Some big thoughts on big data
Is it just me, or are we making some big mistakes in how we talk about big data? This crossed my mind (yet again) as I read Straight Talk About Big Data.
The article starts with a suggestion for the CEO to get 5 questions answered from the executive team:
Do we have a value-driven analytics strategy?
Do we have the right ‘domain data’ to support our strategy?
Where are we in our journey?
Are we modelling the change personally?
Are we organizing and leading for analytics?
The questions would suggest that the CEO is out of touch. He doesn’t know what’s happening within the organization.
Worse, the proposed answers are incoherent and confusing.
As an example: there’s a suggestion that the CEO and the executive team to “become conversant with a jungle of new jargon and buzzwords (Hadoop, genetic algorithms, in-memory analytics, deep learning, and the like) and understand at a high level the limits of the various kinds of algorithmic models.”
That’s cute. But it’s not right.
How CEOs should think big about big data
The CEO is here to formulate a clear vision and strategy. Then, they have to empower people to execute on it. The CEO is here to build a team. They’re not there to understand the limits of algorithms.
The article suggests that the right people should be in the room and empowered. Good! But then it continues with a suggestion. The CEO should ask: “Was a conclusion A/B tested?”
Hold on. A good CEO is not a micro-manager. A CEO expects that questions about A/B testing are handled by his team. Or they should.
It gets worse. There’s misleading information in the infographic labelled ‘Data analytics should have a purpose, be grounded in the right foundation, and always be conducted with adoption in mind.’
It calls for building a strong foundation. But only near the top, it uses ‘Loops not lines’. But consider the fact that the advanced data analytics is new for most organizations. That means the whole process has to use ‘Loops not lines’.
A better way to think about big data
To end on a positive note, I did want to highlight another McKinsey article that seemed to get it right: about making data analytics work for you.
My own thoughts on big data and analytics? To start out, a CEO needs to ask the right questions.
Beyond that, you need a vision of what you might want to achieve with it. And finally, you need skilled people to carry out that vision, once big data (and the questions you’re asking) have illuminated a path forward.
The rest is easy, even magical.