Any retail chain organisation, operating multiple stores across multiple states and cities, and sometimes in multiple countries, has to optimise its supply chain to meet varying customer demand.
Inventory imbalance refers to phenomena where some stores end up having overstock and some stores end up having understock, due to supply chain issues and poor demand planning.
Above issues or combination of issues lead to inventory imbalance problems. This imbalance affects customers and stores both negatively and ultimately the recall value of organization suffers with significant loss of customers and sales.
Inventory imbalance is a result of lack of proper inventory planning. There are multiple signs which indicate poor inventory planning which helps in identifying inventory imbalances.
Out of all indicators presented, Stock factor visualisation is described as below:
Height of the graph can be a good indicator of inventory imbalance. Bigger height suggests excess inventory and lower height suggests very less inventory on-hand. This can be a good tool for identifying inventory imbalance.
For each store-sku combination, if we can define optimal stock factor, then this visualisation will become even more informative. But to come up with an optimal stock factor itself is a complex topic and needs a separate blog as it is out of scope of the current blog. Also please note that, this optimal stock factor can also vary over the time, which makes it even more complex.
As we understood, there are various clues regarding imbalance in inventory.
We need mathematical metrics which can capture inventory imbalance and help us in identifying imbalance. These metrics guide us to accelerate continuous improvement of the whole supply chain.
In this blog, we presented a major problem of inventory imbalance in retail and various strategies on how to identify this. At this moment, we have sufficient background to focus on the solution of this problem, which we will cover in the upcoming part. We will also dig deeper into python implementation of the solution.