Before we jump to any conclusion, it's mandatory to know what Inventory Optimization is?
Inventory optimization is the operation of lessening inventory malformation, a difficulty that arises from out-of-stock and overstock inventory situations. Excellent inventory management branches out of a single dispute: storing just enough stock in the warehouse such that the business keeps running but not excess stock to deplete its restrained cash reserves.
And why does it bother us?
Passed are the days of manually checking inventory. Artificial Intelligence helps companies leverage this task and invest their human resource in other productive businesses. For example- a facility manager can keep track of a product in real-time without even putting efforts manually. AI is now extensively used as a duplicate for the refrigerator and individual shelf level. This gives a chance for companies to keep track of total purchase orders and also to guarantee that inventory is in the optimization stage. When there is an inventory drop, AI will send out a repurchase order without any manual interference. This enhances functioning efficiency.
Smart Managers always tend to avoid hurdles like excess inventory costs because it is highly unproductive and seldom results in poor returns. Their liquidation strategies typically attempt to liquidate stock for max return or at minimal expense.
How can it surge your profit margins
Brands which can evade the dependency of third-party discount retailers/e-tailers will experience an accession in brand value and profit margins both online and offline.In the race of optimizing Inventory costs, brands which keep discount in-house through a factory outlet owned-asset structure are leading with a huge margin.
Consider the case of Amazon- Amazon has intertwined Artificial Intelligence very profoundly in their supply chains. In almost every phase of their operations, AI technologies like time series prediction and reinforcement learning systems are being used. User demand, supplier backorders, warehouse optimization, stock levels are all being controlled by either machine learning or more complex artificial intelligence systems.
The game of demands
The greatest relief that has come with the deployment of AI is Accurate Demand Forecast. The basic framework revolves around the structuring of a time series prediction model to calculate what demand will be like for the following days across all items in your inventory. The perks of having such a model include the facility to incorporate external data sources into the system to measure if they have a positive impact on demand.
One of the tricky aspects in inventory optimization is the variable nature of inventory items. Each item is different and needs to be managed differently. Some elements may be highly predictable and regular in their movement, whereas some items are maybe highly unpredictable and irregular but equally indispensable to keep in stock. Undertaking significance testing former to creating any artificial intelligence implementations enables you to learn what external data is essential and filter the list of items to be predicted.
Reinforcement Learning- the next step
However, further Advanced Artificial Intelligence can also be deployed to optimize the inventory operations and cost. According to study, a company used Reinforcement Learning which cut their 32% operation cost. Reinforcement Learning is a domain in artificial intelligence where the models don’t merely make predictions or classifications but act on these predictions. It is a more advanced artificial intelligence strategy that comprises a model taking a fast charge of the inventory operations, with human checks and insights.
On a concluding note, it’s undebatable that Artificial Intelligence along with Predictive Analytics holds power to transform and ameliorate the future. Therefore, the smart managers are already on the roll to infuse this technology and soar their businesses to grand heights.