The Ultimate Key to Performing Inventory Analysis From Scratch
Inventory analysis sounds like a daunting task. If you’re very lucky, you already have all the data you need at your fingertips ready to turn into actionable insights that will make a real difference to your bottom line.
If so, you can probably stop reading now. If not, then inventory analysis might be the tool you need to turn your business into a profit making machine and we have the key to making it happen.
In reality, the data you need is spread over multiple systems, with yet more data in spreadsheets and who knows where else, performing any sort of inventory analysis on each source of data will never provide a holistic ‘big picture’ view of your enterprise, but a single consolidated view seems out of reach because the different sources of data are all inconsistent.
How do you perform a successful inventory analysis if the same items are measured in different units when bought, stocked and sold? How do you allocate a value to your stock which is managed in locations with different cost bases and with items supplied at different times? And let’s not forget about those annoying expiry dates on perishables…
Getting a single view of all this seemingly inconsistent data can be tricky, but is exactly what is required. An Information Management article suggests that ‘The demand for integration in today’s business environment is greater than ever before’.
In case you thought dealing with inconsistent data was easy, Gary Allemann (@Gary_Allemann) would disagree. His article says, “The number of data stores is also proliferating – companies must also cope with diverse environments, ranging from legacy enterprise resource planning (ERP), mainframe and data warehouse environments, to cutting-edge cloud, Hadoop and other big data platforms.”
Ulimate Key: Data Warehousing to the Rescue
The commonly accepted solution is to transform all the disparate data sources into a single, consolidated data warehouse. All units are standardised along the way, costs are allocated, stock is grouped into lots and linked to a shelf-life. And all that ‘extra’ data in those spreadsheets can be thrown into the mix too.
The hard work is done when creating and maintaining the data warehouse. Get that part right, and quality inventory analysis really could be at your fingertips. Then you can worry about the results of the inventory analysis instead of worrying about how to go about it!
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