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Automated fresh produce quality control savings
For stakeholders across the fresh fruit and vegetable value chain, quality control plays a mission-critical role in their organizations’ daily management. Organizations that can utilize next-gen technology to improve the quality control of their crop and create a consistent approach to testing fresh produce pre-sale are winning on three fronts, boosting enterprise profitability by a third.
Let’s look at each area in detail and translate these benefits into practical dollars and sense. Or, as our customers put it, directly before they sign up to our platform, “How much money is this actually going to save me?”
Rejections and Price Renegotiations
Looking to turn the entire approach to fresh fruit and vegetable quality control on its head. Currently, the process is heavily reliant on buyer interpretation. The supplier has little visibility or control over what happens to the produce after it has been shipped, and the buyer has full control over the price that they are willing to pay once the fruits and vegetables arrive. This is often based on subjective opinions into the quality of the shipment. This system allows companies to be effectively held hostage by the buyer, and has created a situation where ~5% of produce is completely rejected, and another 20% is subject to a price renegotiation.
Now for the numbers that impact your bottom line. Let’s illustrate a use case where the enterprise in question has a revenue of $100,000,000, with a net income margin of 3% each year. For a conservative estimate, let’s say that the 5% of rejected produce causes a 50% margin loss, and the 20% renegotiations average out to a 20% price decline overall. The enterprise is losing $6,500,000, more than 200% of its net income.
Next, let’s take an intelligent look at current QC processes. It’s likely that the way that your organization approaches quality control has not significantly changed in decades. Growers and pickers might manually check for size, compare fruits or vegetables according to a color palette using human judgement to make a final decision, and then write this information down using an Excel spreadsheet or maybe even a piece of paper. This information might then be used to create a report for a particular crop or year.
The average organization invests between 0.5%-1% of revenue in Quality Control testing, representing the labor cost of your inspector pool as well as existing IT systems to support the process. This number sounds small enough that outdated and manual processes have been allowed to continue without change. However, if we use our original use case, 0.5% represents an investment of $500,000 each year.
This cost would be understandable if the results of the testing and QC led to a decrease in the rejects and price renegotiations above. However, year on year, the numbers remain the same, due to ineffective, inefficient and subjective QC – all with a hefty price tag for your trouble.
This is the secondary, but perhaps even more vitally important impact of all of this manual Quality Control. Without a centralized system that stores your data, the process of buying and selling fruits and vegetables is simply repeated each time, with all of its errors and subjectivity intact. Your organization has no way to improve.
All around you, in every other business, AI and Big Data are making a difference to business potential, adding new revenue streams, and having a measurable impact on annual profits. In fresh produce, you’re still reaching for a notepad to guesstimate the value of a bunch of table grapes. Isn’t it time you caught up?
The True Value of an Automated Approach to Fresh Fruits and Vegetables Quality Control
Now let’s look at the same illustrative use case, but update the numbers with the help of the platform for automatic fresh produce quality control. The solution itself is simple. Firstly, a mobile app that uses computer vision technology to accurately identify the quality of produce from any camera-equipped device. Next, a management web application that allows managers to track and dynamically manage this information in real-time. Lastly, a data and analytics platform that provides insights into the trends behind your data and could help you make more profitable decisions.
If we could click our fingers and jump through any hoops necessary to roll this solution out widely across a company, we would expect to see a 15% reduction in price renegotiations and rejects, which in our example would lead to a saving of almost $1,000,000. As we know that these things take time, we’ve slashed that number down to 3%, which saves the business $195,000 –just by adapting 20% of operations in year one.
When it comes to testing, our automated platform takes seconds, generates instant reports, and largely eliminates the need for manual quality control. As a result, we believe that we can step into a business on day one, and save 50%, or in numbers that translate to end of year bonuses – $250,000. Again, let’s reduce that estimate to a more conservative 30%, and you’re still looking at a $150,000 saving in year one.
Altogether, in just these two areas, the enterprise has cut costs by $345,000 – more than 10% of its annual net income, and has accumulated more than 5x the ROI compared to traditional QC methods.