Data is generated throughout the
supply chain – manufacturers of consumer packaged goods analyze key performance
indicators to ensure the equipment is working at capacity. Warehouse managers
need an efficient method of sorting and picking the items on their racks.
Shippers use barcodes and labeling to ensure products reach the right
destination. For an inventory management professional, all of this data can be
overwhelming – or it can be harnessed to improve demand and stock management.
Technology can capture data
effectively and efficiently, even in vast quantities. Meaning that it can then
be used to plan collectively to provide precise forecasting that ensures
informed decisions can be made quickly. This
type of analysis encompasses many different types of data in much larger
quantities than ever before. For example, a company can use big data to analyze
petabytes of data and simultaneously cover such disparate information sources
as sales data, consumer rewards programs and weather predictions.
In particular, companies are increasingly benefiting from
analytics-driven insight that enable them to more intelligently track and ship
supplies from warehouses to stores. By
using automated data collection software to feed information into its big data
analytics program, British grocery and merchandise retailer Tesco has
dramatically boosted profits and more proactively met consumer demands. Since 2006, Tesco
has used big data analytics to improve its supply chain, primarily targeting
its inventory management systems. According to Information Age, Tesco's new
supply chain optimization program helped the company save up to £16 million
(approximately $24.5 million) annually because it is now better able to predict
customer buying habits and track the effectiveness of special sales offers.
Tesco
has developed an analytics model that uses weather patterns to properly stock
store shelves. By looking at historical buying data and expected temperature
trends, the business can accurately predict what consumers in a specific area
will want to purchase and then supply locations accordingly. For example, if
warm weather is expected to come to an area after a particularly brutal cold
spell, Information Age reported that Tesco will ensure that surrounding stores
are well stocked with more barbecue meats and less cat litter. The program is
even powerful enough to detect local habits, as what's considered hot or cold
varies by region."By
adding this effect to model, we reduced out of stock for good weather products
by a factor of four," Duncan Apthorp, Tesco's supply chain systems
development program manager, told Information Age. "That means there is a
97 percent change of customers who come into the store finding what they want,
whereas other supermarkets might not have it."
Additionally,
the retailer uses big data analytics to track the effectiveness of each sale or
special offer at its stores, the news source reported. That way, the company is
able to determine which sales should be run again and how store shelves can be
better stocked to accommodate increasing or decreasing demand of certain
products.
Big Data is here to stay and hence I would like to discuss its significant advantages if incorporated in a company's inventory management strategies.
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