Integration across disciplines and close collaboration enriches our work. It brings diverse lenses of analysis, it sparks new conversations and triggers various ways of working. We encourage ourselves to work more collaboratively and to go beyond the boundaries of our expertise and background. We have even – across our industry – given it several names: integrated approach, cross-disciplinary methodology, blended methods and Art & Science approach.
However, it seems that data analytics – given perhaps its very specialised nature – struggles to enjoy the privilege of integration that is offered to other disciplines, and in many cases, its function has been limited to generate outputs that researchers will then take away, interpret and integrate to the story that is being crafted in a report.
In view of that, we would like to share three points which will hopefully help us think differently about data analytics and data analysts, as well as perhaps dismantle some of the stereotypes and limitations associated with them.
Data analysts are creative creatures
Data analysis is a truly creative activity. It requires abstraction to represent complex and multi-dimensional phenomena into simple and comprehensive models, it requires imagination to explore multiple avenues to reach a solution, it requires curating to make sure results tell incisive and engaging stories to internal and external clients.
Analytics shouldn’t work in a vacuum
An outstanding analytical model can only be achieved when the team (including, of course, the data analyst!) work together across the whole project, collecting and analysing information, and decoding and understanding the context the data is immersed in. In very plain terms, an outstanding analytical model is 70% contextual understanding and 30% statistical equations.
Inspiration doesn’t come from data (at least for a data analyst)
What inspires a data analyst isn’t a database, the data itself or a statistical technique, but the joy of finding, building on and enriching what foundational and contextual insight has taught the team. There is nothing more rewarding than seeing how the collective vision built with the team is coming through the results we produce. It will inspire us to carry on exploring and weaving stories with numbers.
At Truth, we have created a framework that constantly reminds us the need of making data analytics an integral part of our projects, even in cases of qualitative research, as we can see strong ties between analytical and qualitative thinking. We have called it Data Semiotics™ and has become our primary framework to extract meaning and cultural significance from numbers.
Please contact us to find out more: info@truth.ms.