ESOMAR Fusion wrap up: day one and two

Day one and two of ESOMAR covered a lot around the world of data science, machine learning and data integration.

A really important issue was highlighted across the two days: there is a huge amount of data that we are not utilising, and we have limited capacity as to what we can process. Analytics and machine learning are here to stay and here are three clear themes that emerged:

1 / AI, Machine learning and big data are not a silver bullet:

AI, Big data and machine learning are not solutions that will magically make everything faster and better. Although they help us analyse huge amounts of data, we must not underestimate the time it will take to set-up and align with business objectives. We need to structure the data and understand what we need and these processes usually take time and a lot of human power to get right. Human input is key, there is a lot we don’t know still, so flexibility and willingness to fail are necessary.

2 / Business ambitions and purpose must be clear from the get-go:

Just because we have an incredible amount of data in our hands, it doesn’t mean we have all the answers. More than ever it is imperative to have a clear business objective in order to make big data and machines work hard and better for us.

3 / Communication is key:

As data and insights become central for organisations, departments are becoming increasingly fused with multidisciplinary teams. Processes, insights and results need to be easily digestible and tangible to the business parties involved. Effective communication and a common language are needed, an Insights Esperanto if you will.

Check back soon for my day 3 and 4 wrap up, which will be about qualitative methods and the (more) human side of research, stay tuned!

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