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Opinion: Predictive Analytics and Machine Learning AI in the Retail Supply Chain

In retail, supply chain efficiency is essential. Inventory management, picking, packing and shipping are all time and resource-intensive processes which can have a dramatic impact on a business's bottom line.

The problem is these are complex processes, particularly when it comes to large scale operations covering multiple outlets and territories. The fact they are often dependent on outside forces - suppliers, service providers and even weather - make getting it right even more difficult.

This is why retailers - both big and, increasingly, smaller operations too - are keen adopters of Big Data-driven analytics technology. Creating efficiencies in complex systems which involve multiple, often compartmentalized processes is an area where this technology excels. In short, itís about the ability of machines to make lots of little savings and efficiencies, which together add up to very large ones.

Monte Zweben, CEO of Splice Machine, which provides predictive systems for industry, talked me through three key areas where retailers are increasingly looking towards data-driven analytics in order to drive efficiencies in their supply chains. We also talked about why this approach is going to become increasingly important for businesses in all sectors which want to stay ahead of the pack and foster innovation.

Filling your customersí needs more quickly

Todayís Internet of Things industry means that everything is connected and capable of collecting and sharing data on how it is operating. This means that everything can be measured and ó through the use of advanced analytics tools such as machine learning ó rigorously interrogated until it gives up all its secrets on how it works, and, crucially, how it interacts with every other part of an operation.

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