intelligence solutions. This technology is crucial for all fashion-industry stakeholders since it grants them the ability to correctly determine trends and use them to their advantage (Keunyoung, 2020). Business analytics and business intelligence solutions are a technology that renders large arrays of data and helps outline certain patterns which can predict trends in the fashion industry.
Intelligent systems are another technology that will be helpful for the business since it provides an opportunity for an improvement in the customer-oriented approach. Intelligent systems employ machine learning algorithms that accumulate data on clients’ preferences and suggest to them the options they are likely to like. By analyzing the information on the previous purchases of an individual customer, intelligent systems can produce recommendations to both the shopper and the managers (Gonzalo et al., 2020). This will contribute to the business’s ability to offer customized fashion solutions to its clients.
The primary objective of the business is to raise the number of sales through the adoption of new technologies. Additionally, innovative solutions have to assist the company in improving the efficiency of the value chain. The implementation of the aforementioned technologies will provide customers with an experience tailored to their needs and will give the store’s managers the capacity to make better decisions based on computer-assisted analytics. Subsequently, these factors will increase the rate of sales for the business.
Technological advances bring not only challenges but also opportunities for companies that they can utilize to enhance their revenues. Technologies possess the potential to advance consumer-brand engagement, which is particularly relevant in the current context when the supply in the fashion industry exceeds the demand (Varley et al., 2019). Proper technology implementation entails positive results for companies, including decreased overheads, improved relations with customers, and a higher level of efficiency and quality. It fosters cooperation among team members when working on projects which require coordination of activities and helps come to a consensus by relying on the evidence generated by technologies such as business analytics.
The business requires technology that can allow it to advance its business operations by “introducing online shopping, managing inventory and shipping, providing order status and processing of online payments, improving collaboration with employees and clients, overseeing customer contacts, delivering reports, and controlling the brick-and-mortar activities such as sales, payments, inventory, and customer contacts.”
Competitors and Technology
Business analytics and business intelligence solutions
Kohl’s designed and implemented its technology from the sphere of business analytics and business intelligence solutions. The retailer integrated custom-built software, which provided managers with an opportunity to view statistics on sales and other key measurements. The system analyzes arrays of data and generates viable recommendations (Milnes, 2018). For instance, it allows managers to see which products sell better than others in the store’s area and which ones are more likely to be purchased by clients in other locations.
Macy’s, another major competitor of the case study’s business, also introduced a technological solution to its operations management. The company created an intelligent system in collaboration with IBM Watson, which utilizes intelligent suggestions and cognitive learning based on algorithms. The program analyzes every customer’s history of browsing Macy’s website and suggests products that are similar to those they are viewing. The retailer provides clients with an option to receive a selection of products based on their particular characteristics, such as price and color (Dubrova, 2021). This is a good example of an intelligent system that has been successfully adopted by a large enterprise.
Both Kohl’s and Macy’s benefit from the aforementioned technologies, and there are even actual results that point to the effectiveness of such solutions. For instance, according to one of Kohl’s store managers, relying on the recommendations provided by the business analytics tool, they found that one of the products was not selling as well as in other locations because it was incorrectly displayed to customers (Milnes, 2018). Even though that Macy’s has not produced any information on the actual impact of its intelligent system, certain outcomes can be assumed. For example, it is possible to say that a personalized approach facilitated and enhanced the online shopping experience for clients enabling them to buy more items.
Business analytics and business intelligence solutions
Technologies have become integral for the success of fashion companies in the current market circumstances when numerous competing enterprises try to sell their products to a limited number of consumers. The fashion industry is constantly changing as different styles emerge, which enables companies to seek ways to enhance the quality of their services to attract new clients. The utilization of business analytics and intelligence solutions can significantly assist the company in question in solving its existing problems and attaining the desired goals. Namely, currently, the business is struggling to establish a proper online presence and align the business processes related to e-commerce with its brick-and-mortar operations. Business analytics solutions can provide the store with an opportunity to gather data on the customers’ both online and offline activity and determine the preferences of the target clientele. It will allow the business to carefully revise its assortment of products and manage its inventory more efficiently by purchasing only relevant products from suppliers. Thus, the business analytics technology meets the following requirements: integrating online shopping, managing inventory and shipping, facilitating collaboration, and reporting. Even though his technology does not offer a business payment processing solution, it can be used for making informed decisions.
The companies which embrace new technologies should not focus strictly on experimenting with innovative solutions which are unavailable to their competitors. Instead, research has to be conducted to analyze the existing technologies which are guaranteed to bring a positive impact. Intelligent systems are one such technology since their effect on improving customer experience is visible and proven by numerous players across different industries. The business in this current case study has to implement an intelligent system because it corresponds with its requirements. Primarily, an intelligent system contributes to the store’s efforts to become more customer-focused since it facilitates the process of searching for clients enabling them to find the needed items faster. Additionally, the technology will promote the business’s sales growth since customers will view a large assortment of clothes suggested to them by the responsive, intelligent system and thus will be likely to buy more products. Moreover, intelligent systems will help the store integrate smart online shopping, which will not only incorporate a display of available products but also grant clients certain tools for browsing the items based on their preferences. The main shortcoming of intelligent systems technology is the fact that it does not meet the requirements of managing brick-and-mortar processes.
The two aforementioned technologies have different purposes but can equally contribute to the success of the business and also can work in synergy. According to research, more than sixty percent of the executive managers of major retail companies shared the opinion that intelligence-based applications were integral to improving the performance of retail businesses (Gonzalo et al., 2020). Both of the technologies are related to the field of intelligence, and using them together can yield more positive results for the business. Specifically, when used in combination, business analytics and intelligent systems will allow the business to integrate online shopping by making it smarter in a way that is both appealing to clients and beneficial for the store. The two technologies will also ensure better inventory management since, thanks to them, the business will know which items will be likely to be sold based on the clients’ search history and the system’s recommendations. They will facilitate internal collaboration since the store managers will not argue over which items to order from suppliers because the system will provide them with its predictions. Finally, the business analytics tool for predicting trends will guarantee improved cooperation with the suppliers because the business will be able to order certain items in advance without the risk of possible delays.
The business analytics solution will allow the store to assess the data on their clients’ preferences and determine which products to store and which ones have to be removed from the inventory list. It will significantly enhance the store’s efficiency because it will have information on the items which have a better chance of being sold. Based on such data, the business will minimize the number of clothes that are not as popular among the clientele. Moreover, the information gathered with the help of the intelligent system, namely the preferences of clients, will be crucial for the effective use of the business analytics solution. Together, these technologies will meet more requirements of the business. The intelligent system will provide customers with better options for finding the articles of clothing they truly desire and wish to obtain. The intelligent system solution will position the business for future growth because it will provide a certain degree of customization and a tailored approach to clients, which are crucial in e-commerce. The business analytics will contribute to the store’s online success by helping it decide on the most relevant and trendy items for the clients.
Dubrova, D. (2021). Fashion and technology; how online clothing retailers can leverage AI in 2021.
Gonzalo, A., Harreis, H., Altable, C.S., & Villepelet, C. (2020). Fashion’s digital transformation: Now or never.
Keunyoung, O. (2020). The roles of data analytics in the fashion industry. Journal of Textile Engineering and Fashion Technology, 6(3):102-104.
Milnes, H. (2018). Kohl’s is improving store performance by equipping managers with real-time customer data. Digiday.
Unglesbee, B. (2021). Fashion apparel makes a comeback, focus on digital deepens, and other 2021 predictions. Retail Dive.
Varley, R., Roncha, A., Radclyffe-Thomas, N., & Gee, L. (2019). Fashion management: A strategic approach. Springer.