Utilizing quality assurance data has made it possible for businesses to continuously innovate and conduct research to guarantee the safety and reliability of their products.
Big Data gathered by quality assurance teams from various processes can be applied in multiple ways. For example, to enhance supply chain efficiency, cut recurring costs, enhance productivity, and as a consequence, improve margins. This can be attained by gaining valuable insights from collected data for predicting and preventing problems rather than wasting time and money on solving them.
In apparel manufacturing factories, a vast amount of data is recorded at multiple stages:
- Pre-Production
- Fabric And Raw Material Inspection
- Merchandizing Reports
- Lab-Test Reports
- Broken Needle Records
- Industrial Engineering Analysis Records
- Measurement Checking At multiple stages
- In-Line checking
- End-of-Line checking
- In-House Quality Audits
- Buyer’s Quality Audits
- And, of course, the all-important Final Inspections
This forces the question on apparel manufacturers, “To what meaningful use has this data ever been put?”
Today, manufacturers are actively seeking to determine their ideal production processes using the power of data. Big data analytics can be used to uncover innovative new ways of improving performance. Quality assurance data is a critical piece of the puzzle for any business looking to enhance its margins.
Read: Predict And Prevent Problems Instead Of Solving Them
There are many benefits to analyzing quality assurance data, some of which include the following:
- Identifying areas for improvement in the manufacturing process
- Eliminating issues that are the root cause of defective products
- Improving communication between departments
- Enhancing cooperation between factories and suppliers
- Reducing the need for reworks and repairs
- Streamlining the production process
- Shortening lead times
- And, ultimately, reducing costs.
Over the last 20 years, manufacturers have begun using data to decrease the manufacturing process’s variability and improve output and quality. Similarly, an apparel manufacturing factory can use advanced analytics to fine-tune its whole product-development process and improve performance by being first-time right while also cutting costs. Machine learning models and techniques can be used to train complex algorithms on the production data that is already available, thus helping identify potential areas of inefficiency and waste.
Predictive maintenance prevents costly manufacturing machinery from failing, analyzes data across the production process to identify abnormal behaviors in advance, and ensures that proper measures can be taken to avoid prolonged periods of downtime. Predictive maintenance also helps to prevent unnecessary shutdowns by analyzing manufacturing data to detect patterns and anticipate problems before they occur.
A data-driven segmentation approach will help fashion brands, manufacturers, and retailers create customized products and marketing strategies. Applying advanced data analytics in product design or merchandising processes may enable apparel companies to increase sales volumes and lower markdowns while offering products consumers desire. With consumers more educated and engaged than ever, companies need to consider how they use big data to optimize their products and services to compete for market share.
Machine learning and AI can provide helpful insights about supplier data and help make real-time decisions. Machine learning techniques, including deep analytics, IoT, and real-time tracking, can dramatically increase visibility across the supply chain, thereby helping apparel manufacturers improve customer experiences and meet faster delivery promises.
With precise data, managers today can leverage hyper-personalization to generate higher sales, utilize demand forecasting to keep inventories in check, and optimize routing plans to reduce costs.
Quality assurance data can provide predictive and preventative insights that will help improve your bottom line. Utilizing this data is essential for any manufacturer who wants to stay competitive and keep their margins healthy.
At Vineet Sethi Consulting, we believe that Business and People are two sides of the same coin. Our approach to transforming organizations, teams, and individuals is based on Standard Customization, stemming from the philosophy that no one size fits all.
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