The goal of this article is to examine opportunities and show the approach of using big data analytics to boost productivity in the case of clothing manufacturing factories in a sustainable way. The Bangladeshi manufacturing industry is mainly dominated by the apparel and textile sector for a long time now, and this has seen a large growth over the years. However, this industry is still far from using the latest technologies to improve productivity even further and bring sustainability. Usually, manufacturing operations involve the generation of a large amount of structured or unstructured, useful or non-useful data on a daily basis. This huge amount of information is known as big data, which is difficult to handle by using traditional data management and analysis tools. However, with the help of big data analytics used in a proper method, the collected information can be used to track insufficiencies in different areas of manufacturing operations. This research is conducted based on a similar idea where problems are identified, and production data collected from a garments manufacturing plant in Bangladesh are analyzed. Based on real factory data, several hypothetical frameworks were developed to implement and analyse the production data with the help of big data analytics, computerized sewing machines, radio frequency identification (RFID) tags and passive infrared sensors. The paper also shows an estimated implementation cost and return on investment of the suggested approach.