Table 1. Key order-winners and qualifiers for the Pearlwear business.
Operations support
- Operations at Fabritex support Pearlwear’s business needs by providing the type of fabric that the latter requires for manufacturing clothing items, namely, lingerie;
- As of now, Fabritex employes two types of knitting processes called warp and weft;
- The dying is done at another plant that is located in 12 miles from Fabritex. A part of the said plant is dedicated specifically to Fabritex’s requirements to ensure that the end product is up to the company’s standards;
- The end product has two basic specifications: shade and knitting technique. From this information, buyers such as Pearlwear can conclude exactly which products may be of interest for them;
- Knitting times vary depending on the type of fabric, which sometimes complicates the calculation of delivery time. One thing that should be noted about operations at Fabritex is set-up or changeover times. Machines cannot produce fabric without breaks; to avoid accidents, a changeover is needed every four hours, after which a machine receives some downtime. During changeovers, the production processes come to a halt, which should also be considered when predicting delivery times;
- Fabritex compensates for its shortcomings when it comes to set-ups and changeovers by working long hours. As seen from the case description, machines are working 24 hours/ five days a week;
- The process of sending fabric to the dying factory and receiving it back for a checkup and inspection takes about six days;
- Fabrics are typically made to order; at that, the availability of raw materials, the complexity of the order, and other factors are considered. Delivery time is calculated by the system based on the previous orders;
- Production may be customized upon request: in this case, delivery time may change as the process will have to be adjusted to meet customers’ needs (Christopher 2016);
- Some of the strategies that Fabritex employs from time to time includes stocking up on greige in anticipation of big orders. However, sometimes marketers misread the situation, and greige ends up being unwanted. In this case, one measure that Fabritex might undertake is to sell the remaining stock at more attractive, lower prices.
Additional information
As it is apparent from the case description and analysis, Fabritex is facing some issues regarding operations performance. Probably the greatest challenge at hand is optimizing the delivery time to serve Pearlwear’s needs and gain its trust. Therefore, there needs to be gathered some additional information on how exactly Fabritex handles deliveries. First and foremost, the very system that processes requests needs to be revised (Selvarajah & Zhang 2014). It is possible that it needs an update, and probably, underwhelming delivery time could be attributed to its malfunctioning.
Apart from “hard” factors, “soft” factors should also be analyzed to gain deeper insights into why Fabritex is performing below the optimal level. As it has been mentioned in the case description, the company needs to improve communication at all levels.
Bad communication might as well be one of the reasons why Fabritex does not meet its goals (Wilson, Zeithaml, Bitner & Gremler 2016). It makes sense to explore the relationships between different departments and locate obstacles to efficient interactions (Goetsch & Davis 2014). Aside from that, employees’ motivation and engagement could be studied to see whether they understand their role in the company and are satisfied with working conditions. In summation, to advance the case of Fabritex, both hard and soft factors should be taken into account, starting from the system in use and ending with people who make its functioning possible.
Reference List
Cavusgil, ST et al. 2014, International business, Pearson Australia.
Christopher, M 2016, Logistics & supply chain management, Pearson UK.
Goetsch, DL & Davis, S 2014, Quality management for organizational excellence: Introduction to total quality, Pearson US.
Hannington, T 2016, How to measure and manage your corporate reputation, Routledge, Abingdon-on-Thames.
Luo, Z, Chen, X, Chen, J & Wang, X 2017, ‘Optimal pricing policies for differentiated brands under different supply chain power structures’, European Journal of Operational Research, vol. 259, no. 2, pp. 437-451.
Moran, G, Muzellec, L & Nolan, E 2014, ‘Consumer moments of truth in the digital context: How “search” and “e-word of mouth” can fuel consumer decision making’, Journal of Advertising Research, vol. 54, no. 2, pp. 200-204.
San Gan, S, Pujawan, IN & Widodo, B 2015, ‘Pricing decision model for new and remanufactured short-life cycle products with time-dependent demand’, Operations Research Perspectives, vol. 2, pp. 1-12.
Sancha, C, Longoni, A & Giménez, C 2015, ‘Sustainable supplier development practices: Drivers and enablers in a global context’, Journal of Purchasing and Supply Management, vol. 21, no. 2, pp. 95-102.
Selvarajah, E & Zhang, R 2014, ‘Supply chain scheduling at the manufacturer to minimize inventory holding and delivery costs’, International Journal of Production Economics, vol. 147, pp. 117-124.
Stadtler, H 2015, Supply chain management: An overview. In Supply chain management and advanced planning (pp. 3-28), Springer, Berlin, Heidelberg.
Thomassey, S 2014, Sales forecasting in apparel and fashion industry: a review, in Intelligent fashion forecasting systems: models and applications (pp. 9-27). Springer, Berlin, Heidelberg.
Wierenga, B & Van der Lans, R, eds. 2017, Handbook of marketing decision models (Vol. 254), Springer.
Wilson, A, Zeithaml, V, Bitner, MJ & Gremler, D 2016, Services marketing: Integrating customer focus across the firm, 3rd European edn, UK.
Xiao, T & Qi, X 2016, ‘A two-stage supply chain with demand sensitive to price, delivery time, and reliability of delivery’, Annals of Operations Research, vol. 241, no. 1-2, pp. 475-496.