The Role of Analytics in the Apparel Industry

The apparel industry is going through a tectonic shift, with channels proliferating, new markets blossoming, e-commerce booming and customers demanding personalized products instantaneously. That said, every facet of clothing and manufacturing is under scrutiny: from the fabric to the colors, the fit to the style – everything that eventually affects customer satisfaction and brand loyalty.

Considering that success in the apparel industry is built on carefully balancing demand and product development, brands must partner with innovative manufacturers that are able to streamline design and production processes. In this competitive industry, both the brands and manufacturers must look for new ways to boost their productivity and profitability all while being strategic and nimble enough to react to changes in the market.

In a data-obsesses world, the role of analytics in apparel manufacturing has become key. With the ability to provide insights into every aspect of the production lifecycle, and with 40% of all data analytics projects expected to relate to an aspect of customer experience by 2020. Here are five (5) ways in which brands can leverage analytics and make smarter business decisions:

1. Demand Forecasting

One of the best use-cases for analytics in apparel manufacturing is for demand forecasting. With analytics, brands can achieve a core strategic objective: building a tailored assortment that best meets market demands.

By better understanding customers’ style preferences, fabric choices, and fit, brands can identify a set of high-priority opportunities. They can leverage trend analytics, get products made for today’s consumers, and also predict demand for the near future. These insights come from sales from previous periods. Another thing to look at is the relative performance of the manufacturing workflow processes and of the product lines. This allows for smarter risk management and less production waste as the brand grows.

2. New Product Intelligence

One of the biggest challenges of the apparel industry is predicting the reception of new product launches. While fashion brands have long been relying on traditional focus groups to understand the demand for new products, today many are embracing analytics to generate actionable product intelligence.

Such predictive intelligence is allowing brands to discover how previous product details (style, fit, price point, etc.) were perceived by consumers. This helps them in improving the consistency of creating winning products that are a hit with customers while reducing the risk of wasted inventory.

3. Supply Chain Optimization

The complexity of supply chain management has increased tremendously thanks to globalization and the success of e-commerce. Brands today have more products to offer, ability to ship to more locations, more channels to promote and sell on, and more markets to venture into.

Great supply chain management can be the difference between hitting the market at the right time or launching a product when a new trend has already emerged. Analytics can enable brands to improve their speed-to-market and be able to trace product timelines from the conception of the product all the way through to how it is disposed in some cases. It can also help them understand the cost and efficiency of every component in the product life cycle.

4. Warehouse Management

In the fashion industry, efficient storage of apparel is an often overlooked aspect of the manufacturing process. Once products are ready to be shipped, every second becomes important, especially in a world that is increasingly subject to movements like fast fashion.

Using analytics, apparel manufacturers can establish efficient arrangement structures, better product flow management, and the most effective replenishment procedures to improve operations. Advanced analytics makes it easier to understand how to improve inventory management. It also enables brands to store the right mix of inventory across basic apparel and fashion apparel, different sizes, product categories, and price points.

5. Machine Utilization

A problem for brands working with apparel manufacturers is wasted or inefficient time throughout the manufacturing process. Analytics can provide brands and manufacturers insight into machine utilization and identifying the cause of problems, such as poor installation, overdue maintenance, misuse, or simply a lack of downtime coordination. By combining the current systems with advanced analytics, brands and apparel manufacturers can gain real-time insights into how well their manufacturing lines are operating. It can also offer information on how different configurations can improve overall efficiency.

Become a Next-Generation Brand

The rate of change is accelerating in the apparel industry and many brands are struggling to keep up. In such a fast-paced and competitive environment, data has become a core competitive advantage and the only way to truly become a next generation brand is through the use and implementation of analytics. The global datasphere that’s subject to data analysis is expected to grow by a factor of 50 by 2025. Analytics can play a big role in improving the decision-making process for all activities across the supply chain whether it be demand forecasting or knowing when equipment needs to be updated.

In the near future, success will come only to those who can best harness data and make informed business decisions. Data analytics is and will continue to be a critical tool for brands of all sizes. Learn how Suuchi Inc. can help your brand collect and leverage data in order to make the most strategic decisions for your brand regardless of your current size. We’ll ensure that you’re able to position your company as a next-generation brand that will thrive for years to come with a strong and innovative partner that will grow alongside your company.

Reach our team at if you or your team have any questions!


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