Lessons Learned
At the time of this writing, most of the United States is still on lockdown from various state and local policies stemming from public health concerns. Like you, I'm somewhat affected by this action, but not nearly as much as most people. After all, my life as an independent brand strategist has allowed me to work from home for decades. Apparently, all those years of not going to the office has paid off. Most people aren't so lucky. They not only have no commute, they also no longer have a place to commute to.
I'm not here to argue the politics of a virus. I'm not even here to sway your views on how anyone, anywhere, should react to the situation. All I've ever done is simply observe and report, because if there's one thing I know, it's human behavior. It is the rock solid foundation of all brand strategy, so I've gotten really good at observing the things that are critical, yet overlooked by most folks, to wit:
As I've written here previously, I've watched as the rise of big data has surreptitiously allowed the concept of accountability to slowly slip over the side of the ship and sink to the bottom of the sea. Years ago, rational judgement determined more business decisions than data analysis. But when more data became available, it was far easier for bad decisions to be blamed on the data, rather than the person who made the call.
There's a lot of benefit and comfort to be had with reams of data -- along with a few important caveats:
1. The data you collect has to be reliable.
2. The data has to be collected in a reliable fashion.
3. The data has to be analyzed in a reliable fashion.
Back in the early computer days, the common aphorism was "Garbage in, garbage out," but you get the idea. You'd be amazed at how many -- if not most -- of my clients would throw down a 300 page document brimming with data that was almost as useless as it was expensive. And when I say expensive, I'm not just talking about what the research costs, but what its faulty findings cost those clients' businesses.
Bad decisions from bad data happens everywhere. So before you believe anything from anyone, look at the Big Three up there. Chances are you'll find the same things I have: Most "data studies" are nothing more than opinions expressed numerically, usually because the source presenting those numbers knows you'll never question the data. Nobody ever does.
Well, almost nobody.
I do. I always do. "Consider the source" is one of my favorite smirks. So here are a few data points you may want to keep in mind about this virus situation as you muse which mask goes best with the shoes you're wearing today:
1. You know those stats on virus death rates? Pretty scary, eh? Well, kind of. But not really, especially when you understand how the Center for Disease Control (CDC) collects data on Corona Virus death: As it happens, the CDC has mandated that all admissions to hospitals be classified as Covid-19, regardless of test results or symptoms. Even hospice patients dying of a previous, completely unassociated disease are being tagged as Covid-19 because doing so guarantees 100% payment of those cases, even though it falsely inflates the actual mortality rate. Skeptical? Good. Read their mandate here, at their site. Clearly, this is the "garbage in" part of the equation, inflating the mortality rate to the point where the "garbage out" inflates the true mortality rates far beyond any sense of reliability.
2. For the first month of the lockdown, ancillary data about automobile traffic was copiously collected and reported by media through photographs and videos of ghost towns and abandoned highways. Weeks later, as an increasingly angry public begins to reject the restrictions imposed on them, those same abandoned highways are at roughly 70% of pre-panic levels -- but none of that data is being collected or reported. Just because data isn't collected doesn't mean it doesn't exist. Which means this one is a double threat: badly collected and badly analyzed.
3. At this writing, 36% of all Corona virus cases are centered in New York, and not even the entire state. The vast majority of those cases are in Queens. One borough of New York City. In fact, 25% of the counties across the nation have 0% presence of any form of the virus. Which means America, basing its decisions on bad data, is applying a national solution to what is primarily a local problem.
I could go on and on about this, but you get the idea. I'm not here to sermonize, but I am here to point out how bad data leads to biased reporting which forms the basis for bad policy decisions with no accountability, which in turn leads to social panic and unnecessary economic hardship.
It also causes a real loss of your Constitutional liberties, and believe me, that's a whole lot more lethal than anything coming out of a sneeze.
I'm not here to argue the politics of a virus. I'm not even here to sway your views on how anyone, anywhere, should react to the situation. All I've ever done is simply observe and report, because if there's one thing I know, it's human behavior. It is the rock solid foundation of all brand strategy, so I've gotten really good at observing the things that are critical, yet overlooked by most folks, to wit:
As I've written here previously, I've watched as the rise of big data has surreptitiously allowed the concept of accountability to slowly slip over the side of the ship and sink to the bottom of the sea. Years ago, rational judgement determined more business decisions than data analysis. But when more data became available, it was far easier for bad decisions to be blamed on the data, rather than the person who made the call.
There's a lot of benefit and comfort to be had with reams of data -- along with a few important caveats:
1. The data you collect has to be reliable.
2. The data has to be collected in a reliable fashion.
3. The data has to be analyzed in a reliable fashion.
Back in the early computer days, the common aphorism was "Garbage in, garbage out," but you get the idea. You'd be amazed at how many -- if not most -- of my clients would throw down a 300 page document brimming with data that was almost as useless as it was expensive. And when I say expensive, I'm not just talking about what the research costs, but what its faulty findings cost those clients' businesses.
Bad decisions from bad data happens everywhere. So before you believe anything from anyone, look at the Big Three up there. Chances are you'll find the same things I have: Most "data studies" are nothing more than opinions expressed numerically, usually because the source presenting those numbers knows you'll never question the data. Nobody ever does.
Well, almost nobody.
I do. I always do. "Consider the source" is one of my favorite smirks. So here are a few data points you may want to keep in mind about this virus situation as you muse which mask goes best with the shoes you're wearing today:
1. You know those stats on virus death rates? Pretty scary, eh? Well, kind of. But not really, especially when you understand how the Center for Disease Control (CDC) collects data on Corona Virus death: As it happens, the CDC has mandated that all admissions to hospitals be classified as Covid-19, regardless of test results or symptoms. Even hospice patients dying of a previous, completely unassociated disease are being tagged as Covid-19 because doing so guarantees 100% payment of those cases, even though it falsely inflates the actual mortality rate. Skeptical? Good. Read their mandate here, at their site. Clearly, this is the "garbage in" part of the equation, inflating the mortality rate to the point where the "garbage out" inflates the true mortality rates far beyond any sense of reliability.
2. For the first month of the lockdown, ancillary data about automobile traffic was copiously collected and reported by media through photographs and videos of ghost towns and abandoned highways. Weeks later, as an increasingly angry public begins to reject the restrictions imposed on them, those same abandoned highways are at roughly 70% of pre-panic levels -- but none of that data is being collected or reported. Just because data isn't collected doesn't mean it doesn't exist. Which means this one is a double threat: badly collected and badly analyzed.
3. At this writing, 36% of all Corona virus cases are centered in New York, and not even the entire state. The vast majority of those cases are in Queens. One borough of New York City. In fact, 25% of the counties across the nation have 0% presence of any form of the virus. Which means America, basing its decisions on bad data, is applying a national solution to what is primarily a local problem.
I could go on and on about this, but you get the idea. I'm not here to sermonize, but I am here to point out how bad data leads to biased reporting which forms the basis for bad policy decisions with no accountability, which in turn leads to social panic and unnecessary economic hardship.
It also causes a real loss of your Constitutional liberties, and believe me, that's a whole lot more lethal than anything coming out of a sneeze.