A Different Perspective on Becoming (Big) Data Driven

We recently reviewed the 2019 NewVantage Partners Big Data and AI Executive Survey results, and have some thoughts. This recent survey yields some interesting – but frankly not surprising – findings.

Kitty Kolding

In short, the 16-page study details how challenging it is for large corporations to transform themselves into being data-driven and data-savvy enough to capitalize on the tremendous opportunities that AI and big data offer:

71.7% of companies report they have yet to forge a data culture

53.1% of firms state they are not yet treating data as a business asset 

95% of executives cite factors like organizational alignment, agility and resistance to change as the primary reasons behind the slow adoption of transitioning to being a data-driven company

But before we get too riled up about the fairly dismal state of data-drivenness that these results portray, we should look more closely at who was surveyed and what this particular survey was getting at. 

The Survey Participants Are Very Narrow
Firstly, the survey participants were C-Suite executives at large or very large companies, with more than 77% of the respondents in the financial services category. Those two facts alone should cause readers of these results to give pause. Since when do large organizations do anything quickly and with harmonious organizational alignment? And when was the last time you read about large, heavily regulated financial services companies leading the way on any kind of innovation, technology adoption or internal change initiatives? 

Secondly, the questions focused on Big Data and AI, as well as machine learning, cloud computing and blockchain. Again, it’s hard to imagine that large financial services companies are going to be the ones scrambling around to rejigger their business operations to accommodate these very valuable but hugely complex realities, given the legacy systems, data and regulatory constraints within which they currently exist.

Brilliant Innovations are Missing
What this report doesn’t look at is small and mid-sized players that were conceived in the primordial soup of disruptive technologies that built or are reviving their entire companies based on some pretty brilliant uses for AI, machine learning and blockchain. 

This report suggests that American companies are falling behind and don’t get it. We suggest a modifier to that conclusion: large financial services companies in America don’t get it – yet. But companies outside that fairly narrow set of attributes get it in a big way, and are doing astonishing things. For example:

• In 2017 Jigsaw released its Perspective code to the public, giving developers open access to its interface, which can analyze sentences and filter out toxic language, protect against cyber threats and detect fake news
• AliveCor, which describes itself as an AI company disguised as a medical device company, recently released its machine-learning software called SmartRhythm, which continuously analyzes data from a smart watch’s built-in heart-rate sensor and accelerometer to spot unexpected patterns and health concerns
• Digital Reasoning, which now has joined the fight against sex trafficking by partnering with anti-human trafficking organization Thorn to create its Spotlight software, which sifts through internet ephemera and can point out instances of trafficking

Data vs. Big Data
Finally, the report also does not look at just progress toward become data-driven with regular old data – existing, non-fantastical data assets – which are entirely different than Big Data. Big Data, a term which is thrown around quite liberally and means something slightly different to a lot of people, is only a slice of the gigantically big universe of otherwise-sized data that is being intelligently used all over the world. Granted, Big Data is powerful and game changing and still untamed in many ways. But let’s also look at how companies – big and small – are using other data assets that are not defined as Big Data.

How well are they gathering, normalizing, visualizing and ingesting what they learn from their own data assets? How many are using BI platforms, analytics platforms and visualization tools to reap these rewards? How are they creating operational efficiencies? Democratizing access to all employees instead of just the analytical few? Creating new revenue opportunities and better insights into sales success and client requirements? 

A Broader Perspective
This is where the real story of transforming to data-drivenness is being told, and is what we need to study and learn from. Being data-driven doesn’t limit itself to being Big Data and AI driven, and even large organizations have made huge strides with their focus on non-Big Data. There is a huge, ongoing effort underway at companies across industries to make the most of the data they already have and can be using far more effectively, to better run their businesses, grow sales and increase margins. 

For questions or ideas, or to air data disagreements, contact me anytime at kitty@chrysalis.partners.