Big data. Predictive analytics. Machine learning. Artificial intelligence.
All of these concepts can produce significant advantages to organisations of all shapes and sizes - particularly, in efficiently managing supply chains in the retail industry.
However, a company can't run before it walks and the "basics" should not be forgotten for two key reasons:
- There are substantial advantages that can be generated through the more comprehensive use of standard data analytical techniques. Sometimes, the most simple 'cutting and dicing' of data can provide insight into how to improve processes and systems.
2. The "garbage in, garbage out" principle equally applies to these concepts - if companies learn from incomplete, inaccurate or out of date data, then the algorithms may not drive the optimal results, or worse, still could send companies in the wrong direction.
The aforementioned concepts are very powerful, but organisations need to ensure that they are "feeding" the algorithms behind them with accurate, complete and timely data. They also should not overlook the powerful insights that can be derived from more standard analytics.
In retail, supply chain efficiency is essential. Inventory management, picking, packing and shipping are all time and resource-intensive processes which can have dramatic impact on a business’s bottom line... 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, it’s about the ability of machines to make lots of little savings and efficiencies, which together add up to very large ones.