Machine Learning Technology in the FMCG Landscape
We are living in an era where human beings have sophistically created machines that surpass human intelligence in multiple spheres. With the advent of the internet, we are more interconnected than ever. Technologies like Artificial Intelligence and Machine Learning are driving business growth with their intelligent automation and data-backed analysis. These technologies are still in the nascent stage of development but are still very capable of processing complex tasks. Before jumping over to the applications of machine learning in the FMCG sphere let’s understand both the terminologies at play here.
Understanding Machine Learning
Machine learning is a part of the bigger block that is popularly known as Artificial Intelligence (AI) technology. Machine learning is an application of AI that provides machines with the ability to learn things automatically using tons of data. It doesn’t involve explicit programming for the systems to learn and adapt. Machines learn from training data sets and apply insights to solve real-world problems. It’s more like providing machines with the ability to learn from their past mistakes.
The FMCG Industry
FMCG is the acronym given to Fast Moving Consumer Goods, the players in the FMCG industry sell products in high volumes. Some of the prominent characteristics of FMCG products include short shelf life, low price point, high inventory turnover, rapid consumption, etc. Examples include products like toiletries, cosmetics, packaged foods, household items, non-durable consumer goods, etc.
Machine learning tackling the FMCG challenges
The prominent characteristics of FMCG goods like high consumption, high inventory turnover, frequent purchase, etc. makes it a source of multiple data points. Managing data from such frequent transactions is nearly impossible using traditional data analytics systems. This is where machine learning technology saves the day. Let’s gain some contextual insights into how the application of Machine Learning technology helps the FMCG industry.
The volume game
All leading FMCG companies gather data at all stages of the products life cycle, from manufacturing to marketing and finally delivering goods. The amount of data generated can be overwhelming while analysing to gain consumer insights. This is where machine learning helps by reducing the chances of random error that would create biased conclusions about the study.
The inventory challenge
Figuring out the optimum equilibrium point can be challenging for the FMCG players in the industry. The short shelf lives of the products demand nothing less than perfection when it comes to inventory management. Oversupply and undersupply can cost a fortune for FMCG companies. The machine learning technology can help to optimise inventory and remove the over/undersupply challenge.
Manufacturing & Supply chain
One of the most significant uses of the machine learning technology for the FMCG sector comes in the form of optimising manufacturing and supply chain of products. The major challenges faced by FMCG companies are related to on-time delivery of goods and a product’s manufacturing timeline. Machine learning technology can be applied by leveraging historical data to solve these challenges.
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