Why Being Objectively True Should Be Your First Focus In Business?
The Less Connected You Are To What Is Objectively True, The Less Likely It Is You Will Be Able To Make Valid Decisions
Before we delve right into the benefits of objective testing and what it is. Let’s look at one of the biggest frauds of the past decade:
Theranos was a privately held health technology company. On paper, it had a spectacular, groundbreaking new technology that used a wearable chip; this chip communicated with servers to realtime monitor your blood for a whole host of ailments, and, in equally splendid fashion; diagnose and treat you. The documentation at the time stated that it could monitor over 200 individual diseases and infections—some real groundbreaking technology.
There was so much excitement around this technology that in the years 2013 to 2014, Theranos was valued at almost 10 billion dollars.
Let’s put that into perspective: Save $100,000 (one hundred thousand dollars) a year, every year for 100,000 years (that’s right, one hundred thousand years), and you end up with 10 billion dollars in your bank.
It’s no small change.
10 billion that’s impressive, indeed at the time, there was mass fanfare around the founder; Elizabeth Holmes; a college drop out, that, at that period had an estimated worth of almost 4 billion.
Sounds spectacular, you have to agree… an almost 10 billion dollar business in medical science, all from a college drop out who didn’t have a Medical, Engineering nor Science-based background.
But there was one very fatal flaw; the data that was used to woo investors, and gain a seemingly, unlimited amount of funding; had not been robustly objectively tested. From some accounts, it had not been tested robustly at all.
Long story short, 2015 comes around, the company, after the data was tested, in an objective manner, by the FDA- is worth $0.
A very, hard, fall.
No doubt someone saw something in the original data. Still, it was what they wanted to see- cognitive bias, there looked to be no due diligence of the information, after all a wearable chip that could inject antibiotics only measuring a few mm in thickness, should have been ringing alarm bells. Objective data with robust interrogation would have removed most, if not all, investors from this snake oil, marketing scam.
But what is objective testing and how can one simple word wipe the value off a company comparable to an entire nations GDP?
To Be Objective
To be objective is to ensure you use real information points; data, to assure yourself you do not believe something to be true when it is not. It’s using the real, scientific process to prove, or disprove hypothesis’ and gain true clarity.
The gaining of these data sets to utilise in this objective testing has a name, its called experimentation. Experimentation is to gather the data to assess your hypothesis to ensure that you are either right or wrong.
Ok, that’s a mouthful I agree, let’s take it back a step.
Objective vs Subjective
If objective data- derived from testing- is using the information to conclude a hypothesis, then subjective is the opposite. It’s not entirely dumbfounding, it can, for example, user experience, or use someone’s expertise in certain areas to make a judgement. But it’s not using methodically based data to get to a conclusion. It’s using a subjective assessment, usually by a human, to assess a situation.
Let’s use an example that is quite close to my heart: In a past life, I was an NVH (noise vibration harshness) engineer for a (very) large prestigious automotive company. We had two types of assessment for ‘noises’ in the car (these noises could range from overall road-noise to particular noises, such as differential gear mesh whine). These noises could be either measured using test equipment (microphones and excitation equipment), or for a rough and ready assessment, a ‘trained’ engineer with ears like a dog could jump into a car and subjectively assess the vehicles sound based on a rating of 1–10. 1 being bad and 10 being good.
The objective data being the microphone and accelerometer setup, obviously generating data; the subjective, being an interpretation of the noise generated by the car and interpreted by the engineer (a human) basing his/ her assessment upon a baseline, that’s remembered mentally.
We were very, very good at this mental assessment. We had objective data to correlate that the assessments made were in the correct ballpark. However, regardless of the ‘expert’ view, it was still a subjective assessment.
Why Subjective Assessments Are Open To Error
What about if the engineer had been to an ACDC concert the night before a subjective assessment, and had tetanus, or (in my case) the engineer was an avid drummer and loved nothing more than to smash some cymbals within an inch of their life in an evening. Subjectively assessing something, therefore, could then drive some errors into the data. Different engineers had different ears; a whole host of external factors can alter subjective assessments.
The only way that you would be able to accurately determine the correct level of noise inside a vehicle would be to microphone many test vehicles up. Gain a benchmark that was deemed acceptable (from a customer expectation) and in a known standard way; test them methodically, in the same test environments using the same road conditions, in the same weather, with the same tyres, humidity and driving cycles, to gain the objective relevant data.
Applying This To Business
You may have been in a meeting with a senior manager or director, and he or she throws the BS bingo card phrase “Where is the data”, or “We are a data-driven company, I want to see the data”. To only receive data that was obtained subjectively, he/she is satisfied…
When really the question should be, where is the data, how was this data obtained, under what standardised test conditions were this data captured and, what secondary evidence do you have to validate the experiment where this data was generated?
It sounds simple, and in principle, it is, by using testing standards you can follow methodically derived testing specifications to produce test results that in theory are normalised, and the data generated is, well… standardised. You can compare the same components and processes side by side to get a real indication of their effectiveness.
So next time someone gives you data in business, ask the questions that a scientist would, explore the data, get deep into it. Ask how it was obtained, was it objectively obtained or subjectively. Look at the data sets, the data, does it look like an assessment made by a human, or does it look like an interpretation of raw data from an output of a robust experiment?
By asking yourself these simple but crucial questions, you will be able to look through the complexity of numbers and gain clarity by interrogation. Saving you, and your company the possibility of an embarrassing 10 billion-dollar failure.
We use objective data in our testing services for businesses in all areas of trade. Get in touch with us here to find out how we can help you. Add me on Linked In to discuss testing and importing items daily.