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Your production process and supply chain is a rich seam of raw data that could be giving you the insights you need to make impactful changes to your business. Predictive analytics and artificial intelligence (AI) have been benefiting the global food industry as a whole in recent years. And that quantitative approach to decision making can be adopted by individual producers, too. By analysing the data available to you, you can optimise your product, packaging, and manufacturing processes without the guesswork and wasted resources.

Benefits of data analysis

The insights that come from understanding your data influence a number of outcomes. Here are just a few possibilities.

  • Take better control of operational costs by responding to real-time demand
  • Spots trends and take proactive measures to avoid issues
  • Manage inventory better across business functions with shared visibility of reporting
  • Improved reaction times in the manufacturing process ensures compliance with changes to regulations
  • Avoid customer frustrations by monitoring more granular location or product related sales data
  • Improve ongoing operational expense by introducing product changes

10 Steps to continuous improvement

  1. Start with your baseline. Use what you have, even if it’s just Excel, to capture what’s happening in your production process now.
  2. Look objectively at what that data is telling you. Look for cost overruns, gaps in the data, and ingredient wastage. Uncover where you need to focus on improvement.
  3. Review your business intelligence tools. PowerBI and ThoughtSpot extend your analytics capabilities. 
  4. Establish your improvement strategy by prioritising targets while maintaining or exceeding product quality.
  5. SpecPage is specific to the food industry and allows you to design and modify your recipes, process and packaging faster while avoiding labeling mistakes and recalls.
  6. Start with a benchtop trial followed by a factory trial.
  7. A sensory trial will confirm whether recipe modifications will work as expected.
  8. Using the data from your trials, implement the change to your production process.
  9. Monitor your adjustment for at least 12 weeks.
  10. Optimisation is an ongoing process, so continue with your data-led approach to improvement.

Conclusion

Data is revolutionising our food industry by lifting efficiency, improving productivity in the back office of organisations, as well as assisting products to get to market faster and safer. The impact on supply chains is clear, but understanding your own data gives you the power to make strategic decisions that increase the profitability of your SKUs.

The challenge is learning how to design your business intelligence platforms and build data-driven tests into your product development process. You may already have a stage-gate process across your organisation or you can adopt the simple 8P model.

However, you decide to embed data analysis into your everyday processes. Be consistent about capturing and reviewing your data flows so you can mature the insights you have into your business and your marketplace.