This is an area that is probably not discussed often enough but all you have to do is look at the jobs ads and about 80% of what you see out there are jobs doing analytics.  This does not take a rocket science to figure this out and sure other costs increase as well but as a country we are actually imageaddicted to analytics beyond the use with “common sense” entering the picture and someone has to pay for all of this and more than likely is reflected in rising premiums.  Think about this as insurers have created and sold wellness programs to employers and sure there’s some benefit there but is it being oversold?  Probably according to this article there’s not a big enough return on investment as employers were sold.

Again I’m not saying that wellness is bad by any means, but who pays for it and many insurers own a bunch of wellness companies as subsidiaries so insurers get money both ways with policy payments and companies paying for wellness programs and like everything else out there today it’s probably over sold and we have insurers wanting people to change their behaviors faster than education efforts allow, so we have analytics and reports that appear to drive this faster with saving “trillions” of dollars, you see that bunk all the time with new studies. I said not too long ago that insurers are basically software companies anymore and they do a lot of that and move money.  They still cherry pick, just different models and again when you look at all of this, I think it’s time to look at some models because some are not accurate and some lie.  If you have read here for the last few years, I point those out as they come up, calling many of the “Attacks of the Killer Algorithms”…

Banks Are Actually Just Software Companies and the Same Can Pretty Much Be Said for Health Insurance Companies As Well-5 Unspoken Reasons Tech Projects Fail

Accuracy with analytics and actually having value is big deal and we see so many out there today seeing what sticks to the wall and that costs a lot of money to spend a lot of time on a model that may end up being just flat out “junk”.  It happens in banking too.  As a matter of fact if you read the link above I am commenting on this fact and the author of the original article is banker on Wall Street who will remain anonymous due to the content not being politically correct with his industry telling you the same thing.  It’s odd as myself being a consumer advocate seeing eye to eye with bankers who speak out.  As a matter of fact I wrote another post where I also agreed with a group of Australian bankers in the fact they too said half of all analytics investments will be a waste.  Think of it as they too invest in software and analytics and are probably looking inside their own shops and seeing their own waste, thus their comments.  If you want more on this scroll down to the footer of this blog and watch the 4 videos I curated, you’ll get the message. 

Half of Analytics Investments By Companies and Banks Will Be a Waste–What Do We Analyze with Big Data and Does It Have Value–Some Algo Fairies Would Do Better at Disneyland…

When value is not proven and models are written strictly for profit you have a lot of throwing it against the wall to see if it sticks and now employers sadly are finding too that what’s been thrown against the wall with ROI promises are just not there, no matter what the model says and all the analytics they pay for, the cost is just too much for all of this when it’s rolled out in premiums…again the banker in the post about software makes that point right off the bat that ROIs sold are a farce, his words not mine but I agree. 

As he points out it’s one of the unspoken areas that lead to failure being way oversold.  In addition we see it all the time in the news with analytics being used out of context and how it hurts consumers.  All that’s on that screen maybe flawed, so ask question is you think something is fishy as you might be right.  The link below has a great video included to where you hear big companies talking about “where can they find value” and how it relates to the Quants companies use and what can they do better, again the mention is there about “throwing against the wall to see if it sticks” when it comes to using big data.  The gal from T-Mobile hits the nail on the head in the video in saying “what we are doing is silly” as she found a lot of internal analytics the company was using to be “junk”. 

Big Data/Analytics If Used Out of Context and Without True Values Stand To Be A Huge Discriminatory Practice Against Consumers–More Honest Data Scientists Needed to Formulate Accuracy/Value To Keep Algo Duping For Profit Out of the Game

So keep this in mind when you look at one of the causes for insurance premiums to go up as you might be paying for a lot of analytical junk.  It’s out there and this example here with Blue Cross buying data about consumer purchasing to run analytics to see who might be buying clothes a size larger?  That’s their words and you can’t make that stuff up.   I had to laugh at that response myself.   Come on. 

Obesity and being over weight is such a visual issue anyway and in their claims a patient’s weight is in again a wasteimage here as they use such analytics way beyond where it needs to go and besides that they are probably analyzing where you buy your gas, what you buy at the drug store and who knows what else since they have it in house.  People that write queries in tech kind of have a “built in” brain process to do that as everyone looks for value and how they can make things better and that is a normal process with writing software.  Some of the processes do improve things and some are just matching data to dive off the cliff with predictive analytics to sell to someone that fall into the “junk” category to make a buck.  Again when you think of what you pay for insurance with policy dollars, this is a big contributing factor right here.  How much information do they “really” need…and with high visibility with being over weight and addressing with education, why do they need more…good questions and further implicates “data addiction”, looking for predictive Algo Fairies that we have to pay for. 

Insurance Companies Are Buying Up Consumer Spending Data-Time is Here to License and Tax the Data Sellers-As Insurers Sell Tons of Data, Gets Flawed Data When Data Buyers Uses Out of Context Too

So obviously between not being affordable and the amount of data analytics employers are being sold, the value is not there and thus more employers are dropping health insurance.  Certainly this is a different way of looking a this but it is the reality of non tangible analytics pushing the price of health insurance through the ceiling.  With the example above, you can see to where the “value” of these analytics fall right into the “junk” and “data addiction” areas and employers and consumers are getting stuck with higher policy rates so insurers can chase and throw things against the wall in the search for fictitious value to write modes that will create profits.  It’s a huge marketing effort on the part of insurers too and they sell it well.  It’s odd today that we end up investing so much in “junk” and “fictitious models” today that a lot of the accurate and good stuff gets over looked. 

If the models are not paying off with less expensive rates for the employers, well the insurers go back and create yet another model to run the numbers through and usually of course that requires some change with the employer to now recommend yet other projects or wellness programs as well.  Again remember many of the wellness programs are owned as subsidiaries of insurers too so they can generate money that way too.  I am not picking on wellness by any means but rather the “junk” marketing that is used to promote some of it.  If employers can’t afford or find value with health insurance with the methodologies being used today, sadly away it goes. BD

Moen Retirees to Lose Health Insurance January 1, 2014, Off To Medicare And Exchanges for Coverage

The State Health Access Data Assistance Center, an independent group that studies health care, found about 11 million American workers lost their employer-provided health insurance plans between 2000 and 2011. That’s a drop of 10 percentage points nationwide.

Ohio had the fourth biggest drop in the country, falling 13.7 percentage points.

Analysts blame the decline in employer-provided insurance on a combination of economic turmoil, ever-increasing health care costs and uncertainty about President Barack Obama’s Affordable Care Act, also known as Obamacare.

However, until health care costs stabilize, Matthews said, employer-sponsored insurance plans are unlikely to bounce back. He said companies tried for a while to cut costs through wellness programs or other tweaks to coverage, but costs kept rising.


Post a Comment

Google Analytics Alternative