<img src="https://secure.leadforensics.com/133892.png" alt="" style="display:none;">

In addition to managing fast-changing consumer demand, food and beverage manufacturers juggle sustainability requirements, product freshness, food waste and spoilage, delivery and shipping schedules, quality control and allergens.  

Compound these factors with the kind of unplanned setbacks seen in the past year or more and it’s easy to see how even the most minor change can have a significant impact on operations. 

Incorporating advanced analytics, using artificial intelligence and machine learning, is the way forward for the food and beverage industry.  

With AI and machine learning, food and beverage manufacturers can: 

  • Make smarter business decisions 
  • Gain consumer insights for more targeted marketing efforts 
  • Improve customer experience 
  • Enhance productivity 
  • Prevent human errors
  • Increase efficiency 
  • Save money 

 Artificial Intelligence vs. Machine Learning 

Artificial intelligence (AI) is the use of algorithms and advanced technology to solve problems instead of a human. Under this umbrella is machine learning, which uses a trained computer model to create dynamic data and make sense of patterns.  

Use Cases for AI and Machine Learning in the Food and Beverage Industry 

Food and beverage manufacturers can use advanced analytics at every stage of their supply chain, including: 

Real-time market and brand analysis 

When companies launch a new product or a variation on an existing product, this labor-intensive process traditionally requires deep market and consumer research. However, artificial intelligence can produce real-time analysis of market trends to make this process more efficient.  

For example, social media analytics can mitigate low responses to customer surveys. You can see which products people are talking about and what the positive or negative qualities associated with those products are.  

You can take that data and improve product development with more precise and reliable insights. 

  • Assess consumer views in real-time 
  • Identify high-value features for products/services 
  • Identify challenges for products/services 

Market trends forecasting 

Social media analytics enabled by AI can also be used for market trends forecasting. You can project patterns to better understand where the market is heading. Although AI tools can’t fully predict the future, they can help food and beverage manufacturers better understand what the future might hold. 

  • Identify shifting consumer interests and trends 
  • Spot market trends related to offerings or brand
  • Forecast waning or growing interest in product types 

Predictive maintenance  

Every part of every machine in every warehouse or production facility has a lifespan, which can be reduced because of poor maintenance. The space between when a machine begins to fail and when a human would start to notice an issue can be shortened, if not eliminated, with AI. Critical data, such as temperature or speed of operation, can be analyzed in real-time with the use of machine learning. The model can identify patterns and predict when a machine needs maintenance. For example, when X begins to happen, then this machine needs attention. Using predictive analysis, the technology can alert your analysts to when maintenance is required. Predictive maintenance then becomes preventative maintenance, instead of having to recover and restart from catastrophic failure. 

  • Streamline product delivery  
  • Reduce production downtime 
  • Reduce manufacturing errors 
  • Feed optimization algorithm 

Supply chain optimization 

Your supply chain has a direct impact on your ability to bring ideas from conception to consumers. Food and beverage manufacturers must consider a lot of factors in production and delivery, such as demand versus capacity or how much materials cost along the supply chain. Depending on your company’s requirements, constraints and restrictions, you can program those criteria into your AI algorithm, which will then find the best arrangement/solution. For example, if you’re considering sustainability, AI can find the best balance between energy usage, waste and cost.  

AI can also enable the most efficient production plans for supply chain optimization, which is especially useful when confronted with unexpected delays or shortages. It’s much easier to adapt to the unexpected when you’re backed by AI. Simply add new constraints, and the technology produces a new optimized plan for that situation. 

  • Maximize revenue subject to demand/production constraints 
  • Streamline product delivery processes 
  • Reduce or eliminate waste and human error 
  • Target delivery to predicted demand 

Rapid A/B testing 

AI and machine learning can make A/B testing measurements faster, more precise and not as costly as traditional efforts. AI-backed technology can also segment your customers. For example, they can identify groups with similar buying behaviors within a customer base. Companies can leverage these insights for marketing efforts and product launches. 

  • Analyze results from rapid prototyping
  • Assess sales change effects of different innovations or product features 
  • Narrowly target consumer demand 
  • Tighten development/test/feedback loops 

Time to market 

Advanced analytics can improve the efficiency of your overall business. Address workflow challenges and make more informed business decisions. 

  • React to market opportunities and challenges 
  • Build an agile development process 
  • Streamline approval process and overall workflow 
  • Automate processes  
  • Define marketplace and sample 
  • React to response from several, combined sources 

The Role of Humans in AI in the Food and Beverage Industry 

These tools, although powerful, aren’t magic. AI and machine learning cannot replace humans. The technology helps you focus on patterns and trends that the human eye might not catch – and enables analysts to dive deeper by providing greater detail and data-supported forecasts. AI and machine learning help teams do what they’re already doing – in a faster, more efficient way. 

Gathering data and insights is only one part of the process. The other is leveraging that information to make better, more informed business decisions at every step of the process. Working with a trusted partner can facilitate the integration of this technology into everyday use. At Columbus, we take our years’ worth of business and technological know-how, combine it with data strategies and help you drive growth and gain a competitive advantage in your market. 

For more on how AI is used in the food and beverage industry, watch our webinar on-demand. 

Discuss this post

Recommended posts