Staying fashionable with fast-analytics

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The retail industry for years has made use of data and intuition to forecast customer demands. With tight margins, volatile markets, and the pace at which customer demands change these days, retailers and wholesalers can’t rely on intuition alone to drive growth and adapt to change. They need data-guided insights. By looking across datasets, businesses ranging from fashion houses to retailers to e-tailers have been able to optimize their product mix and inventory by season, market, or segment in a few clicks.
Driving innovation in fashion with speed-to-insights
One game-changer in empowering these businesses to making these leaps in optimization is data analytics that drives speed-to-insight – not confined within IT teams, but democratized across the organization, and placed in the hands of business users who need it most.
With self-service analytics, business users can zoom in to a period or market, compare individual stores or locations, or get the bigger picture across all one’s operations to create sustainable, profitable strategies. When conditions change, these users become ready with a data engine that handles vast amount of information in real time.
Outperforming the category with self-service analytics
One of Singapore’s marque department store chains, Metro is an example of a fashion retailer that has been able to rise above its category by becoming nimbler and more innovative with self-service data analytics. Its share price gained 6.3 per cent in February this year, against a marginal dip in Singapore’s Straits Times Index, the health barometer of the local market, by 3.2 per cent. Similarly, Metro reported an increase in retail sales in its third quarter performance, just as Singapore saw falling retail numbers across the board.
Established in the 1950s as a textile store, Metro has grown over the years into a multi-national property and retail group. The company currently has two core business divisions – property development and investment, and retail. Its geographical focus is in China, Indonesia, Singapore, and the United Kingdom.
In spite of its roots in ‘brick-and-mortar’ – as opposed to being another tech unicorn – Metro’s management was agile enough to realize that shoppers are now making more informed buying decisions, mainly due to the accessibility and convenience of e-commerce. To remain competitive, the team empowered its staff, beyond the IT department, to see and understand data for themselves. In a case study, Metro shared how its team looked into data of popular shoe sizes and discovered that customers rarely purchased half sizes. As a result, Metro stocked more of the popular sizes and significantly reduced the problem of overstock of inventory. In turn, this has led to savings in markdowns, storage costs, and opportunity costs.
In another example of how a company has been able to make the innovation leap is local company, Marico which is one of India’s leading consumer products and services companies in the global beauty and wellness space. An expanding middle class population with rising average income and increasing spending power, coupled with rapid urbanization, have galvanized India’s consumption story. Fast-moving consumer goods (FMCG), with a market size of over US$13.1 billion as of 2012, has been identified as the fourth largest sector in India’s economy.
Marico depended on daily sales reporting that the staff would prepare and email to senior management. These reports offered little flexibility and management was not impressed as they could only get few insights out of them. Lack of standardization and inaccuracies also plagued these manually created reports.
Today, the company analyzes a large amount of data on retail behavior, sales and marketing, inventory movement, procurement of key inputs, etc., gaining detailed insights into the company’s performance. The users are able to present the data in a visual form to teams from various departments in the company. This has helped drive a change management initiative to provide easy-to-consume and highly customized dashboards/reports (updated with the latest data) to the company’s decision-makers and management.
In the recent times, India has emerged as one of the most important and fast growing markets for big data analytics with some of the big names like Snapdeal, Westside, and Myntra leading the way. Stories like Metro’s and Marico’s, and other players in the fashion eco-system point to the importance of organizational agility and the role that data can play in driving speed-to-insight which enables one to stay ahead of changes in the marketplace.
In a nutshell, big data helps and can further revolutionize the fashion retail industry in almost each and every aspect like sales, marketing, advertising, supply chains, etc. The usage of big data analytics boils down to delivering the core need of every analyst which is to “Have the ability to see and understand their data, so they can make better business decisions”.
Staying fashionable with fast-analyticsABOUT THE AUTHOR: Deepak is the Country Manager for Tableau India and is responsible for sales and customer success in the region. He has spent his early years with Tableau in Dallas where he worked on Enterprise Sales and was responsible for various sales territories in the Enterprise and Federal government space.

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