The data leadership series part Two

Choosing an
operating model

What is the Data Leadership Series?

Each month, with the help of data and analytics experts in the panel, we will guide you and your teams through a relevant data leadership topic – with practical advice that you can follow. 

What is this event about?

An operating model for enterprise data management refers to the structures and processes needed to efficiently manage and use data. Without one you may struggle with data quality issues that don’t get resolved and decisions that never get made, due to miscommunication between teams and a lack of ownership. You will learn about how to select the right operating model, the key structures to include and the steps to take to successfully make it a reality.

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Agenda

Approaching an operating model

Part 1 introduces the idea of a data operating model and the benefits it can bring, and considers how centralised, de-centralised and federated models suit organisations of different complexity and data maturity.

Understanding the core concepts

Part 2 describes the three main structures your operating model should include: the data structure defines how your data is organised, the organisational structure sets out roles and responsibilities, and the governance structure puts in place the processes.

Foundations for success

Part 3 discusses the practicalities of implementing a data operating model: how (and when) to get started, who to involve, what tools to consider, how to measure success – and importantly how to maintain a positive story throughout.

Speakers

Pete Youngs

Managing Partner, Ortecha

Sean Russell

Principal Consultant, Ortecha

Selena Wark

Head of Data & CRM, Mind

Read more

If your Data Strategy is the map, your Operating Model is the vehicle that will get you to your destination. Discover the guardrails, operating levels and accountabilities it should contain.

A Data Operating Model can be thought of as a series of models that address the different aspects that need to be defined. This is our view of the eight essential elements a good Data Op Model should have