One of the tools of our suite, namely QQinventory.HealthCheck™ is able to evaluate the total losses coming from Out-of-stock, No-Moving and Slow-Moving situations over a period of time, day by day, item by item, location by location, case by case. And provides also overall, consolidated infomation at the group level.

And when we deployed this tool to some of our big retailing clients, the results our analytics were outlining were pretty dramatic: the total loss from all these 3 inventory issues were exceeding twice the net profit for the same period ! (see for yourself below !)

Therefore our initial afirmation has a strong base.  See following a snapshop from such a real case, with real data (just depersonalized), from a retailer: estimating a cut of only 40% of total losses calculated by QQinventory.HealthCheck™ we can get over 100% net profit increase !
(For this durables retailer, expiration date was not a major inventory loss driver., so we didnt’t include it in the model, for the moment).

The details on how we have modelled the losses on each situation are available on request. And all these details are subject of further improvements and adjustments, based on your business specifics and understandings, of course. 

The averaged assumptions you can see on the bottom-right side of the analytics below (with red and purple background) is underlining a weighted average of the parameters that are set specifically, as relevant values for special situations, combining general company values with specific values for different level entities, such as brands, suppliers, category products, or even products.