John Miller
In April 2022 Bee Culture I mused on the emergence of Analytics in beekeeping. Analytics is not new. Observant beekeepers have for thousands of years mused on the super organism, the beehive, and invested careers observing beehive and honey bee behavior. The tools now available, or soon to be available will not be revolutionary – but a big improvement in our practices, our business performance [profitability], and beekeeping is underway.
A few of the outfits occupying this Beehive Analytics space include HiveMind, Nectar, BeeHero, BroodMinder, Arnia, Apis Protect, osbeehives, Hivetracks and others. More outfits and software platforms exist. Others will emerge. Beewise, an Israel-based outfit with robotic hive care devices recently knocked down $80MM in the investor C round. The Capitalist economic system is messy. Some hive-management platforms will be gone in five years. Look at the emergence, and demise of computer manufacturers in the past 30 years. ‘Hardware is Hard’ is a well-worn technology term – that done right – produces the first $3 trillion-dollar company in history. Nearly all the above outfits [except Apple] have in-hive hardware devices linked in one way or another to software.
Beekeeping Analytics is slightly different.
With all the various parties working on the process there will be winners and losers. The thing to keep in mind though is the eventual outcome. Fragmentation is an economists-used term to describe how and who participate in market functions. Beekeeping suffers from perhaps the most fragmented business model in agriculture. Literally millions of beekeepers husband their hives with varying degrees of success. Big commercial outfits crash their outfits along with the single-hive hobbyist. We are fragmented, but in this beekeeping love affair together, right?
Now in use hive-management tools are much better than five years ago. This improvement is the product of another wonky term called Community Intelligence. We’re getting better at controlling for example, Ms. Varroa and her children with different, better materials than five years ago. The beekeeping community intelligence was focused on Ms. Varroa. We have only scratched the analytics surface in beekeeping.
Take for example the above-named outfits. All of them. Crucial to success in any beehive diagnostic device or program is this question: Why Would I Do That? Why invest a ton of money, and dedicate lots of brain cycles to understanding how this gizmo placed in your hive – will unalterably change your world?… if it doesn’t.
Community Intelligence might, in ways beekeeping might not yet see. All the gizmos and all the software summarize all the data collected. The customer receives a year-end, door-stop pile of data – that provides intimate knowledge of the past. This exasperates me. Our beekeeping and beehive data is in the rear-view mirror. I may be able to learn why my hive died with a post-mortem report. Does it inform the future?
Sort of. The rear-view report may rightly observe the deceased hive had too many diseases, vectored by a parasite, or maybe a fungus, or a bacteria; it might report the hive lost weight over a period of time – until the woodenware & three pounds of starved bees are all that remains. This is exasperating. These blinding flashes of the truth – all are looking back in time.
I’m tired of knowing too much about the past – tell me what will occur – when certain indicators trigger a change, a predictable – maybe even the precise moment or condition or set of conditions that will predict the hive future.
The above companies now harvest micro-troves of data. It is very likely the proprietary platforms used by each of the above… may turn out to use nearly universal tabulating and reporting platforms to document their gizmo’s performance.
Think of Wikipedia. It’s an open source of information. Contributors may comment or publish [vetted] data in support/scorn of a previously proven bit of history, or medicine or whatever, right? Open source information.
What could the above companies do to perhaps increase the value of micro-data troves?
Without compromising the customer relationship; without compromising their identity as a participant – what if millions of hive[s] data, accumulating to billions of data points, accumulated over time – went into an open source platform?
What if a bee research funding outfit hired a team of data miners to investigate; using computers to solve previously unsolvable questions. What if a predictive set of guidance emerged? What if we could knowledgably predict the optimum time to replace a queen?
What if we could know ahead of time if a hive will make or fail a pollination inspection?
What if we knew the individual hive and outfit wide optimal annual nutrition – months ahead of time? What if we could better husband our hives?
Analytics are in use from fisheries to tubers to everything above the ground. Some bee outfits will embrace the change. And I’m now thinking about a number; perhaps 30% of all commercial beekeepers who once ran their own outfit, or now do run an outfit, will die. Soon. These beekeepers are BC beekeepers, ‘Before Computers.’ We learned the art of beekeeping from a mentor, a parent, books [!], someone taught us beekeeping. Us 30%? – our centuries of accumulated observed behavior will die with us. Our successors embrace technology not because they want to; they must.
I’d say it’s a good time to stomp on the gas pedal of big analytic beekeeping data.
JRM
