I have been involved in many projects to improve product quality and reduce food complaint levels. One of the best tools for indicating where action for improvement needs to be applied is by analyzing your complaint data appropriately.
Whilst you can identify faults in your factory your customers are your 100% inspection service so respect their feedback. Whilst all of your customers will not complain when they find a problem so you will not capture all of your product faults you will however identify trends.
The first step is to collate all of your complaint data. Your data should then be categorized by product type, complaint type and size. Analyzing complaints by numbers alone will not give you a real picture of your performance. What you need to know is the proportion of complaints you are getting for each product. By far the most practical way of doing this is by using the sales volumes to calculate the proportion of complaints you get for each product. Some people use weight or volume such as complaints per ton or 1000 Liters. My preference is to use complaints per million units.
So, you analyze your complaint data product type, complaint type and size per million units. From this data, you can easily spot the worst performing product lines.
You should then analyze the results for the worst performing products:
Are they all the same size?
Are they produced on the same filling machine/production line?
Is it the same type of complaint?
The answers to these questions will generate your corrective action plans. If products with the highest complaint levels are all the same size it could be a particular problem with that size of packaging. If it is all the same type of complaint then why are some product lines worse than others? If product from one particular production line is generating the highest number of complaints per million units then there must be a reason for this, it needs investigating.
You should compare product performance and if there are significant differences you should ask the question why? At this point complaint trends are useful. For example, when I worked with fresh pasteurized milk sour complaints were higher in larger sized containers. The reason for this was not related to the quality of the product but the fact they took longer to consume and spent more time in and out of the fridge. Such products would be targeted for improvement projects as opposed to corrective action to remedy a problem area.
A few words of caution though, your analysis needs to take into consideration the comparative value of the products and the market. People are more likely to complain about higher value products. Also, some retail customers are much better at reporting complaints from customers to the extent that I used to get 10 times the complaint levels from one particular retailer compared to another for exactly the same product.
My last tip the more data you analyze the better. In the past I have analyzed 3 year’s worth of data. Why? It gives a year on year performance so you can see if things have been improving or deteriorating and also it shows any effects of seasonality. For example, it is not reasonable to compare summer levels of “off” complaints on a fresh product with winter levels. This is why in the Northern Hemisphere I would compare August complaint performance with the complaint levels for August in the previous year.
The complaint analyzer that I have developed based on over 30 years’ experience in the food industry is included in our Food Safety Management System Implementation Packages.