Analytics & Business Intelligence
The Anatomy of Effective KPIs
KPIs measuring customer satisfaction and/or customer loyalty aren’t good enough anymore.
KPIs measuring customer satisfaction and/or customer loyalty aren’t good enough anymore.
Technology leaders need to take a new approach to regain user trust.
MIT professor Munther Dahleh proposes a marketplace for data that bases the cost of data on the financial value it generates
Agile companies are assigning accountabilities for specific business outcomes to small teams.
MIT Sloan Management Review’s first annual cross-industry survey of senior executives in collaboration with Google offers insight into organizations’ use of key performance indicators in the digital era.
Are you on the path toward strong KPI alignment? Take this self-assessment to uncover challenges and opportunities based on your score.
Early adopters of artificial intelligence will divvy up a global profit pool valued at $1 trillion.
Retailers have new challenges in getting customers to accept different prices on different channels.
Innovation-focused adopters of AI are positioning themselves for growth, which tends to stimulate jobs.
Apps that encourage users to share contact information expose companies to a huge security liability.
As smart technologies embed deeper into human processes, a more powerful form of collaboration is emerging.
Using AI to create humanlike computers is a shortsighted goal.
The fundamental disruption introduced by AlphaZero’s hyperlearning in the chess world can teach business executives about AI.
Executive transparency better positions organizations for growth.
Deploying AI is very different from implementing standard software — and human input is essential.
Advances in inventory and sales analytics make it possible to deliver products both cheaply and quickly.
Join the co-authors of “Using Analytics to Improve Customer Engagement” and special guest Teddy Bekele as they show how analytical innovators are gathering and sharing data to build loyalty and keep customers.
Aspiring leaders need to harbor healthy skepticism of the digital technologies they champion.
Machine learning is susceptible to unintended biases that require careful planning to avoid.
Sports analytics leaders are now using data to understand fans as well as they know their players.