Analytics Consulting

Analytics Showcases

I worked for the Deloitte Analytics Institute from 2016 to 2020. In the first years, we created value for our clients by storytelling to describe business insights and visualizing showcases. Topics ranged from predictive maintenance, sentiment analysis, benchmarking, portfolio analysis, geospatial analytics, customer analytics, telematics, and anomaly detection to insight-driven organization optimization
Over the years, our clients and we became more mature with applied analytics. Larger companies established analytics competencies departments. Rather than developing fragmented use cases, we consulted them on how to prioritize use cases and how they could define their data strategy.
Internally, we build different capabilities, such as the data strategy team, legal engineers, backend engineers, cloud architects, and UX designers.

Analytics Strategy 2019/2020
Companies use or want to use data to create an advantage. But what kind of data should they use? And how do they want to use this data? We combined tried and tested methods to answer these questions and find the right strategy. We believe that this approach can help you prioritize your company’s use cases and design a relevant data strategy. The overall aim of the process was to combine qualitative and quantitative methods to enable C-level executives to understand the needs of the customers and consumers. Underlying the concept was assumed that customer needs and business impact must be analyzed to understand which projects are worth investing in.

Machine Learning Canvas + Customer segmentation + Mockup of data modelling tool

Evaluating a use case for machine learning solutions?

An excellent tool frame AI use case is the Machine Learning Canvas by Louis Dorard. It helps to build a holistic view in an easy-to-use format.

Team: Data strategy framework developed with Anna Ryzhova