Retailing discovers science

More than at any other time, Canadian retailers face a myriad of business challenges, from a slowing economy to the entry of American giants like Target and Marshalls.  To drive sales, improve customer service and increase profitability, Canadian retailers should consider the insights of Professor Marshall Fisher, an operations professor at Wharton.  Fisher argues that operational “science” can help merchants better match product supply with customer demand. OS is already being practiced by some leading retailers including Zara, Walmart and World, a successful Japanese clothing manufacturer. 

In laymen’s terms, OS looks to ensure that customers can consistently and easily find the items they are looking for.  At the same time, OS emphasizes product supply management to minimize over-stocking,  a situation which leads to expensive discounting.  At the heart of OS is the use of advanced marketing and IT methodologies known as data analytics.

Marshall Fisher was recently interviewed in Knowledge@Wharton, a newsletter published by the Wharton School at the University of Pennsylvania.  Below are some of his key conclusions:    

Poor operational performance is costly

Over-stocks create inventory problems, leading to cash flow issues and expensive discounting.  For perspective, the average item now sells for 40% off its full price, up from 33% in the mid 1990s.  Furthermore, out-of-stocks and poor merchandising decisions are resulting in sizeable revenue losses.  According to Fisher,  up to one-third of potential sales are lost when customers walk into a store clearly intending to buy something and walk out empty-handed because they couldn’t find the item.

Small operational gains can drive big bottom line improvements in a high fixed cost business like retail.

Assuming a merchant has a gross margin of 50%, a small 5% increase in sales can generate a 2.5% increase in profit.  For those retailers who lose one-third of potential customer sales via out-of-stocks, modest operational improvements could lead to revenue increases that double their profits.

Retailers are not effectively using the data they have. 

Most firms are awash with point of sale, customer satisfaction and demographic data.  To fully leverage this data, managers should apply data analytics methodologies, such as: 1) determine what of the collected data (e.g. product sales by form by store) is relevant to its corporate strategy;  2)  ensure the collected data is granular enough to be actionable by store;  and; 3) understand what and how factors like weather, merchandising and promotion impact these numbers. 

There is a “science” to deciding which products to add. 

Deciding which products or stock keeping units to add is more difficult than figuring what to cull – that is, eliminating low performing SKUs by store etc.  One data analytics approach is to  compare sales results of different SKUs by their attributes like color and style.  New products that have attribute profiles that mirror the most successful SKUs or fill obvious gaps (e.g., needed for the local selling area) would be added to the merchandising mix.

In-store execution is crucial.   

OS strategies will flounder if the customer experience is poor, merchandising strategies are counter-productive or front-line staff are poorly trained or lacking sufficient numbers.

According to Fisher, most merchants are (on average) under-staffed, and they tend to under-invest in the people they have.  A human capital deficit arises from the fact that retailers typically view labor as an expense rather than an investment. This deficit creates an in-store execution gap that translates into poor customer service and lower revenues.  For perspective, Fisher’s research with customer satisfaction surveys suggest that for every extra $1 invested in adding employees, an incremental $10 will be generated in revenue.

Explore greater supply chain speed and agility

Inflexible or slow supply chains are often a root cause of the supply and demand mismatch.  Increasing speed can be accomplished in many ways, including:  producing more accurate demand forecasts, optimizing the product mix and enhancing supply chain management.  To accomplish the latter, managers could analyze the optimal (read:  fastest and cheapest) way of getting product from offshore to the store.  For example, will operational performance increase with faster but more expensive shipping as opposed to slower but cheaper shipping?  This analysis could prompt retailers to backshore production previously sourced in Asia or consider faster shipment strategies like air freight.

For more information on our services and work, please visit the Quanta Consulting Inc. web site.


2 comments so far

  1. […] Express, Capital One, Amazon and CarMax use cutting-edge Data Analytics to outflank competition, improve marketing & operational efficiencies and get closer to their customer’s needs.  Making sense of internally generated data – it’s […]

  2. […] Express, Capital One, Amazon and CarMax use cutting-edge data analytics to outflank competition, improve marketing & operational efficiencies and get closer to their customer’s needs.  Making sense of internally generated data – its […]

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