Traditionally, bakers used a combination of experience and intuition to oversee the baking process.
And yet experience alone isn’t enough to eliminate human error.
At a time of rising costs, reduced margins, and consumer volatility, modern bakeries must look to new methods to remain competitive.
From intuition to data-driven baking
Historically, bakers physically checked and measured every step of the baking process.
Ingredient quantities, temperature, humidity control, mixing and fermentation were all based on sight, touch and instinct.
This experience remains essential, but it isn’t sufficient to detect hidden changes in structure.
For example, these anomalies can indicate variations in yeast activity or oven performance, resulting in off-spec batches, additional costs and reduced profits.
By using analytic tools to assess baking data, bakers can constantly monitor the process and adjust proactively if they need to.
How baking analysers work
Predictive quality control systems, such as the C-Cell baking analyser, allow bakers to evaluate the internal cell structure of baked products.
The analyser is pre-programmed with more than 50 different parameters and a target profile, in accordance with user requirements.
A sample of the product is placed in the device, and a detailed image is produced. This is then compared against the target criteria.
Examples of the type of data points analysed:
· Thickness of cell wall and volumes
· Cell size and distribution
· Shape and visual appearance
· Sample texture and softness
Disparities between the target profile and baking data indicate where adjustments are required. These can be done immediately, thus avoiding defects and delays.
The database also checks across batches, so a comprehensive picture of the baking process is always available, and quality control is reliable and constant.
Key metrics for bakeries
All metrics should facilitate the same goal – achieving maximum operational efficiency and customer satisfaction, now and for the long term.
Key criteria must include the following:
· Identifying defects: Uneven crumb structure, collapsed or misshapen products, surface flaws, size and weight inconsistencies
· Discrepancies between batches: These may pinpoint problems with oven calibrations, issues with the quality of ingredients, or inconsistent staff procedures
· Cell parameters: Quantity and uniformity of cells, and thickness of cell walls indicate dough mixing problems or fermentation issues
· Texture defects and crumb structure: the right mouthfeel, softness and chewiness are essential for customer satisfaction
Access to reliable baking data throughout the production process allows necessary adjustments to be made proactively – the best way to maintain quality and reduce costs.
How proactive analytics leads to improved yield and waste reduction
Example 1: A bakery struggling with varying loaf sizes and periodic issues with tunnelling
Crumb data analysis across numerous batches reveals inconsistencies in mixing time, leading to problems with gluten development.
Mixing controls are adjusted to ensure consistent structure.
The likelihood of off-spec batches is significantly reduced, and cost savings improved accordingly.
Example 2: A cake manufacturer produces cakes that quickly go stale
As cakes go stale, they become less springy. Texture analysis indicates the level of springiness (resilience).
If this is insufficient, hydration and/or flour-to-fat ratios can be adjusted, or different preservatives can be used. This prevents off-spec batches and ensures high quality is maintained.
By using the correct ingredients in the right quantities, bakers prevent costly waste and improve yield.
Even small adjustments have substantial effects, especially in high-volume operations.
Impact on ROI
A baking analysis system such as C-Cell should be viewed as an investment rather than a cost.
Larger bakeries can recover their costs between one and two years.
These figures are approximate, but all businesses will start to see improvements in productivity and reduced waste very quickly.
Proactive monitoring and problem solving reduces downtime, while optimal use of ingredients produces consistent quality and reduces waste.
Fewer customer complaints ensure brand loyalty and protect future sales.
Barriers to adoption
Adopting new processes inevitably involves challenges, including:
· Initial costs: Smaller bakeries may be reluctant to invest
· Job concerns: Bakers may have concerns over job security
· Integration: Careful planning is needed to integrate a digital system with existing processes
· Data skills: Employees must learn to interpret baking data
Successful implementation depends on strong management support, in partnership with an experienced market leader such as C-Cell.
Employees must be clear on the benefits and appreciate that the system still needs their expertise to function correctly.
The future for baking analytics
Data analytics are transforming the baking industry.
Analyser systems provide exceptional, predictive quality control and consistent results. This leads to greater efficiency, superior products, a reduction in waste and an increase in profit margins.
Learn how C-Cell Baking Analysis can transform your business.