How can inventory managers leverage data analytics and visualization tools to enhance decision making?

My experience in limited shelf life CPG manufacturing and distribution indicate that the manufacturing variables, even in a very complex multinational manufacturing and distribution environment, are more reliable and predictable than the variability injected into the demand signal by either competitive response in local or regional markets, or unplanned or responsive price promotion activity. Regional sales management teams detailed plans and their competitive intelligence must be captured and frequently refreshed by a robust Sales & Operations planning process over time. Without that human driven process input, the aggregate plan data just ages out creating waves of inventory and out of stocks that strip operating cash and punish margins.

Leveraging data-driven inventory optimization can provide a plethora of benefits ranging from financial benefits to production downtime avoidance. However, the key component to making timely and accurate decisions is the data itself. Utilizing world class data normalized to an industry specific schema will ensure the dataset is free of unnecessary duplication, contains data accuracy and consistency, enhanced where available, and product or category coding has been assigned. Incorporating legacy and non-structured data as your main source of "data-driven" decisions will provide a meaningless output subject to scrutiny. As the adage goes...Garbage in, garbage out!

As a professional Chef for over 30 years and also many years in retail management its my opinion from my experiences that old school has always worked and the old saying “if it isn’t broke then don’t fix it.” Technology isnt always the answer but hard work, mental fortitude and basic math skills w a calculator has always been proven to work. Technology has made the human race LAX AND LAZY. Count the merchandise one by one, factor in the cost ratios and you will have a near perfect inventory or atleast find the issues that lie within and address them accordingly. GS

As a consultant, I've seen the benefits and drawbacks of traditional dashboards and reports. Although KPI reports provide useful data about inventory performance, they often lack the depth of analysis required to make data-driven decisions. Reporting and BI tools show the numbers but don’t tell what these numbers mean. Interactive heatmaps, I think are a more effective approach to data analysis, allowing managers to explore their data in greater detail. With just a few clicks on the map, you can access detailed information about stock levels, velocity (ABC, XYZ), occupancy, and storage compliance. This level of interactivity helps to identify potential issues and opportunities that may have gone unnoticed with traditional reports.

I daily spend an amount of time performing Data analytics -the process of sorting out structured and unstructured inventory data sets from ERP so as to provide real-time and up-to-date inventory level and availability information for planning - production operations… I agree that visualising data is the process of presenting data in graphical or pictorial forms, such as charts, graphs, maps, or tables…

In my experience transitioning from a more traditional inventory approach to a cloud based system was a game changer. It reduced complexity, improved accuracy, and saved time. There was an up front investment in terms of time and materials and that investment paid for itself within two weeks of adopting a new system. Employee morale improved and our ability to more accurately track the full life cycle of inventory was unparalleled. I would only have been happier had I explored RFID in conjunction with cloud based systems.

This is a very useful technology to improve the locations accuracy of the objects and to give a better visibility of where/ when the materials moved in/ out warehouse (specially in big warehouses). The only downside of the RFID is lack of signal frequency when the warehouse has double deep locations of materials storage as it can't get the signal back from the tags attached to the objects.