Analytics & Business Intelligence
The Quest for a Killer KPI
Streamlined metrics can get people moving in the same direction and improve business performance.
Streamlined metrics can get people moving in the same direction and improve business performance.
Respondents to recent global surveys say their organizations are capturing substantial value from AI.
Scotiabank’s focus on AI projects likely to deliver value in a short time frame is paying off.
In this webinar, Ishit Vachhrajani of AWS offers expert advice on becoming a data-driven business.
David Kiron and François Candelon discuss the latest MIT SMR-BCG AI and business strategy report at Web Summit 2021.
Want to establish a genuinely data-driven organization? Read this Management Briefing to learn how.
Adapting entrepreneurial identity, adopting value-based selling, and advancing AI with an experimental approach.
DBS Bank’s CEO exemplifies how a willingness to experiment and even fail can help advance new technologies like AI.
Data science success strategies, developing simple “no-code” apps, and independent contractors’ outsider advantage.
Six strategies can help guide data science teams toward greater success in cross-unit projects.
In this webinar, speakers discuss the benefits and pitfalls of monitoring in-person and remote workers.
Addressing social capital in return-to-office plans, deploying AI to manage wealth, and reducing coordination complexity with microservices.
Many organizations have challenges with deploying AI. Wealth management is a clear exception.
Dramatic changes within the life sciences industry present unique opportunities to use AI.
Data science obstacles, concerns about data executive roles, and the virtual hiring process.
Only a third of data executives feel that their role is “successful and established.”
Leaders need to examine their core beliefs if they want to prosper in a COVID-19 world.
Encouraging employees to speak up, growing data and analytics talent, and nimbler supply chains.
A Q&A with AWS’s Ishit Vachhrajani on how leaders can generate excitement about and support for AI organization-wide.
Companies need to identify the type of talent they need in order to become data-driven.