What best describes the scope of your process automation program? Primary drivers for investment center around: - Improving operations (optimization and reducing process errors) - Enable workers to better serve customers Base: n105 manager level or above from operations groups, shared services, finance/accounting and other lines of business Source: A commissioned study conducted by Forrester Consulting on behalf of November 2017 Q14. What are the primary drivers for your investment in RPA? 68% 58% 43% 40% 34% 28% 15% 14% Improve the optimization of operations Reduce process errors Augment human intelligence to free up workers to focus on more strategic tasks To complete tasks for internal employees who can better support customers Lower costs by replacing humans performing low value tasks Reduce cycle time for revenue generation transactions Improve compliance with regulations / regulatory bodies according to the country the office is based Link RPA with chatbots and self-service support to raise customer self-service experiences 6. 6 2017 FORRESTER. RPA Definitions › Attended RPA is defined as: "Automation that interacts in real time with humans who initiate and control robot tasks, often embedding functions within apps., generally associated with front-office, agent-led activities." What are your organization's plans when it comes to digital workers for intelligence augmentation (IA)?
Self-driving cars are making headlines every day; the future being envisioned as a car that runs itself, maintains itself, sends alerts when help is needed, and prevents accidents. While opinions of a self-driving car vary from excitement about simplifying the daily commute to "no way would I ever put total control in the hands of a machine," the concept gives rise to thoughts about self-driving data centers. What would they look like and how would they change IT as we know it? Reports indicate that enterprises are losing $21.8 million per year on average in downtime and 87 percent expect this to increase1. For organizations that are trying to manage and optimize increasingly complex hybrid IT environments that span mainframe and multi-cloud infrastructures, could evolving to a self-driven data center provide the keys to driving smarter, faster IT operations and preventing downtime?
While there has been plenty of talk about how artificial intelligence (AI) will transform the workplace, so far the effects have been subtle and slow to reveal themselves, although the scale of the oncoming change is starting to become apparent. Machine learning, task automation and robotics are already widely used in business. These and other AI technologies are about to multiply, and we look at how organizations can best take advantage of them. The ability of computers to learn, rather than be programmed, how to carry out specific tasks puts a wide range of complex roles within reach of automation for the first time. While this fresh wave of automation is not yet widespread, today there are glimpses of how profoundly these new capabilities will change the nature of work: Amazon Go's cashierless supermarket where shoppers just grab what they want and leave, the thousands of Amazon Kiva robots that ferry goods to and fro in the retail giant's warehouses, and the pairing of AI and IoT sensors to carry out predictive maintenance on ThyssenKrupp elevators across the world.
Forrester Research just published The Top 10 Technology Trends To Watch: 2018 To 2020. Ten trends, which Forrester breaks into three phases of dawning, awareness, and acceptance, are setting the pace of technology-driven business change. In the dawning phase, a few innovators experiment with new technology-enabled business models and exploit emerging technologies. In the awareness phase, change agents leverage the accelerating returns of evolving technology to steal customers, improve the bottom line, and inflict massive impacts on industries. In the acceptance phase, surviving enterprises finally make the tough changes necessary to fight disruptors.