Analytics: A New way of Managing Inventory

Today, the companies are experiencing a major upheaval in the way their supply chains are managed due to the advent of big data, data science and predictive analytics. With an estimate of 40 zettabytes (40 trillion gigabytes) by 2020 the data industry would change the way of addressing the challenges related to inventory optimization. On the basis of inventory carrying costs studies, it is estimated that 25-30% of the inventory costs represent the inventory on hand for a usual company. It is also seen that a 5% decrease in inventory cost can result upto $20 million increase in profits for a typical Fortune 1000 company.

The way Inventory is Optimized Today

While inventory optimization is all about finding the right balance between meeting the customer demands and funding the cost of the inventory required for keeping stocks as per the changing demand. It has become an uphill task for major organizations given lack of understanding of the actual demand and a lack of coordination between supply chain upstream and downstream functions. Businesses do not invest the time or do not have the analytical capabilities to understand customer needs and sales patterns, which ultimately results in poor understanding of actual demand. It becomes dangerous when the planning is done without the consensus of the sales contact.

This is point, where companies having global supply chains should look to introduce their strategic left hand to their operational right hand. The Supply chain planning and point of sales need to have visibility over each other’s functions which in turn will create an increased focus on the use of analytics and building capabilities in sales pattern analysis and forecasting. The process of understanding and solving issues in inventory optimization is usually very data intensive. It involves handling large data sets and the ability to rationally consolidate different information sources.

How Analytics makes a Difference

Nowadays, more companies are exploiting observed patterns, correlations and relationship among data elements by using complex algorithms and advanced machine learning techniques to make supply chain decisions and optimize inventory levels.

Walmart has evolved to be one of the early adaptors in leveraging various means to enable real-time analysis of the 2.5 petabytes of data, which it processes every hour. Analytics has enabled a rapid response to market changes or issues at stores. Walmart now also has the world’s largest private cloud and is employing it to support real-time data feeds to its decision-makers. Walmart’s “Data Café” timely information for a large cross-section of operational staff looking to resolve daily issues, not just a handful of strategic decision makers.

Conclusion

It is inescapable with the amount of available connectivity, capacity, transparency of data and virtually limitless computing power at tap that this would be the approach companies would opt for in the world of inventory management. The million-dollar question would always be how accurate and responsive these systems would be, which will again require precise coordination across all levels of the supply chain.

References

http://sloanreview.mit.edu/article/how-to-do-strategic-supplychain-planning/
Data Science, PredictiveAnalytics, and BigData: A Revolution That Will Transform SupplyChain Design and Management: Waller & Fawcett
https://www.rtinsights.com/walmart-cloud-inventory-management-real-time-data/
https://rav.no/wp-content/uploads/2015/03/Predictive-inventory-IBM.pdf

What we found interesting

http://www.ibmbigdatahub.com/blog/5-inventory-analytics-best-practices-achieve-inventory-optimization