The retail industry is constantly evolving. Those who stay behind real-time customer and sales feedback often end up forced into liquidation. Retail brand Toys R Us faced a dismal conclusion last week as all 735 UK stores closed. In this competitive industry it is important to look at well-performing brands and see what it is they do that sets them apart.
Zara come to mind as one of the most successful fashion retail brand on the market. Inditex, named the world’s largest fashion retailer in 2008, owns Zara. Although Zara is just one of their eight brands, it accounts for two thirds of their total sales. Zara’s key to success? Measuring trends in real-time and acting on them. Data is the main ingredient.
Zara has over 4300 stores in more than 70 different countries. Their POS, ERP, Workforce, HR, Marketing and Finance systems all play a role in determining what stock gets sent where, what promotions are put into place, where are greater amounts of staff needed plus what items are customers not responding to and when do we need to pull these items off the shelves? The result? A brand that delivers products most customers appreciate while cutting costs at the same time.
A key concept Zara employs is the just-in-time concept and Theory of Constraints (TOC) fundamentals. They identify the most fundamental limiting factor standing in the way of achieving a goal. They then systematically improve the constraint until it is no longer a limiting factor. This applies to the ever present problem of stock. Retailers want to have enough stock to sell but not too much stock on the shelves. This is why we always see only a few stock in popular sizes for each unique item. The customer feels a sense of urgency to buy that item as it might soon run out. Little do they know that item will be replaced shortly. Using TOC principles – when one item is missing in one shop but is present in another or central warehouse – Zara fast delivers the item to the store in need. When they run out, it is easily redistributed and replaced allowing all stores to perform well. One cannot achieve this without effective systems that deliver data in real-time.
Delivering data in real-time
The main obstruction to delivering data in real time is the absence of a data lake. A data lake is one, single, consolidated source of data from which real-time analysis and predictions can be drawn. A data lake consists of:
- POS data
- Customer Intelligence
- Finance and accounting systems
- HR data
- Staff workforce data
- Marketing data
Currently, most Tier 2 retailers use manual input to bring these systems together. Reports take over an hour each day to be drawn up. Site managers put in overtime hours on the weekend to collect this data. Trends and predictions can be provided, at the most, once a day.
What hurts the most is, because it takes so long to organise such vast amounts of data, the forecasting is often inaccurate as it relies on information too far back in the past.
Accurate prediction and foresight is needed to run a successful retail chain. Ted Baker, a new up and coming brand delivering traditional English quality designs, uses a flexible approach based on current trends in their business. Ted Baker was one of the few retail fashion brands to thrive during the autumn retail slump felt by most fashion brands. At the end of January, their annual sales revenue grew by 11.4%.
This hike is largely due to their current strategy where they focus on online sales and rely more on concession stores rather than standalone shops. Ted Baker has 75 standalone stores and 327 concession stores. They analyse data- assessing the performance of each store. If one is not achieving optimal performance, the concession is removed- minimising cost. This flexible approach means maximum results at minimum investment. Without an accurate measurement of customer intelligence and sales forecasting, Ted Baker would have reduced visibility and not have the power to make these decisions.
The main constraint to delivering data in real time is the complex and sheer number of different systems retailers need. ERP for stock management and POS systems for sales need to be matched with accounting and financial systems. An accurate measure of stock, sales and revenue is formed. HR systems and workforce data needs to be collated with sales data to effectively manage staff.
AI to the rescue
Big data and AI allows for the intelligent integration of these different systems- in turn allowing brands and chains to gain visibility into their products at least twice a day. The first time is to measure current trends and put interventions into place to facilitate positive impact. The second time is to examine the results of their intervention strategies.
For example, a Zara store can access their POS systems to see vast amounts of one item being sold. Management can then access ERP systems to send more stock to stores selling that item. They can use marketing data to determine if this is a result of an effective marketing campaign. Customer intelligence can be accessed to see what target market is buying, why they are buying it and whether this can be replicated among other items. If one store is particularly overloaded with sales- comparisons against workforce data can be generated to see if there is enough staff on hand in that store to facilitate maximum sales. These are quick decisions that need to be generated from efficient insight. Quick insight is impossible to achieve without an integrated, intelligent data lake.
Actionable insight is delivered quickly with minimum cost and labour. If concessions are not performing? Change them or shut them down. If items are not selling? Stop manufacturing and re-distribute them. If marketing campaigns do not lead to increases in sales? Change them. It is this flexible approach that makes brands like Zara and Ted Baker stand out. Whether you are on level with these brands or just a Tier 2 retailer hoping to expand- real time data can give you the power and flexibility to make better decisions.