Case Study
Case Study
Case Study
Data & AI Engineering
Data & AI Engineering
Data & AI Engineering
Transformation Delivery & Change
Transformation Delivery & Change
Transformation Delivery & Change
Case Study
Data & AI Engineering
Transformation Delivery & Change
Case Study  |  2 min

Data and Analytics Delivery

Published
June 8, 2020
Tags

CLIENT

Large Industry Regulator

ABOUT THE PROJECT

Agile management for the delivery of new Data and Analytics platforms and solutions.

THE CHALLENGE

The client wanted to establish a new central analytics platform which made data easily available to authorised persons, and provided suitable tools and processing power for analytics purposes, making best use of the latest thinking in the world of data science and AI. Teams were not sure of their requirements but did know that they couldn’t wait around for the perfect platform to be built – the needed something now.

THE ENFUSE APPROACH

We introduced an Agile based delivery model (whilst retaining some of the waterfall governance) to allow the programme to deliver iteratively and have early releases. This posed challenges as the regulator was naturally risk adverse and had a culture of wanting senior sign-off on most deliverables before proceeding to the next stage.

We provided Agile coaching to get the right behaviours and mindset within the delivery team, and worked with the Programme Manager to set the right expectations among the Programme Board and other key stakeholders. We worked closely with the solution, security and enterprise architecture reps to be able to iteratively develop the solution in a way which minimised the risk of regret spend, whilst it gave users what they wanted in terms of early and quick releases.

THE OUTCOMES

The platform was able to have users utilising a central data store and core analytics tools within 3 months. Previous approaches would have likely meant a year. The platform had strong positive feedback and its early release meant that client departments didn’t need to go forward with purchasing other solutions as bridging gaps whilst the central platform was built. Our iterative approach also meant a 15% delivery saving as we were able to quickly pivot the scope when user needs became clearer, meaning we avoided notable design work which was no longer valid.

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