FMCG Industry Introduction
FMCG stands for Fast Moving Consumer Goods refers to organizations that provide products in large quantities. These products are generally inexpensive, the volumes sold are large and might usually have a short shelf life. Profits on specific products are small and large volumes are needed to have a suitable business. These characteristics offer's several challenges and also many opportunities.
We all know the fact, Knowledge is Power and Data Science is making it possible for FMCG companies to realize what truly makes their customers tick.
Across industries, companies are taking advantage of data resources and analytics abilities to lower expenses and target customers more efficiently than ever before. In the consumer goods industry, companies have begun to see how big data may be used to discover new visions that drive consumer goods business.
We believe that market analysis, operations excellence & analytics can't work in a silo for just about any large customer business. As the digital world is getting more complex, leadership teams start to be increasingly dependent on data and analytical techniques to guide actions and decisions.
Most FMCG companies are not lacking in data from a wide range of sources. What they do lack is the capability to generate actionable insights from this data to generate real economic value. Supermarket stores are increasingly accessing advanced methods to assess their customers´ customer journeys and determine to buy triggers that will drive investments and improve loyalty, typically at the cost of the FMCG models they stock.
Change has come quickly to the FMCG market during the last 5 years. Smaller and mid-sized FMCG producers have started to find their place in an industry driven by economic uncertainty, much more adaptable production techniques, extensive distribution options, and naturally more and more demanding people who have much more choice from ethical and niche FMCG brands.
The analytics capability is not only restricted to the MNC's along with Domestic IT companies and captive units of Banking companies. The broader Data Science domain name has transformed beyond simply supporting business functions Analytics has today emerged as a required capability across organizations, with organizations enhancing Data Science abilities that transcend the entire business model and operation value chain of the companies.
Analytics is not the purview of advertising, IT, and data-rich firms. Firms across types and sectors, which include Industrial and FMCG makers, are more and more adopting analytics and investing each capital and operational online resources in the Data Science domain to obtain a competitive edge in the market. Now every FMCG company understands that the company has abundant data that needs a revolutionary treatment.
Data science allows FMCG companies to ''fail quick and learn faster''. Managers or employees can use it to visualize patterns of causality and business value from different transactional and behavioral data solutions. These insights let businesses be relevant and responsive to consumer needs, which may be a genuine competitive advantage in a crowded customer market.
On every stage in its business process, from manufacturing to sales to delivery and marketing, any FMCG company faces several challenges in decision making. The only source that can be relied upon is the data and that's where Data Science comes into the picture.
An FMCG company can gather data in the form of customer market data, market analysis data, finance data, market research data, social media data, and a lot more. Even so, this data is frequently unstructured, scattered, noisy, and also not available in the same format. This might be challenging for a company to use this data and then create action products that not merely cater to the existing situation but also as a future plan.
Data Science and Machine Learning might be extremely helpful resources in this kind of situation. Optimizing data science or machine learning in the FMCG industry can assist small businesses in order to make use of data for developing revolutionary products, improve targeting, and to raise revenue per customer.
Be it a humble toothpaste, toiletries, staples, medicines, or even electronic items, all of us use Fast Moving Consumer Goods (FMCG) every day. In India, after Agriculture, IT, Telecom, and Healthcare, the FMCG sector provides the highest employment to more than three million people in the country. Major players in the FMCG sector are ITC, Hindustan Unilever, Amul, Coco-Cola India, half of them being in the household, and personal care. At every stage of this journey from manufacturing to delivery to marketing and sales, an FMCG company faces several challenges in decision making and the only resource that can be relied upon is data. From day one of inception, the company starts collecting data in the form of POS data, customer demographic data, market research data, promotional campaign data, finance data, Twitter data, Facebook data, weather data, and the list goes on. This data is often noisy, unstructured, scattered, and available in different formats.
With the help of advanced machine learning algorithms, the FMCG Company can merge all the data and bring structure to it, and therefore find better answers to various problems that plague their business.
With the help of Supply Chain Analytics, a supply chain manager can set up and maintain the most cost-effective supply chain that would result in OTIF (On Time In Full) deliveries.
A sales manager can forecast his sales more accurately with the help of Time Series concepts and recommend effective improvements in operations.
FMCG companies invest a large proportion of their funds in advertising. With the help of machine learning and predictive analytics, the brand manager of an FMCG company can efficiently utilize his marketing spend in the right mix of advertising and promotional channels, that would result in a high return on investment.
With the advent of social media, text mining can help FMCG companies understand the taste & purchase behavior of consumers and thus create better and timely marketing campaigns.