In the last few days I had to call a friend out for sharing a couple of news stories that were fake. He’s a great guy, friendly and very intelligent but even he was caught out by Fake News. It can be so easy to fall for it as well. Being the great guy that he is, rather than have a go at me for calling him out he thanked me for the wake-up call and said he should have checked them out before sharing. That’s a great attitude to have in my opinion. It takes a strong mind and personality to admit to one’s mistakes and own them.
The thing is, I see these types of stories every single time I log on to Facebook, Twitter or Instagram. People sharing Fake News without even realising it. It does not take long to check the accuracy of a news item; maybe a minute or two. Sharing an item of Fake News only takes a second though, and the more sensationalist the item the faster it seems to spread. Once the Fake News reaches critical mass it becomes almost impossible to correct the narrative.
The most recent Fake News I spotted was the one about Anchor Butter being infected with HIV. I mean, it’s obviously fake. This sort of post has been going around for ages, it’s just the product that changes. A few bits of google-fu shows it’s complete rubbish. The following link to Snopes sums the whole case up quite well:
It’s worrying how many people will fall for any claim on the internet so long as it’s accompanied by a picture. I’ll give you a fun example from personal experience. Last December, just before Christmas, my girlfriend’s parents contacted me to help arrange for them to surprise her. We sneaked around for weeks back and forth sorting out the logistics. They told my girlfriend they were going to the mountains in Romania for a few days with friends when in reality they were flying to Manchester and then driving to Sheffield. As they were crossing the hills between Lancashire and Yorkshire they sent pictures to my girlfriend of the rolling hills and countryside with statements about how beautiful the Romanian countryside was. My girlfriend agreed, not realising she was actually looking at the British countryside. People generally believe what they are told. A few hours later when we were at dinner we all had a real laugh about this. There is a darker side to all this though, especially when people share photos of other people they have never met, with uncorroborated stories that they are a terrorist, wife beater or thief.
On a similar subject, it is amazing how many people fall for sensationalist headlines with statistics. I’ll give an example of some fictional headlines:
DEATHS BY PENGUIN UP 50% IN A YEAR
DEADLY PENGUINS KILL ONE MORE PERSON THAN LAST YEAR
PENGUINS KILL TWO PEOPLE LAST YEAR AND THREE PEOPLE THIS YEAR
All these headlines are reporting the same data but some sound more extreme. So, when you see headlines that alarmingly state that the murder rate has doubled in a year, it could mean that two people were murdered instead of one. This all sounds so obvious but we all fall into these traps. There are certain questions to be asked when it comes to dealing with statistics.
A few years ago I heard a story from a friend about a large business that reported massive problems with staff morale. On the annual colleague happiness survey, or whatever it was called, the results were summarised and fed up the ladder from store level, to area level and right up to the office of the CEO. On his desk was a report that slammed the way the business treated its employees. Focus groups were held and staff were invited to discuss their feelings about how they were treated with their line manager. In a confusing turn of events, many of these meetings produced a sense that the staff were actually pretty happy with how they were treated. The higher ups were baffled.
Sometime later, in a further follow up to these negative survey results, someone pointed out the simple reason why nothing positive had been reported in the employee surveys. The surveys had not given the opportunity for positive feedback and every question on the survey focused on negative aspects. If you don’t give your employees the chance to provide positive feedback, then they will not provide positive feedback.
All data can be useful but one has to know what data they are looking at. Let me give you an example again…
There is a business that has contracted out the design for an App for customers to interact with the business and complete transactions on that platform. The business is really keen to push forward the use of this App and sees it as a cash cow. Customers using the App will have better service, and it will free up staff from other channels of communication. The business generates a tracker for staff to track how many customers agree to download and use the App going forward. However, the App is only released for use with Apple and disregards Android. For the sake of the example, let’s assume the business has an equal number of Apple and Android users.
As customers contact the business to complete transactions, staff promote this App. They get some positive responses and 60% of Apple users download the App and use it. The Android users are also keen to use the App and roughly 60% of them would have used the App had it been available. The tracker that has been designed offers several possible outcomes that the staff can select. Unfortunately, there is not an option for “Customer would use if available on Android”. Instead, there are the following outcome options;
Initially, the staff complete the tracker with 60% of half of their customers answering as per the first option. The remaining 40% of half their customers (Apple users) and the other half of their customers (Android users) are recorded under option two.
Using some round numbers for simplicity let us assume the business has 100 Apple customers and 100 Android customers; 200 total. If the tracker was being completed as common sense would dictate there would be a 30% “buy in” on the new App.
60% of Apple users (100) state they will use the App. That’s 60 customers.
None of the Android customers can use the App. As such, 60 customers out of a possible 200 are saying they will use the App. 60/200 = 30%.
The CEO is not happy. The CEO wants at least a 45% “buy in” from the new App. No one bothers to tell the CEO about the fact it is going to be difficult when half the customer base is excluded. The easiest way to get to 45% is to fudge the figures.
Taking another look at the tracker, at line manager level it is decided that the first option can be hypothetical. Now you have 60% of both customers from Apple and Android agreeing that, should they be able to use the App, they would in fact use the App. The data is reported back to the CEO that 60% of customers are now “buying in” to the App. Senior management pat themselves on the back for their ability to motivate their staff to sell more Apps to their customers.
A short while later, further data comes out that the actual number of transactions on the App has remained steady. Senior management cannot understand this and to get feedback on why the App is not being used more frequently, they arrange for a notification to be sent to their customers through the App asking for feedback. Rather than looking at how many downloads the App actually has from the App store, they fall back on their own data (as it is cheaper than requesting data from their IT contractors) which shows 60% of customers (120 total) are (apparently) using the App. As with previous surveys, the business expects a 25% response rate to their request for feedback. As such, they expect 30 replies. They actually get 15. Feeling that the business is losing touch with the customer base, sweeping reforms are commissioned. Line managers are thrown out. Front line staff are warned that they need to engage with customers even more effectively. Pressure is applied across all employees. All this because someone designed a poor tracker that did not collect data in a useful manner.
Critic. Writer. Thinker. Observer. Creator of nowwelive.com.