Data has become the hottest commodity of the digital world — and also its fiercest source of debate. Data can improve quality of life, bolster capitalism, and help combat natural disasters. On the other hand, many believe it can overwhelm businesses, eliminate personal privacy, and reduce human beings to statistics.
So where do we draw the line? How much data is enough, and can we even process everything we accumulate?
What is Data?
Data is just information, and information is everything: every action, movement, conversation, hesitation, and an infinite number of others. On some level, data is the fundamental building block of context. Without it there would be no why or because, and human productivity would cease.
But that’s not the argument. The fact that information powers human activity is indisputable. We are now treading new and murky waters, facing two particular questions: what information do we need, and how much?
Quality, Quantity, and Questions
Ongoing revelations about personal data have flooded newsrooms for most of 2018. From the Cambridge Analytica scandal to GDPR in Europe, the world has started asking companies what they’re doing with their data and why. In the vast majority of cases, freely given personal data is used to enhance the customer experience and has a net benefit for all involved.
Where individuals take issue is the quantity of information used and an uncertainty over whether it’s all necessary. Businesses are asking themselves the same questions: how much data do we need in order to optimize our performance? Data management in business extends far beyond personal customer data: revenue, seasonal performance, conversions, social activity — the list of data points is endless.
And that’s the problem. The rise of AI and machine learning means automated data analysis is incredibly powerful and software platforms can now produce reliable business insights. This, in turn, fuels strategic decision making and allows companies to flourish like never before.
We praise analytical tools for becoming more powerful. But why do we need so much power? Could it be that we, the users, are inundating analytics tools with too much data and forcing them to evolve exponentially just to keep up?
Time to Deploy the Data Doormen
Imagine you’re a company that produces organic fruit juices. You need a biology expert to guide your team through concocting new flavors, and release a job advert. The applicants are: a farmer, a psychology student, eleven football players, a biologist, a musician, and four squirrels.
Do you invite all of these candidates to interview? Of course not. You screen for relevant experience like previous jobs and training, and then construct a detailed application process which only qualified candidates will pass. It should be the same with data: just because you can process endless silos of disparate data doesn’t mean you should.
The key is to filter the data before it reaches analysis. If your data comes from asking questions, then build custom surveys which ask the right ones. If you use consumer activity data, then constantly reassess to see which data is eventually useful and which isn’t — and then be proactive about optimizing this input.
Do We Need Data…At All?
Again we’re left with the question: where do we draw the line? Some say that 75% of information is all you need to make a decision, but 75% of what? Steve Jobs, founder and former CEO of Apple, was famous for basing decisions on intuition. He said that zero market research went into designing the iPad and his tech products became the most sought-after in the world and redefined an entire industry.
It’s true that data can’t answer every question. At the end of the day, it’s a human being making the decisions. Data, gumption, intuition, bravery, desperation — every decision is a combination of far more than ones and zeros, and occasionally we need to be reminded of that.
Data Beyond Business
Let’s ignore business-driving metrics and personal data for a moment, and take a step back. In the bigger picture, can measuring, aggregating, and analyzing data bring a net benefit to civilization? The answer is a resounding yes.
When the Texas Advanced Computing Center uses its extensive analytical power to predict the movement of tropical storms, it can save lives. Big Data is being touted as a powerful tool to combat poverty in the developing world, and countless other societal and economical advancements are being enabled through intelligent data analysis.
In isolation, it’s clear that using data can have a transformative effect on almost anything. But we always come back to the same point: to get the best results, as much of the data as possible must be as relevant as possible. Even in an informational world, more does not always mean better.
What Can We Do?
There is no right answer to the question of “how much is data enough data?” If you have one, let us know. All we can do right now is place more emphasis on qualifying good data and filtering out everything irrelevant at the gate. At SoGoSurvey, we help you design bespoke surveys which fuel your business with the most relevant data possible – that’s one option.
If you’re already using data for your business, then do some internal auditing, ask the difficult questions, and see if you can optimize your input. Data hasn’t become the world’s most expensive commodity by accident. Our ability to leverage vast silos information is bringing countless benefits to society, business, and human well-being.
But many companies use so much data that they can’t see the wood for the trees; maybe the answer isn’t plowing even deeper into the forest, but taking a few steps back, and opting for the right route.