- business analytics – liaising across the business, to translate the business problem into the appropriate types of data and analysis and provide clear insight
- data architecture and management – sourcing and manipulating datasets into a form for analysis, develop infrastructure from secure on premise solutions to deploying analytics on a private or public cloud
- data science and modelling – developing decision models, exploiting advanced analytical tools, spatial analysis, visualisation, statistical and machine learning techniques
- blending design research such as qualitative techniques, customer journey mapping, focus groups, and ethnography
- interpretation, application and recommendations – taking the analysis output, enabling you to fully understand and apply the insight, from strategic decision making to AI based process automation.
Best practice analytics always start with trying to answer a specific business question, such as ‘where in the process does the problem lie?’, or ‘what will happen if these trends continue?. These questions could be posed by management, staff, suppliers or customers who are grappling with what to do in a particular situation. Data analytics provides a robust evidence base for decision making.