Dear McKinsey, you can do better than this.02
When I saw the article from McKinsey ‘Straight Talk About Big Data’,
I got excited. McKinsey produces quality content and it positions itself as a thought leader. Not this time.
This article is full of truisms, clichés and at worst competing or not fully baked ideas.
Let’s begin from the end.
‘ … Science-fiction writer Arthur C. Clarke once said that “any sufficiently advanced technology is indistinguishable from magic.” We haven’t advanced to that level—yet. …’
It is perhaps magic to the writers now, however once they reach that level it will be normal and obvious.
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 modeling the change personally?
- Are we organizing and leading for analytics?
The questions would suggest that the CEO is out of touch and doesn’t know what’s happing within the organization. The proposed answers are incoherent and confusing.
As an example: to suggest to a 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.” is cute.
CEO is here to formulate clear vision and strategy; and empower people to execute on it. CEO is here to build a team, not to understand the limits of algorithmic models.
Indeed, the article suggests that the right people should be in the room and empowered (good), continues with direct intervention, and then the CEO should ask: “Was a conclusion A/B tested?”
Good CEO is not a micro-manager and expects that questions about A/B testing are handled by his team.
Another completely misleading information is in the diagram/infograph labeled ‘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 and only at near the top, it uses ‘Loops not lines’. Considering the fact that the advanced data analytics is new for most organizations, the whole process has to use ‘Loops not lines’.
Rather then wasting time on rebuking other parts of the article, I would suggest to the authors to read an article by their colleagues – http://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/making-data-analytics-work-for-you-instead-of-the-other-way-around
It provides far better description of the space and the suggested route.
I would simplify it even further – to start with ‘Big Data & Analy29tics’ you need the right question, vision and people. The rest is easy, even magical.