Rescue Your Business from Inventory with Machine Learning
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Rescue your business from inventory with Machine Learning

Published datePublished: Mar 10, 2018 ViewsViews: 1915
Ayush Chauhan

Ayush Chauhan

Associate Director, Pre Sales
Ayush Chauhan heads the pre-sales department at TechAhead. He's an aficionado of technology and gadgets, always looking for ways to leverage the best in tech landscape to create viable and efficient solutions to customers and wonderful user experience to their users.
Rescue your business from inventory with Machine Learning

Rescue your business from inventory with Machine Learning

When it comes down to any business dealing with physical goods, the major capital investment affecting the cash flow and profitability of the company is the inventory. There are cases where one-third of the total assets of a company comprises of its inventory alone, along with a significant amount of expenses which are associated to manage and possess it.

“Inventory is fundamentally evil.
You kind of want to manage it like you’re in the dairy business.
If it gets past its freshness date, you have a problem.”

Tim Cook, Apple

Most of the people may not perceive Tim Cook as innovative or be leading as Steve Jobs, but his real contribution to Apple has been in the field of the operations and supply chain. The inventory management tactics developed by Cook after joining Apple are the work of a genius where the company is able to make an impressively high turnaround ratio.
The Future is Zero Inventory Model

In the zero Inventory system, product or the stock is efficiently flowed back into the supply chain by the retailer where they can see that the demands are low and does not want the risk or cost of holding inventory. This may seem beneficial to the cash flow but it is an equally risky way of working if viewed through the warehouse management perspective.The whole responsibility for the stock management is on now dependent on the manufacturer, who is now required to fulfill orders on an individual basis and ship them to the customer. Manufacturers now require forecasting for stock availability and get directly involved with Business to Customers orders. The pivot where they never wanted to involve themselves to the ordering process is now required to deal with the customers with the help of ordering portal to process orders and manage delivery to end user rather than sending to a warehouse. This whole process requires a change in assets tracking adopted by the manufacturers to label & package the products to maintain their distribution & warranty, wherein an inventory managed the system, manufacturers wouldn’t concern themselves with this.

Implementing Zero Inventory system

Zero Inventory is a system in which a company keeps zero or a very little inventory. They only order the absolute number of products according to the forecasted sales and receiving them when it is needed. The manufacturers also order their supplies and raw materials accordingly, to keep up with the demands in real-time.

Zero Inventory model is dependent on the Just-In-Time principle which uses short leads instead of huge inventories. The Just-In-Time approach is more effective, flexible, less expensive and significantly benefits the cash flow. With zero inventory approach, the business can take leverage from the benefit that no huge amount is invested on inventory, giving the companies time and resources (cash flow) to strategize new concepts or plans in case expected outcome was not met.

The sole idea is that supply chain needs to be 100% reliable, delivers exactly on time including the raw materials and components whenever they are required. For zero inventory to be implemented, goods have to be produced and moved on the basis of actual demand.
For the uninitiated, it may seem impractical but the current technology has made it more possible.

Machine Learning & Route Optimizations to the rescue

“Machine learning is the key to determine the volume, nature of demands with the help of forecasting to keep up with the supply chain and the ever-growing demands of today’s e-commerce.”

As mentioned earlier, to achieve zero inventory, supply chains need to be 100% reliable, demands need to be processed in real-time and forecasting needs to be generated. To ensure the process are optimized, companies need an interface with a comprehensive view of all their suppliers throughout the chains, tracking of insight data carefully.
Technologies such as machine learning play a vital role in ensuring that an effective cost reducing zero inventory system is implemented. Traditional Warehouse Management System have their strengths in planning inventory, but they do come with crippling shortcomings when pitted against the boom in e-commerce, which requires rapid processing of complicated orders while warehouse management systems only focus on daily, sequential waterfall style task assignment system.

Zero Inventory need to leverage the benefits of Machine Learning. The amount of data that is generated through the inventory management system and ordering system can be easily used to implement machine learning which will help companies to forecast the demands for upcoming weeks or even months.

Ways by which machine learning can improve Zero inventory model-

• With the help of machine learning companies can determine the shortcomings in their supply chains, demand forecasting, expected returns or warranty claims.
• Machine Learning grows and gets a better understanding of the situation with the help of input data that is present to analyze and can make near to 100% accurate forecasting which is very well required for Just-In-Time concept initiation.
• The core principle is Just-In-Time demand and supply, which required impeccable supply chain and 100% assured assets delivery and management which can be automated to manage all the assets in the most accurate manner by pre-computing all the variables of current situation along with the data of past similar situation to create modal which is impossibly accurate.

The above implementations can be a daunting task if done manually, but with the current of technology and the recent development in Machine Learning, Fleet Management Systems, and Route Optimization Software, companies can predict and analyze each order to have a very comprehensive view of their supply chain and order and dispatch exactly when needed.
Machine Learning combined with route optimization software is a powerful combination where one can analyze the past trends to make sure that the goods and processed in the most time-effective and accurate manner.

Are you optimizing your inventory and deliveries in a cost-effective manner?

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