Case Study
Case Study
Case Study
Data & AI Engineering
Data & AI Engineering
Data & AI Engineering
Strategy & Operating Model
Strategy & Operating Model
Strategy & Operating Model
Case Study
Data & AI Engineering
Strategy & Operating Model
Case Study  |  2 min

Data and Analytics Vision and Op Model

Published
June 9, 2020
Tags

CLIENT

Large Industry Regulator

ABOUT THE PROJECT

Established the business vision and op model for a more data driven organisation.

THE CHALLENGE

The Regulator was faced with needing to regulate a fast changing market which was being heavily disrupted by new digital channels products. Whilst there was a desire to use data to better regulate the market the organisation was struggling with making its data available to its people and then equipping them with the appropriate skills and tools to analyse this data.

THE ENFUSE APPROACH

We managed a ‘strategic capability’ initiative which was focused on building out the direction, op model and supporting capabilities for the organisation to be more data driven. Through utilising a range of research methods, we engaged analytics internal users and customers to understand the current usage of analytics. We articulated this in the form of personas, with each one representing different user archetypes.With the As Is understood, and archetypes defined, we worked with senior management to collaboratively define what type of analytics organisation the client wanted to be, looking at different industry trends and op model options for adoption. We then articulated this through a strategic report on the proposed strategy for how the client could change its structure and focus to better exploit data and be more data driven.

THE OUTCOMES

Agreed vision and strategy for the type of data driven organisation the client wanted to be. This influenced everything for org structure design to recruitment strategy and training.Persona groups agreed and in use for strategy setting and for tailoring data and analytics services.Increased senior support and buy-in for data and analytics across the organisation.Clarity on the data and analytics user base in the organisation, and the direction for how this mix was to evolve over the coming years.Agreement on the creation of a central analytics hub to promote analytics and support ‘spokes’ of highly advanced analytics users.

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