We recently caught up with Alistair Croll, Visiting
Executive at Harvard Business School as well as our Marketing Analytics &
Data Science Conference keynote speaker, to discuss the state of marketing
analytics and data science, and where it’s going in the future.
Today, Croll helps to accelerate startups, and works with
some of the world’s biggest companies on business model innovation. As an
entrepreneur, he co-founded Coradiant; the Year One Labs accelerator; and a many
other startups. Not to mention, he’s a sought-after speaker, and has launched
and chaired some of the world’s leading conferences on emerging technology,
including Startupfest, Strata, Cloud Connect, and Pandemon.io. Croll is also the
author of four books on technology and entrepreneurship, including the
best-selling Lean Analytics, which has been translated into eight languages.
What is the state of
the data science and analytics industry in 2017?
Croll: There is a realization that data itself doesn’t lead
to answers. This is really maturity: It’s asking the right question that’s
hard. Big data is replacing business intelligence, but most of it is still
being used to run reports and batch processes’rather than to find advantage or
At the same time, feeding the corpus of data into learning
algorithms holds promise. Those with the authority to do so are pointing
machine learning at their data seta to find correlations, then testing those
for causal relationships they can exploit.
What have been the
biggest changes data science and analytics since you started your career?
Croll: I’m not an analyst by trade. But the biggest change
is clear: once, we first defined the schema, then collected data. Now, we
collect the data, then define the schema.
In other words, “Collect first, ask questions
later.” This is a huge difference, but it has sort of snuck up on us. It
means we can iterate more, answering questions and adjusting our lines of
Have the influx of
social media and mobile made your job easier or harder?
Croll: More data sets mean more potential insights, but also
more spurious correlations. So it’s a two-edged sword.
How is data science
and analytics transforming every industry right now?
Croll: The simple, and somewhat terrifying, truth is that AI
gets unreasonably powerful, very quickly. Whether driving a car, or playing a
video game, or diagnosing a disease, or optimizing the design of an aircraft
part, algorithms are better than humans. They don’t get tired; they make fewer
mistakes; they don’t take breaks.
And what do we feed such algorithms? Data. There is no
industry that will not be changed by the ruthless efficiency of algorithms
advancing its digital frontiers.
Why is data science considered
the ‘sexiest job of the 21st century’?
Croll: Data science is the intersection of statistics,
critical thinking, and engineering. It requires a sense of narrative, and the
ability to build something. It’s that element of engineering that distinguishes
it from simple analytics, because it builds things that become products, or
processes. Rather than running a report, it improves the report’s results.
If big data is oil, data science is the refinery that makes
What is the biggest
challenge in data science and analytics today?
Croll: We are still, sadly, trying to replace opinions with
facts. My good friend Randy Smerik argues that there’s no such thing as big
data: An airline that knows you’re running late fails to update your hotel;
false positives about in credit card management.
His point is that while we have tremendous amounts of data,
we seldom apply them to significantly improve the business or the customer
experience because doing so means making fundamental changes to the organization,
job descriptions, customer policies, and so on.
Where do you see data
science and analytics moving in the next 5 years?
Croll: Democratization, with the help of smart agents.
Pundits have been saying that for a long time, but in the last couple of years
tools like Cortana, Google Now, Siri, and Alexa’as well as various chat
interfaces like Slack, Sophos, and Skype’are going mainstream.
I also think that insurers will put significant pressure on
companies to implement better analytics and algorithms because it will be too
risky to do otherwise. If the organization can know everything about itself all
the time, it will be expected to do so. “We didn’t know this was
happening” will no longer be an excuse. And consequently, algorithms that
can parse all of that data and reduce risk will be mandatory.
Data science and marketing analytics are transforming every
industry. There is a reason why it is being called the sexiest job of the 21st
century. Calling all professionals that want to harness analytics and data
science! Do you realize how critical you are to the future of your organization?
Learn more here: https://goo.gl/CbYosj
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