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Currently, the global population is expected to reach 8.6bn by 2030. By 2050, it’s been predicted that we’re going to need a 70% increase in calories to feed that population. Yet still, huge quantities of food are wasted across the supply chain through contamination by pests, severe weather, or because goods are left to spoil or be discarded, amongst other factors.
If things continue the way they are, this will soon become an increasingly unsustainable situation that stretches the capacity of the food industry to its limits. But what if there was a new way, based on intelligent ways of analysing data, that could start to solve these problems?
In the pest control industry, this is a possibility which we are actively pursuing right now.
Data is nothing new in pest control. It’s always been there in the form of various reports and documents. At Rentokil, for example, we have been gathering data for decades via thousands of our technicians who visit businesses, assess infestations and record their recommendations in reports.
The way that data is recorded is now changing. Our technicians are still visiting sites and recording information, but that information is now stored in myRentokil, a digital pest management reporting and analysis system that provides trend reporting, recommendations, interactive maps, charts and analytic tools that help support pest control measures and audits.
We are also generating data in new ways. Our Rentokil PestConnect solution, for example, is an ecosystem of connected traps that detect, capture or kill pests and alert our technicians when any activity has occurred.
With over 70,000 devices worldwide, the system helps to generate huge volumes of new data on pest behaviour in different food production environments and regions.
All pest activity detected by PestConnect devices is also recorded and uploaded to the secure myRentokil customer portal.
The most important thing to recognise is that generating data is not in itself a solution. It’s the action you take from it that counts.
Data must be used to analyse root causes, predict future infestations and generate insight that informs planning and implementation of preventative measures. When that happens, there is clear evidence that tangible benefits follow.
One such example comes from work that Rentokil has carried out in the agriculture sector, which also features a novel way of gathering data. We designed a bespoke drone fitted with thermal imaging technology to monitor a tomato plantation. The drone recorded critical data such as small changes in temperature to track and identity the movements of rodents.
This insight made it possible to then predict when rodents are likely to be present in the fields; target pest control measures more effectively; and ultimately prevent rodent hairs contaminating raw produce.
Another good example comes from the food retail sector, where we have partnered with a US supermarket chain to create predictive data models that evaluate a site for pest risk, create targeted solutions and even recommend changes in building design before a new store is built.
This kind of activity, we believe, is the future for a pest control industry that needs to evolve to become more informed by data insights, more proactive and more intelligent in the way that it helps to manage pests that impact food safety.
The food industry needs to do more than ever to mitigate risk and improve food safety. However, businesses in all parts of the food supply chain can take significant encouragement from the fact that technology is generating new data that could help.
What’s also clear though is that data is of limited long-term use without action. Data only becomes truly valuable when it is analysed – often also using other data sources – in order to create actionable insight that helps to drive tangible improvements in the management of pests and their impact on food safety.
More information on this intriguing subject can be found in our new whitepaper that focuses on the growing use of data insights in the food industry and how this data could be analysed to create actionable insights that are applicable across the global food supply chain, including agriculture, logistics and warehousing, food processing and food retail businesses.