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Strategy & Thought Leadership

Dimensions of a Data-Driven Culture

In non-data-driven businesses, data may play a part in decision-making, but it doesn’t drive decisions. Instead, leaders may rely on intuition, mistake conventional wisdom for facts, and use confirmation bias. Data-driven businesses let data guide decisions, outcomes and strategies, even when the data goes against…

Embracing Data Governance

Data governance has often been looked upon as a necessary hedge against legal or compliance issues, which often means it is looked upon as a burden to most. We refer to this as Data Governance 1.0 (DG1.0). The pain of ineffective data governance on analytics…

Creating An Analytics Community Of Practice

A Community of Practice (CoP) enables individuals to come together to work towards a common goal. Here are just a few reasons a CoP is worth considering: To improve analytics activities within an organization by tapping into the energy and passion of individuals around topics,…

A Framework For Establishing A Self-Service Program

To enable the change in demand-side mindset, IIA recommends leveraging a framework focused on what we believe are the four elements you will need to address to find success with self-service initiatives. These four elements - Surface Assumptions, Segment Audience, Incentives for Initiatives, and Identify…

Prioritizing Analytics Efforts: A Framework

Analytics resources are scarce and the demands on those resources are ever increasing, so it’s critical to have a clear, transparent, and intentional method to source and execute the analytics projects that will secure business value and, as result, meet or exceed the expectations of…

Creating A Data Strategy

The growth of data itself, and more importantly the growth in the demand for better decision-making with data, means that a comprehensive data strategy is no longer a nice to have. You need a data strategy. It needs to address questions about how to improve…

Analytics Application Lifecycle Framework

An analytical application combines data and computationally-intensive logic – coded by machines or people – to produce a mechanism for predicting future states, or prescribing actions in the present, that are demonstrably valuable to a business beneficiary. An analytical application lifecycle model is a framework…

Six Organizing Models for Analytics Teams

Companies that think strategically about analytics achieve the biggest impact from analytics. It takes a lot more than technology and talent to make analytics work. For analytics programs to thrive and make a positive difference within your organization, it is essential to structure your analytics…

Analytics 4.0

Building on its predecessor, Analytics 4.0 marks a point when organizational culture allows for the embedding of finished-product advanced analytics into decision flows and operational business processes. IIA sees Analytics 4.0 – automated, embedded analytics – as a crucial phase in the evolution of advanced…