How can artificial intelligence help retailers forecast demand?

Are retailers on the verge of extinction?

Confronted by supply chain issues, labour shortages, fickle demand, inflationary pressures and rising interest rates, retailers are scrambling to cope with the immensity of the challenges they face.

Consider a retailer with 20,000 SKUs and 50 stores (potentially 1 million store / SKU combinations) and the latter’s implications for the inventory planner. The sheer volume of data is mind boggling. Every stage of the stock life cycle, from building the range to end-of-line sell through, calls for a level of detail in execution that is constrained by available resource and the capacity of the human mind to process the myriad of data points simultaneously. Invariably, the planner compromises. They may apply approximations such as calculating at aggregate and extrapolating across individual SKUs, rely on intuition or focus on the top performing lines at the expense of the others. The outcome is stock imbalances leading to costly inter-store stock movements, markdowns and lost sales.

AI for retailers

Enter AI with its potential to alleviate all the above. When we speak of AI, we mean deep learning. But what is deep learning? How does it work? And how can you apply it in your business?

Deep learning replicates the human mind’s ability to perceive underlying, often subtle patterns in data. Consider predicting the age of a person standing in front of you. Your eyes absorb millions of bits of information, and your brain easily maps them to a notion of age based on a lifetime of experience or “training”. Now imagine if you could just as easily predict sales for all your SKUs across all stores by simply glancing at millions of rows sales history. This is the mind enhancing power of deep learning. Like the brain, deep learning algorithms learn from historical examples, but they aren’t overwhelmed by large volumes of numerical data. In fact, they require it.

AI in retail

Demand forecasting

Knowing what will sell, where and when underpins all stock optimization problems in retail. Deep learning is the panacea for demand forecasting, and by extension is the ultimate approach to accurate, autonomous stock optimization.

Retailers invariably have rich transactional history and master data which should be capitalized using AI. Companies like Seer offer artificial intelligence as a cloud service, allowing retailers to: -

  1. a)  Circumvent the cost and complexity of establishing their own AI teams and infrastructure.
  2. b)  Benefit from the considerable increases in efficiency and outcomes that AI brings.
  3. c)  Free up teams to focus on core business.

An AI implementation entails identifying a problem - typically a labour intensive or inaccurate process. Pertinent data is replicated to a secure cloud using APIs, the algorithm is trained, and predictions are made which are autonomously applied to address the problem. The process can then be repeated.

An AI enabled business will not merely survive but thrive and will be prepared to face the challenges the future will inevitably pose.

Contact the team at SEER Inc to learn more about how an AI retail solution could work for your organisation.

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