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Key Takeaways from Unified Retailing 2019

The Unified Retailing 2019 Conference hosted by Columbus Consulting yesterday was energizing, as it’s always a fun to meet up with our customers, old colleagues and friends. The speakers were excellent, with frank and interesting conversations around how to win in today’s new retail environment. However, what really struck me throughout the event was the fact that everyoneand I mean everyone—appeared to be dealing with the same type of challenges, such as:

  1. How to support an environment where store sales are dropping, e-commerce is flattening, and mobile continues to grow
  2. How to win in an environment where there are so many store closures, but just as many store openings from digitally-native brands
  3. How to support the shop anywhereexperience consumers demand
  4. How to keep product, experiences and services relevant 

As every speaker discussed different strategies to address each issue, it became apparent over the course of the day these problems haven’t really changed over the last few years. In fact, they’ve only magnified. Despite these struggles, it only solidified my beliefand that of many others in the room—of the following:

If you want to be relevant, you must consider the customer and their preferences first in everything you do.  

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Topics: artificial intelligence, inventory optimization, brick-and-mortar retail, physical stores, machine learning, awards

Lucky Brand's Approach to Successful Merchandise Allocation

The idea behind inventory allocation seems pretty straight-forward: Ensure stores are kept in stock with respect to their ability to sell merchandise. Simple enough, right? Yet, as an allocator, one end-of-season scenario you’re likely familiar with is the aching realization of a missed opportunity — where better inventory allocations in one store could have led to more transactions, fewer markdowns, and improved margins.

Of course, you and I both know the subtle art to successful allocation is far from simple. In fact, a recent U.S. retailer survey estimated inventory misjudgments, including misallocating inventory, account for more than half (53%) of unplanned markdown costs. This issue has prompted retailers, like Lucky Brand, to search for ways to infuse intelligence into their allocation systems and processes.

Mike Relich, COO of Lucky Brand, recently shared his experience leveraging Celect artificial intelligence and machine learning (AI/ML) software to successfully improve retail allocation results. 

Here are the five biggest takeaways:

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Topics: allocation, artificial intelligence, inventory optimization, brick-and-mortar retail, physical stores, machine learning, merchandise assortment

Why I'm Excited for the Future of AI & Retail

I’ve spent most of my career in the retail industry. Throughout that time, I witnessed a great deal of change – from the evolution of the stores’ role, to the seismic shift in how retailers sell within the context of convenience, service and compelling experiences. Most noticeably, the fundamental core of how retailers think has changed: Managing at averages will no longer suffice. 

Despite these ongoing transformations, the one constant—and what, for me, is the most enticing aspect of the industry—is the intimate connection retail has with the consumer. With a background in astrophysics, my passion for science and innovation fuels my desire to help retailers use technology and data to make smarter decisions and preserve this crucial connection.  

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Topics: artificial intelligence, inventory optimization, brick-and-mortar retail, advanced analytics

The Subtle Art (and Science) to Successful Retail Allocation

Knowing how and where to allocate products to the right stores can make or break a retailer. We live in a consumer-centered world. For better or worse, thanks to companies like Amazon, customer delivery expectations have changed so that they expect to get what they want and when they want it at the single click of a button. Often, this product can arrive on their doorstep the very next day.

Not wanting to be left in the dust, many brick-and-mortar stores are utilizing tools enhanced with artificial intelligence to master the subtle art of retail allocation. In today’s retail landscape, companies who do not utilize advanced analytics to allocate their products will be left behind or even fail completely. 

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Topics: data overload, allocation, artificial intelligence, inventory optimization, ecommerce, brick-and-mortar retail, data, cross-channel demand, advanced analytics, technology adoption, customer preference, accuracy, demand prediction, markdowns

The Seven Deadly Sins of Retail

The retail industry of today is a hyperactive and ever-changing environment, ripe with emerging technologies, competition, and an opportunity for those able to navigate through the waters of uncertainty. Retailers today not only need to be able to see through the smoke of change to determine the best path forward but also need to avoid the most common mistakes that have marked the end for past retailers. Here are seven deadly sins to avoid in today’s retail environment.

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Topics: data overload, artificial intelligence, inventory optimization, ecommerce, brick-and-mortar retail, innvoation, data, advanced analytics, technology adoption, customer preference, speed, accuracy, demand prediction, markdowns

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