On 23 February 2016 Giles Hindle (University of Hull) and I gave a presentation to the York and Humber OR Group (YHORG) at the Circle in Sheffield on our thoughts about OR practitioners and data scientists: where they overlap and where they might differ. In coming to some tentative conclusions we reflected on our experiences on an analytics project for food banks that we have recently completed. It is only fair to say that we grossly over-simplified and set up stereotypes (caricatures?) of OR practitioners and data scientists arriving at our points for discussion:
- Technical skills: OR practitioners need IT skills, top of the list being Python and R. They also need to know where to start and where to stop with IT work (e.g., when should it be handed over to an IT professional who knows how to deploy an operational system?).
- Heterogeneous data: OR practitioners need to work with different data types, e.g., text mining and video analysis, rather than only seeing the world in terms of quantitative data.
- Out of the comfort zone: OR practitioners need to get out of their comfort zone and engage with the business and business users in an agile way, rather than being in a specialist departmental niche with a traditional engineering mind set in which they provide solutions to the business (e.g., using small scale data in simulations).
- Embedded analytics: Analytics will become embedded in successful organizations with a greater emphasis on prescriptive (action-based) applications where action is then subject to an evidence base (e.g., randomized controlled trials).
- Transformation: Analytics is about organizational transformation – culture change is needed throughout the organisation if it is to become data-driven and embrace evidence-based management.
The last two points relate to the business analytics methodology that we are developing, BAM, which uses value mapping and soft systems to develop business questions that can be tackled through analytics. The full presentation is here: