How an Analytical Mindset and Data Storytelling Became Invaluable Skills
I’ll cut straight to the chase: the tidal waves of digitization that swept through the music industry in 1999 and the news industry 2006 are landing on every other sector of the world and remarkably few companies or knowledge workers are even remotely close to ready.
It’s not like there were no warnings.
In August of 2011, Marc Andreessen (a prominent venture capitalist and the guy who helped create the first internet browser) wrote a piece in the Wall Street Journal: Why software is eating the world.
Back then, Facebook was still a year away from its IPO, and plenty of industry analysts were skeptical of its ability to justify its expected $100 billion valuation.
But, as Andreessen wrote:
Too much of the debate is still around financial valuation, as opposed to the underlying intrinsic value of the best of Silicon Valley’s new companies. My own theory is that we are in the middle of a dramatic and broad technological and economic shift in which software companies are poised to take over large swathes of the economy.
More and more major businesses and industries are being run on software and delivered as online services—from movies to agriculture to national defense. Many of the winners are Silicon Valley-style entrepreneurial technology companies that are invading and overturning established industry structures.
Over the next 10 years, I expect many more industries to be disrupted by software, with new world-beating Silicon Valley companies doing the disruption in more cases than not.
And Andreessen was not even the first prominent voice to offer this exact warning.
Three months earlier, in May 2011, analysts at McKinsey Global Institute published a report predicting that big data would be the next frontier for innovation, competition, and productivity.
The authors (James Manyika, Michael Chui, Brad Brown, Jacques Bughin, Richard Dobbs, Charles Roxburgh, Angela Hung Byers) opened with a simple observation:
The amount of data in our world has been exploding, and analyzing large data sets—so-called big data—will become a key basis of competition, underpinning new waves of productivity growth, innovation, and consumer surplus…Leaders in every sector will have to grapple with the implications of big data, not just a few data-oriented managers.
What’s more, they wrote:
There will be a shortage of talent necessary for organizations to take advantage of big data. By 2018, the United States alone could face a shortage of…1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions.
Now, 6 years after these comments, it’s clear that far too few people were paying attention.
Facebook’s market cap is now close to $500 Billion – 5x the value it had when, before IPO, the International Business Times had said “there isn’t that much room to grow.”
And so, in December 2016 – slightly over 5 years after McKinsey’s original report — many of the same authors and a few new colleagues published a follow up: The Age of Analytics: competing in a data-driven world
Here are the three key takeaways relevant to this essay:
- Much as McKinsey’s team predicted in 2011, digitized data is sweeping across every corner of the human world. The way “business gets done” in every sector–government, energy, healthcare, retail, manufacturing – is already changing radically as a result. But unlike traditional retail companies – which have been dueling with Amazon for over a decade – most incumbents in industries like manufacturing, health care, insurance, etc have not reconfigured themselves to capitalize on this new reality. As a result…
- 20th Century incumbents in every sector face a serious risk of disruption at the hands of “digitally-native” companies which were born on the internet. Or, as the authors put it: “Data and analytics are changing the basis of competition…the network effects of digital platforms are creating a winner-take-most dynamic in some markets.”
- The biggest obstacles facing older companies are their own cultures. These companies–along with their leaders, their operating logic, and their IT infrastructure – were all forged long before quintillions of bytes of data started exploding into the world every day. Today, very few of these companies have the leadership, the processes, or the talent necessary to adapt to the new rules.
The authors summed this up well:
Adapting to an era of more data-driven decision making has not always proven to be a simple proposition for people or organizations. Many are struggling to develop talent, business processes, and organizational muscle to capture real value from analytics.
This is becoming a matter of urgency, since analytics prowess is increasingly the basis of industry competition, and the leaders are staking out large advantages.
Meanwhile, the technology itself is taking major leaps forward—and the next generation of technologies promises to be even more disruptive. Machine learning and deep learning capabilities have an enormous variety of applications that stretch deep into sectors of the economy that have largely stayed on the sidelines thus far.
So where does that leave us?
More to the point – where does that leave you?
In case the arguments above were not explicit enough, the exponential growth of digital data means that strong analytical mindsets and data storytelling skills are among the most valuable professional skills of the 21st century.
The logic here is simple: our species creates over 2.5 quintillion bytes of data every 24 hours. A quintillion means 18 zeros, so make it gigabytes and the human species is generating 2,500,000,000,000,000 gigabytes of data EVERY SINGLE DAY.
As if those numbers were not mind-boggling enough, those 2.5 quintillion bytes/day are JUST THE BEGINNING.
Because over the next years and decades, every forward-thinking nation and community in the world will be retrofitting the physical world (roads, buildings, industrial machinery, light fixtures, cars, streetlights, kid’s toys, coral reefs, jungles, livestock, etc) with internet-connected sensors.
When that trend (generally called “The Internet of Things”) reaches full steam, the amount of data all those connected “things” generates will make the volume of data we humans generate our smartphones, tablets, and laptops look like a small lizard facing off against King Kong with Godzilla standing on his shoulders.
So even if McKinsey’s 2011 prediction of a 1,500,000-person analytical talent shortfall by 2018 was aggressive (actual figures TBD), it is certainly directionally correct.
For these reasons, a company without access to the analytical skills to deal with big data is in serious danger.
Likewise, being a person with an analytical personality who HAS those skills positions you remarkably well for the world that’s already here today and–even more so–for a near-future where the tidal waves of digitization currently heading towards every sector of the economy have made their landfall.
In more concrete terms, with quintillions of bytes of data coming online every day and way, way more than that coming online in the coming years, analytical thinkers with the skills necessary to:
- Analyze massive quantities of data to uncover patterns and actionable insights…
- Communicate what they find in ways that other people relate to and understand…
- Make much better informed, data-driven decisions…
…will be in the excellent position of being highly in-demand AND extremely hard to find at the same time.
And as our ecomomics 101 textbooks love to remind us, something very specific happens when the demand for an asset far outstrips its total available supply: its price goes WAY up.
In other words, if you have strong analytical skills in a job market that is experiencing a shortfall of 1,500,000 million with analytical skills, you get hella paid.
So if you’re reading this and wondering if you would benefit from developing your analytical mindset (if you haven’t yet) or expanding and strengthening the analytical skills you already have, the answer is almost definitely yes. For those who are considering moving into a data analyst position, have a look at some data analyst job descriptions/samples to see if you would make a great fit in this ever-expanding field!
For help thinking like a data analyst, consider Springboard’s Data Analytics Career Track. You’ll learn both the technical and business thinking skills to get hired—job guaranteed!