What are the benefits of using AI for food and beverage product formulation

Advanced analytics can be used by food and beverage producers at every point in their supply chain, including:

Real-time market and brand analysis

When a company launches a new product or a variation of an existing product, this painstaking process traditionally requires in-depth market and consumer research. However, artificial intelligence can make this process more efficient by generating real-time analysis of market trends.

For example, social media analytics can help reduce low response rates to customer surveys. You can see what products people are talking about and what positive or negative attributes are associated with them.

Leverage that data to improve product development with more accurate and reliable insights.

• Estimate user views in real time

• Identify high-value attributes of your product/service.

• Identify challenges for your product/service

Market trend forecast

AI-enabled social media analytics can also be used to predict market trends. You can predict patterns to better understand where the market is headed. AI technologies can aid in the better understanding of the future by food and beverage businesses, even though they are not able to fully foresee it.

• Identify changing consumer interests and trends

• Identify market trends related to your product or brand

• Assess whether interest in your product type is waning.

Predictive Management

The lifespan of any machine in any warehouse or production facility can be shortened if not properly maintained. The gap between when machines start to break down and when humans begin to identify problems could be narrowed if not eliminated by AI. Important data such as temperature and operating speed can be analysed in real time through machine learning. The model can detect patterns and predict when machines require maintenance. 

For example, if X starts happening, this system needs attention. This technology uses predictive analytics to alert analysts when maintenance is needed. Predictive maintenance then becomes preventive maintenance rather than repairing a catastrophic failure and starting over.

• Streamline product delivery

• Reduce product downtime

• Reduce manufacturing defects

• Feed Optimization Algorithm

Supply chain optimization

Your supply chain has a direct impact on your ability to get your ideas from concept to customer. Food and beverage manufacturers must consider a variety of factors, including demand and capacity for production and delivery, and the cost of ingredients in the supply chain. Based on your company's needs, constraints and limitations, you can program those criteria into an AI algorithm that finds the most suitable solution. For example, when considering sustainability, AI can find the optimal balance between energy consumption, waste, and cost.

AI also enables highly efficient production planning for supply chain optimization, which is especially useful when faced with unexpected delays or shortages. Adapting to unexpected situations is much easier with AI assistance. As you add new constraints, the technology creates a new plan optimised for that situation.

• Maximise profits based on demand/production constraints

• Streamline your product delivery process

• Reduce or eliminate waste and human error.

• Targeted delivery in line with expected demand

Quick A/B testing

AI and machine learning make A/B testing measurements faster, more accurate, and cheaper than traditional efforts. AI-based technologies can also segment customers. For example, you can identify groups within your customer base that exhibit similar purchasing behaviour. Businesses can use these insights in their marketing efforts and product launches.

• Analyse rapid prototyping results

• Estimate the impact of different innovations or product features on sales.

• Narrowly Target Consumer Demand

• Strengthening development/testing/feedback loops

Release time

Your company's overall efficiency can be increased with the use of advanced analytics.Solve workflow challenges and make more informed business decisions.

• Respond to market opportunities and challenges

• Create an agile development process

• Streamline approval processes and overall workflow

• Process Automation

• Market and model definition

• Respond to feedback from multiple combined sources

Read Also : AI Use Cases in Food and Beverages

Conclusion

Food and beverage companies recognize the abundant benefits of AI, but not knowing where to start prevents many manufacturers from fully leveraging this technology.

First, don't be afraid to ask for help. Inertia is paralysing. Coaching that provides insight and new perspectives that challenge initial assumptions and assumptions can help you get started and realise the value of AI faster. Put off perfection and avoid analysis paralysis. Instead of focusing on the 10% that you can’t get right, focus on the 90% that can provide meaningful data today.

Next, begin small by developing a pilot proof of concept or prototype.For example, start with packaging with information such as the number of items produced, disposed of, or reworked. This area is relatively simple and easy to visualise. Make decisions and take action using the data you have today. It gives you the passion and drive to expand into the next area.

Finally, list what kinds of investments your company has already made to make data more readily available today through IoT or other automated systems. Leverage that investment and build additional features to make this data more meaningful. You may need additional sensors or data to take your investment to the next level.