Nayur Khan, partner, QuantumBlack, AI by McKinsey

What key skills or attributes do you consider have contributed to your success in this role? 

My combination of a people-first and engineering backgrounds has allowed me to have a hands-on approach to leading organisations to digital change. I have been fortunate throughout my career to have participated in all stages of the development lifecycle, from planning, designing, data modelling, data management, AI and application development. 

The knowledge accrued in these roles has set me up perfectly to understand what needs to happen at each of these stages and to communicate this effectively to those in top-level positions.

What level of data maturity do you typically encounter across your client base and what tends to hold this back? 

The data maturity of an organisation varies depending on the business itself, the sector, the size and its technical maturity. We find it can be a spectrum from those just using data for simple insights, all the way to fully data-driven companies. Many challenges hold back businesses, but the main issues include a lack of leadership buy-in, unclear investments, data quality, data availability, talent challenges, unclear incentives and inefficient ways of working between groups. 

Fundamentally, achieving data maturity takes time and cannot be addressed overnight. In many cases, organisational change is required, learning from what worked and what didn’t work. It is not for a single team to fix, nor a silver bullet technology but a combination of people, process, tech, and governance, tied to delivering clear business objectives.