Fuelled by the rise of Artificial Intelligence, data moats have recently received a lot of attention as an essential lever of strategic competitiveness.

Two schools of thought have emerged around this topic:

• The first one (Ivy Nguyen, Jocelyn Goldstein et al.) argues that gathering a massive collection of unique and relevant data provides a substantial strategic advantage and defensive shield against the competition and cites companies like Google, Amazon, or Netflix as evidence of this.

• The second school of thought (Andreesen Horowitz et al.) contends that a massive and unique dataset is insufficient and that the corporate culture and business processes exploiting that dataset make the difference. Such methods and culture include the Go-to-market strategy, the branding approach, and the vertical or horizontal integration, to name a few.

Both sides have a point, and the truth (specific to each company and market segment) lies between these data-centric and process-centric views.

The following article attempts to bridge the gap between these two schools of thought by proposing four ways of turning a data moat into a real strategic advantage at the enterprise level. It is a great read.

https://bit.ly/3mCaqdw