Data Discovery and Breaking Down Silos

Simone RobertsHead of Data and Analytics HubFoxtel

5 Impacts of Silos

Inefficient time use

Duplicated effort

Low credibility of data

Reliance of key point knowledge

Promotes individual success not corporate

Silos are often one of the first stages of Analytics Maturity growth

Davenport & Harris 2007 later developed by SAS

Analytics maturity models show the progressive development of use of data in organisations

3 reasons silos exist

Different priorities and success measures

Disparate hidden data

Culture and individual behaviours

*Dun & Bradstreet’s 2016 Enterprise Analytics Study

Only 38% of companies share data outside of their business units*

Recognising we’re all in it together

Common Goals and KPIs

Shared definitions and success measures

Data Stewards and a community

Connecting the Silos

Integration of data into a single source of truth

Dedicated Connectors (Data Hub)

Knowledge management tools

Making it available

Easy to use and access data

Visualisation of key insights and KPIs

Clear process for sharing

But what about data discovery?

3 ingredients to maximise insights

Innovate and Transform your data

Know the Value of your data

Apply Business Context

Start with the business questionApply Business Context

Businesses are not starving of data; they are starving of insights

Build foundational data and insights

Innovate and Transform your data

Raw Data

Meaningful Customer Metrics

Segments

Increased data sources

Value

Data product innovation using multiple sources will ultimately lead to exponential growth of insights

Avoid the Data SwampKnow the value of your data

Use a gated approach to progress data through the layers – not everything makes it through

Automated actions

Defined data and insights

Discovery Area

By bringing silos together things can be created you never imagined