How data science and analytics changes the food industry

Data science and analytics is changing the food industry for the better. Whether this includes securing supplies to a city or ensuring food quality meets standards, the food industry has a lot of responsibilities.

Data science and analytics is changing the food industry for the better. Whether this includes securing supplies to a city or ensuring food quality meets standards, the food industry has a lot of responsibilities. Food is especially important for Australia, where over 65% of the produce is exported abroad. So, it makes sense to look at the technology that allows the industry to do its work efficiently and in less time.

What data science and analytics can do

Predicting shelf-life

Food has a shelf life, which causes it to change or expire over time. For example, wine gets stronger over time but fresh produce will expire. Managing food and drink with different shelf lives is a huge challenge for the industry because there are different procedures for each category. For example, the procedure for wine is very different compared to the procedure for dealing with expired produce. But by using data science and analytics, data engineers can predict the shelf life of produce giving the insight needed to take preemptive action to reduce the amount of produce wasted and, in the process, saving money and time.

Sentiment Analysis

Social media and review websites have allowed the food and beverage industry to do something that has proven very difficult to do in the past: sentiment analysis. Using NLP, organisations can analyse what people are putting up on social media to discover the patterns and trends that reveal the most popular foods and beverages of the season. It allows brands, restaurants and other organisations to know about the latest recipes that are popular, and adapt accordingly. The insight will help organisations be more responsive to consumer demand.

Better supply chain transparency

Consumers want the food industry to be more transparent. The leading firms of the multi-billion dollar beef industry realised this when they gathered for Beef Australia 2018, a convention that sees over 90,000 visitors. Consumers expect organisations to be more forthcoming with how the food was produced, how the livestock was treated and what chemicals were used in the food – these are just some questions citizens want to know.

Data science and analytics help build transparency within supply chains, so they can be more honest with their customers. Transparency also helps in solving problems and increasing efficiency in supply and logistics. For example, it will be easier to track contaminated food supplies to its storage location, reducing the chances of food-borne diseases.

Measuring critical quality attributes

The food and beverage industry measures the quality of its products using key attributes. These attributes can be a great asset in marketing – for example, the alcohol concentration in beer. However, conventional methods of measuring key attributes are time-consuming.

Sticking with the example of beer, the alcohol level is measured using a method called near-infrared spectroscopy. However, this method is time-consuming and holds up the production process. Data science and analytics allows organisations to explore other measurement methods that are faster and more cost-effective, like the Orthogonal Partial Least Squares (OPLS) which uses multiple regression models to measure alcohol content and colour.

Better health management

Data science and analytics allows organisations to protect food health and cross-contamination. Geographical data combined with satellite data and remote sensing technique allows data analysts to discover changes. This information combined with data on temperature, soil property and proximity to urban areas can predict which part of the farm will be infected with pathogens and take action before the produce is infected. Another excellent example is food inspectors when cities are short on them – data analytics can analyse historical data on 13 key variables to help pinpoint the riskiest establishments, making better use of limited food inspectors.

Data science and analytics to the rescue

Data analytics brings a positive development to different industries, including food and beverage which is great because the industry will face a lot of problems. With the global population growing every year, climate change and desertification of land, the industry will have many problems to overcome.

If they wish to devise unique solutions in an efficient, timely manner, they will need technology that can collect and interpret data in a meaningful way. Data science and analytics allows organisations to collect and analyse data to identify interesting patterns and trends. The technology can also be used to devise several creative solutions to problems plaguing the industry while bringing positive developments to food and beverage.

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