Unlocking Sustainable Efficiency instead of Using Average Data

Understanding the impact of this practice is vital for companies striving to enhance product quality, reduce costs, and bolster sustainability by accurately measuring and optimizing water and energy (or resource) consumption in the ever-evolving landscape of fashion and textiles.

In this article, we will explore the implications of relying on average data in the textile and apparel sector, shedding light on the hidden challenges and consequences that often remain unnoticed. The misuse of seemingly innocent data points, such as average data, can play a role in perpetuating greenwashing.

Using average data instead of accurate data in manufacturing processes in the textile and apparel industry can lead to several significant problems and challenges:

Inefficiency

Average data may not accurately represent the variables within a manufacturing process. This can result in inefficiencies, as the process may not be optimized for the actual conditions and variations encountered. However, the real challenge lies in recognizing that only accurate data can inspire manufacturers to make informed decisions that reduce resource consumption and improve sustainability. Inefficient processes not only lead to higher production costs and longer lead times but also hinder progress towards a more sustainable future.

Competitive Obstacles

In industries like textiles and apparel, where competition is high, companies that can produce high-quality products efficiently gain a competitive advantage. Using accurate data for process optimization can help achieve this advantage while relying on averages can put a company at a disadvantage.

Compliance and Regulation Issues

Many industries, including textiles and apparel, are subject to regulations and quality standards. Failing to meet these standards due to inaccurate data can result in legal and regulatory issues.

Process Variability

Manufacturing processes in textiles and apparel often involve complex machinery and multiple steps. Variability in these processes can lead to inconsistent product sizing, color, and other characteristics. Accurate data is crucial for managing and controlling this variability.

Difficulty in Continuous Improvement

Accurate data is essential for implementing continuous improvement initiatives such as Six Sigma or Lean Manufacturing. Without precise data, it is challenging to identify areas for improvement and measure the effectiveness of process changes.
Continuous improvement must be driven by customers (e.g., brands and retailers).

Supply Chain Disruptions

Using average data can lead to inaccurate demand forecasts and production planning, which can result in supply chain disruptions, including stockouts or excessive inventory. In this case, supply chains must be optimized to achieve the required quality with reduced resources.

In summary, using average data instead of accurate data in the textile and apparel industry can lead to a range of operational, quality, and cost-related problems. To remain competitive and meet customer expectations, it is crucial for companies in this industry to invest in accurate data collection, analysis, and process optimization.

User-friendly tools that simplify the calculation of real resource consumption for every product run, size variation, and color option can greatly enhance a company's sustainability efforts and help consumers make more informed choices, ultimately contributing to a more eco-conscious and environmentally responsible marketplace.

It is also recommended to use cutting-edge platforms that streamline the integration of all resources/inputs at every stage of the supply chain. So, a more comprehensive evaluation of the final product’s sustainability is a must.