Points of View

The HFS ML Execution Guide

Dec 14, 2018

Building on our report, “How to avoid your looming machine learning crisis”, HFS presents an execution guide for getting started with ML.

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RPA’s ticking time bomb: enterprises and service providers must make RPA talent their top priority to avoid disaster

Dec 10, 2018

As enterprises scale their RPA initiatives, the market’s lack of deep expertise will become an ever-greater risk to RPA success.

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Learning from the Birds and the Bees: Start Looking at Swarm AI to Harness the Power of Human Insights and Opinions for Your Enterprise

Dec 10, 2018

Swarm AI is helping organizations make complex decisions that require tapping into the collective opinion of large groups of people.

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Exploring the Next Frontier Beyond OneOffice: HFS Research Agenda 2019

Dec 06, 2018

Our 2019 Research Agenda explores the breathtaking advancements in technology enabling the Digital OneOffice and leading to the creation of a Hyper-Connected Enterprise.

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Taking a Closer Look: Excerpts from Interviews with Sandy Khanna of BT Group

Dec 06, 2018

Here are excerpts from Steve Dunkerley's recent interviews with Sandy Khannah of BT Group.

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Make Digital Twins Be Your Enterprise’s New Best Friend in an IoT World

Dec 06, 2018

Digital twins could be the form of AI to give enterprises a competitive edge in an increasingly connected world of IoT devices.

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Smart Analytics Impacts Your Competitive Edge with Predictive OneOffice Capability

Dec 05, 2018

Survey-based report from 262 enterprise decision makers on their use of data and analytics as strategic assets

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How the NHS Could Save $650m Using RPA to Combat Complexity, Save Money, and Bring Admin Staff Back from the Edge

Nov 27, 2018

This POV looks why healthcare leaders should investigate robotic process automation (RPA), which battles complexity, digitizes broken workflows, reduces costs, and give professionals room to breathe.

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Get Ahead of Automated Machine Learning (AutoML) to Accelerate Your AI Roadmap

Nov 27, 2018

In this POV, we’ll explore the emergence of Automated Machine Learning (AutoML) which is making it much more feasible to use machine learning algorithms to develop machine learning algorithms.

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