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Case Study: Aviva cuts data project lead time by nearly 98% with Dataiku

Aviva Case StudySourced & dated by Case Study Desk
Key facts · TL;DR
Company
Aviva
Industry
Financial Services
Challenge
Siloed, underpowered analytics
Headline result
98% reduction in deployment lead time

Key results

98%
Reduction in lead time for data project deployments
75%
Improvement in time-to-market
Idea to production
50%
Time saved on data analytics audit work
£10,000
Monthly cost savings
Customer feedback solution

The challenge

Aviva previously had no integrated analytics platform: data stores were siloed, analysis ran on underpowered on-premise hardware, and different parts of the organization used different technologies. Deployment on the legacy platform could take multiple weeks, and audit and customer-feedback analysis relied on time-consuming manual work.

The solution

Aviva standardized on the Dataiku workbench for connectivity, governance, and deployment, and applied it across use cases including a plug-and-play process-mining solution for its audit team, an algorithmic decision agent for marketing, and an ML-based customer-feedback solution using NLP. Usage grew from around 10 data scientists to roughly 250 data scientists and 2,000 data and AI consumers.

The most beneficial thing about Dataiku is having everything in one place, so you don't have to go from one program to another to another and have them work all at the same time. Dataiku takes away that hassle.

AK
Ayca Kandur
Data Scientist, Aviva

The results, in context

Aviva reports a nearly 98% reduction in deployment lead time and a 75% improvement in time-to-market from idea to production. Its audit analysts saw time spent cut by about 50%, and its customer-feedback solution reduced weekly report generation time by at least 50% while saving approximately £10,000 per month.

Products used

Dataiku DataikuDataiku Process MiningDataiku NLP