Data Science Applications In The Food & Beverage Industry
The Food & Beverage Industry is one that is highly competitive and caters to a large market. This is precisely why it is extremely important for every F&B business to gain some sort of competitive edge in order to stand out. Thanks to the new age Data Science Solutions and Tools readily available, F&B businesses now can easily take advantage of technology to completely reshape and transform their organisation.
1. SHELF-LIFE PREDICTION
In the Food and Beverage industry, stock management can be a tricky task. Since most of the supplies are perishable products, over time, their quality characteristics will degrade. This is why understanding the factors that could affect a product’s shelf life (the time within which it can be safely utilised) can make or break a F&B business, depending on how the business takes action.
Using certain effective big data governance organization techniques, it is possible to sort through information that relates to the products that are being stored or used by organisations. Determining the shelf life of these foods ensures that only the freshest and safest ingredients are being served. Additionally, it also significantly cuts down on waste, saves time, saves money, and makes it easier to know the time at which a business needs to replenish its inventory and place orders to restock on the supplies.
Online food delivery services have made it easier for families to get food on a regular basis. Even if a F&B business does not specialize in food delivery, it is critical to verify that the food preparation times, and delivery packing are suitable for clients that utilise these services.
It can be better evaluated how the food delivery service is operating by utilising data analytics to collect information and data governance to ensure that the information is organized and accessible. Businesses can simply monitor and track orders to accurately provide projected delivery times to clients by deploying data analytic tools and processes.
Closely related to deliveries are distribution channels: It is not rare for a distributor to show up at a company without warning and demand a full truckload of food/beverage products. These unannounced deliveries make it impossible for the F&B firm to prepare the exact volume of goods to have ready at any given moment, in addition to causing a enormous workload for the employees and extended wait periods if numerous trucks arrive at the same time. Businesses may ensure they have the proper amount of goods ready on hand by developing a model that predicts when trucks are likely to arrive.
Using this, businesses can also supply logistics organizations with information such as the optimal time for trucks to arrive and projected wait times. A system like this can aid any F&B business that wants to ensure they have adequate stock on hand without having too much and efficiently distribute these products to purchasers/retailers.
A F&B business could be unknowingly wasting money on blind advertising campaigns that do not add to profit or growth if they do not make use of data analytics in the marketing process. It is critical to first define the target consumer, as well as the appropriate timeframes, platforms, and marketing tactics to reach them. A marketing analyst can use certain tools such as SEO Analytics, Lead Generation & Attribution, and Web Analytics help to create an effective marketing campaign by gathering data on:
-When are the food/beverage in demand?
-Where do the target customers spend the majority of their time?
-Which marketing platforms are appropriate for the product?
-What aspects influence the customers' purchasing decisions?
For example, it might be discovered that the ideal customer is a city inhabitant in their late thirties or early forties. It might also be found that the target customer spends a lot of time on social media and is more inclined to order food delivery than to dine out. This would provide the business with valuable insights that might lead it to develop a social media-heavy campaign to reach consumers in this criteria.
This way, prior to commencing the marketing campaign, data science tools will help choose when and how to contact the target clients, which will result in more successful advertising that interests and draws people.
4. COUNTERFEIT MODELING
F&B industry businesses must take special care to ensure that their products are genuine and ethically sourced, depending on the target market. Developing a means of "fingerprinting" goods samples to show their original source is useful for ensuring quality and preventing false labelling. Advanced data analytics can be used to distinguish between genuine and phoney products, such as confirming that a product is from a specific region or has a specific claimed composition.
To illustrate this, for example, depending on data on the trace element composition of the wines, it can be used to distinguish between Spanish Sparkling wines and Champagne wines. Champagne is a considerably more tightly regulated wine than Spanish Sparkling wines, with very stringent requirements to qualify as a Champagne, therefore data analytics can be beneficial in detecting counterfeits.
This entails coming up with parameters based on how far specific characteristics deviate from the acceptable model domain, as well as figuring out what the crucial boundaries are for a specific product to fall within the acceptable range.