Analytics Strategy

Survey report: What 1,000 business and data leaders think about using generative AI for analytics.

Effective governance enables KPIs to evolve, remain aligned with strategic goals, and gain workers’ and managers’ trust.

Join us to learn about strategies for great customer experiences in a variety of industries.

In this webinar, Ishit Vachhrajani of AWS offers expert advice on becoming a data-driven business.

Want to establish a genuinely data-driven organization? Read this Management Briefing to learn how.

Develop a “digital thread” that connects people, products, and processes internally and externally.

Organizations that struggle to gain payback from data science efforts can recognize and overcome five common obstacles.

Planning for the post-pandemic workplace, managing hybrid teams, and optimizing your organization for AI.

To deliver on the promise of AI, leaders must focus on improving their organization’s culture and decision-making capabilities.

In this webinar, Jeffrey D. Camm and Thomas H. Davenport explain how the COVID-19 pandemic has impacted the practice of data analytics.

Recommendation engines promise to revolutionize how customers buy and employees work.

A Q&A with AWS’s Ishit Vachhrajani on how leaders can generate excitement about and support for AI organization-wide.

A new MIT SMR Executive Guide offers managers and decision makers new insights, research, and strategies for leading a data-driven culture.

In an era of constant change, data and analytics teams must change rapidly to enable businesses to survive, never mind compete.

Companies can use an array of tactics to make sure that their data products inspire action — and create value.

Companies need to evolve and shift thinking around what it means to have a data-driven culture.

A Q&A with AWS’s Rahul Pathak on the advantages of transitioning your company to a data-driven enterprise.

Companies today are swimming in data — but how do we build a data strategy that creates value?

Preparing for AI’s next phase means prioritizing your talent pipeline and technology infrastructure.

Companies are beginning to reboot their machine learning and analytics, disrupted by the global pandemic.