A productive, efficient and smooth flowing supply chain can be the backbone of a successful business. An effective supply chain will allow you to be resourceful and reduce wastage, and one of best methods for achieving these goals is by accurately predicting demand.
While a business is smaller, it may be a simple matter of looking at historical data to determine future demand trends. However, this becomes much more difficult as the business grows and as business owners struggle to navigate changing market patterns and market fluctuations.
In the following article, we look at how machine learning can improve your supply chain. Moreover, we illustrate how machine learning can not only improve your supply chain but also improve the extent to which you are able to accurately predict future demand.
The Existing Situation
Many business owners are currently relying on outdated forecasting technology to predict future demand trends. However, these technologies are often based on historical data to predict demand trends, but historical data is no longer the only thing planners need to consider.
Demand is much less predictable than it used to be and can fluctuate on very short notice, causing havoc for inventory control and making historical data useless. This means that existing technologies are prone to making planners commit severe economic mistakes. This issue has arisen because consumers’ data is becoming increasingly complicated and accessible. This accessibility has obvious benefits for business owners, but it now means that predicting demand trends can be much less straightforward.
The Solution: Machine Learning
Since business owners now have to contend with increasingly unpredictable demand patterns, old technology will no longer suffice. Business owners and planners need technology that accounts for the current changes in the market as they happen, and which do so without the need for human interaction.
Machine learning provides the solution. Machine learning is a special type of technology that allows computer systems to learn useful things through different types of data. Over time, the computer builds up a model using multiple types of data to produce the most accurate predictions for demand.
Machine learning technology harnesses information about consumer needs through big data sources like social media, digital markets and other internet-based sites. This means that companies can use data signals from other sites which are generated by consumers to predict trends in demand and prepare their supply chain accordingly.
By enabling business owners and planners to accurately keep up with consumer demand, they will be able to ensure every step of their supply chain is equipped in time to deal with increases and decreases in demand.
This means that business owners can, for example, ensure that there are sufficient levels of stock in inventory for increased demand in particular products. This will ensure that, when the demand increases, the business will be prepared. Likewise, if there is a decrease in demand for any given item, planners can ensure that there is no obsolete stock or over-ordering that results in products going to waste.
Article by Melanie Chan in collaboration with our team of Unleashed Software inventory and business specialists. Melanie has been writing about inventory management for the past three years. When not writing about inventory management, you can find her eating her way through Auckland.