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How Zara Used the Big Data to Create Business Value

Businesses can produce value through the use of modern business analytics tools and Big Data technology. Big Data technology is capable of handling massive amounts of data, which enables more precise analysis and prediction. The larger the information, the more accurate the prediction, and businesses are capitalising on this advantage of Big Data technologies. Zara, a Spanish retailer, is one such corporation that has incorporated Big Data analytics results into its business strategy. Big Data aided Zara in increasing production, streamlining decision-making, and establishing a competitive edge in the fashion business.

Zara has long been a poster child for supply chain success, owing to its ability to identify emerging trends and promptly deliver new items to stores to meet the demands of its fashion-conscious customers. In an industry where the usual lead time for designing, producing, and delivering new clothes is approximately nine months, Zara is setting the bar with lead times as low as two to three weeks.

However, the key to this supply chain’s effectiveness is its use of data and analytics to provide precise forecasting and decision-making. It is made possible by procedures and systems that integrate data, analytics, frontline tools, and people in order to provide corporate value. Zara’s primary differentiating analytics applications include the following:-

Collection and use of real-time statistical market data

Each day, Zara’s cross-functional design teams look over sales and inventory information to determine what is selling and what isn’t, and they update their understanding of the market on a regular basis. Orders from store managers are received twice a week, providing further real-time insight on what might sell.

Supplement the statistical market data with fined-grained raw market data

Clients’ demands and preferences are frequently communicated to empowered retail managers through word-of-mouth feedback – anything from “the length of this skirt is too lengthy” to “our customers do not like the fabric of this dress.” Alternatively, managers can suggest tweaks to an existing style or totally new articles or designs.

In the case of a line of slim-fit apparel that was not selling, the usefulness of store knowledge can be illustrated by the following example: Women who tried on the slim-fit clothes said they liked how they appeared, but they couldn’t get them to fit into their typical sizes. The stores received positive comments on the outfits. Following the recall, Zara replaced the labels with those from the following size up, resulting in a sales explosion.

Create an adaptive and informal planning process.

It is embedded in the company’s flexible supply chain, which is characterised by strong ties with its 1,400 external suppliers, all of whom collaborate closely with the company’s designers and marketers. Zara experiments with a wide array of offers in tiny quantities, all based on market data collected from customers. After determining that they are a success, production is ramped up in response to local market conditions while maintaining lean stocks and a low rate of markdowns. This strategy assists firms in avoiding significant losses as a result of a large amount of capital being invested without first assessing the market response.

Disseminate information widely throughout the organisation

A single open-plan office floor serves as a home for designers, pattern makers, marketing managers, and merchandisers, as well as everyone else involved in the production. This makes it possible to have regular dialogues, chance encounters, and visual inspections. The entire team can assess the overall market, understand how their work fits into the overall picture, and identify opportunities that could otherwise slip through the cracks of organisational silos.

Build simple and effective IT systems for all

Zara’s in-house information technology mirrors the company’s culture. It is free of silos and easily available to vendors and suppliers, who have described it as simple to use and quick to respond to questions and requests.

Build a culture of data usage to learn new things and discover the right answers

Zara’s business is built around data analytics, and the use of data analytics for decision-making is encouraged because incorrect decisions are not severely punished. Zara’s new goods are said to have a failure rate of just 1 per cent, compared to an industry average of 10 per cent.

Zara first joined the virtual world of e-commerce in the United States, Europe, and Japan a few years ago. The company has now entered the next generation of using analytics for decision-making and real-time marketing, which includes tracking the behaviour of individual customers from Internet click streams, updating their preferences, and modelling their likely behaviour in real-time, as well as monitoring social-network conversations and location-specific smartphone interactions.

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