Isabelle, vice-president of customer loyalty and insight at a big bank, has led the development of a package of new products/services for clients, and a five-minute presentation to explain the offering. In a pilot test, where client managers randomly select walk-in customers and offer to go through the presentation, some agree to listen but others don’t have the time.
Isabelle, vice-president of customer loyalty and insight at a big bank, has led the development of a package of new products/services for clients, and a five-minute presentation to explain the offering. In a pilot test, where client managers randomly select walk-in customers and offer to go through the presentation, some agree to listen but others don’t have the time.
Recent studies indicate that the majority (60-80%) of advanced analytics/AI projects fail, often citing “management resistance and internal politics”. However, having reviewed/supervised hundreds of such projects around the world, our experience suggests that many projects are ill-conceived and fall victim to poor analyses and pre-launch planning.
Recent studies indicate that the majority (60-80%) of advanced analytics/AI projects fail, often citing “management resistance and internal politics”. However, having reviewed/supervised hundreds of such projects around the world, our experience suggests that many projects are ill-conceived and fall victim to poor analyses and pre-launch planning.
Recent studies indicate that the majority (60-80%) of advanced analytics/AI projects fail, often citing “management resistance and internal politics”. However, having reviewed/supervised hundreds of such projects around the world, our experience suggests that many projects are ill-conceived and fall victim to poor analyses and pre-launch planning.
Recent studies indicate that the majority (60-80%) of advanced analytics/AI projects fail, often citing “management resistance and internal politics”. However, having reviewed/supervised hundreds of such projects around the world, our experience suggests that many projects are ill-conceived and fall victim to poor analyses and pre-launch planning.
Recent studies indicate that the majority (60-80%) of advanced analytics/AI projects fail, often citing “management resistance and internal politics”. However, having reviewed/supervised hundreds of such projects around the world, our experience suggests that many projects are ill-conceived and fall victim to poor analyses and pre-launch planning.
Recent studies indicate that the majority (60-80%) of advanced analytics/AI projects fail, often citing “management resistance and internal politics”. However, having reviewed/supervised hundreds of such projects around the world, our experience suggests that many projects are ill-conceived and fall victim to poor analyses and pre-launch planning.
Recent studies indicate that the majority (60-80%) of advanced analytics/AI projects fail, often citing “management resistance and internal politics”. However, having reviewed/supervised hundreds of such projects around the world, our experience suggests that many projects are ill-conceived and fall victim to poor analyses and pre-launch planning.
Recent studies indicate that the majority (60-80%) of advanced analytics/AI projects fail, often citing “management resistance and internal politics”. However, having reviewed/supervised hundreds of such projects around the world, our experience suggests that many projects are ill-conceived and fall victim to poor analyses and pre-launch planning.
Recent studies indicate that the majority (60-80%) of advanced analytics/AI projects fail, often citing “management resistance and internal politics”. However, having reviewed/supervised hundreds of such projects around the world, our experience suggests that many projects are ill-conceived and fall victim to poor analyses and pre-launch planning.
Recent studies indicate that the majority (60-80%) of advanced analytics/AI projects fail, often citing “management resistance and internal politics”. However, having reviewed/supervised hundreds of such projects around the world, our experience suggests that many projects are ill-conceived and fall victim to poor analyses and pre-launch planning.
In an age where digital experiences hinge on fast, flawless visuals across countless devices, Cloudinary has emerged as a category-defining software-as-a-service (SaaS) solution for AI-driven image and video optimization. Founded in 2012, the company tackles a universal pain point: how to deliver the right image, perfectly formatted for every screen—without manual intervention.
In an age where digital experiences hinge on fast, flawless visuals across countless devices, Cloudinary has emerged as a category-defining software-as-a-service (SaaS) solution for AI-driven image and video optimization. Founded in 2012, the company tackles a universal pain point: how to deliver the right image, perfectly formatted for every screen—without manual intervention.
The credit card unit of a commercial bank needs to come up with a data-driven model to predict which credit customers will default.
The credit card unit of a commercial bank needs to come up with a data-driven model to predict which credit customers will default.
Kusha Ahmad is tasked with facilitating headcount reduction following the acquisition of the Societe Francaise de Biotechnologie (SFB) by Big American Pharmaceuticals (BAP), and the subsequent closure of the SFB office in Lyon, France. In accordance with regulations introduced in 2017, staff are entitled to a “rupture conventionnelle collective”.
Kusha Ahmad is tasked with facilitating headcount reduction following the acquisition of the Societe Francaise de Biotechnologie (SFB) by Big American Pharmaceuticals (BAP), and the subsequent closure of the SFB office in Lyon, France. In accordance with regulations introduced in 2017, staff are entitled to a “rupture conventionnelle collective”.
Analytics and Artificial Intelligence (AI), with specific applications to: Behavioral Operations; Strategic Behavior of Consumers and Firms; Pricing Analytics and Revenue Management; Customer Lifetime Value (CLV) and Loyalty Analytics; Innovative Operations; Sustainability; Remanufacturing; Green Technology Adoption; Applications of Analytics and AI in Business, Government, and Non-Profits; Ethics of AI; Biases of Analytical and Generative AI; AI agents
