By Jimmy Fitzgerald, Vice President, Asia-Pacific & Japan, ServiceNow
Dec. 13, 2016
According to ServiceNow's State of Work research organisations with 5,000 employees collectively across the United States could save $575 billion a year by automating unnecessary tasks and inefficiencies which would equal a 3.3 percent gain in the U.S. GDP, or approximately the combined annual profits of America's 50 largest public companies. Banks that have implemented RPA technology in Singapore have seen 50 to 70 per cent cost savings. Consulting firm Accenture has also found that implementing RPA technology can increase the volume and speed at which tasks are processed and up to two to five times faster.
Machine automation-such as moving from email and other unstructured process to automation-and machine learning will achieve greater productivity. Machines can be taught to understand things like tone or language based on text fragments. Today, you can take a fragment of text and a machine will tell you which language it is and whether the text is conveying happiness, sadness or anger. In customer service settings, these are both useful to know for routing and client management perspectives. Automation enabled by machine intelligence will personalise and speed the work tasks, boosting customer and employee satisfaction but most importantly boosting productivity.
When Machines Talk To Machines Good Things Happen
Humans are not yet ready to move to a pure robotic world. At the same, we are quantifying information like never before-we create 2.5 quintillion bytes of data every day. It is impossible for humans to manage all of this data and analyse all of the relationships between people, information and things. Future connected machines won't be like today's, which require the human interface. Instead, the Internet of Things will drive machines to talk to machines, with M2M connections reaching 27 billion by 2024. It will be the machines that decide if circumstances require human-to-human communication. The highest levels of collaboration and productivity will be achieved when machines understand activities, context and motivation and can make the appropriate decision. Companies that find the right balance of digital humanism will win.
Yes, machines will become faster, smarter and more proficient than us at many tasks. However, we are decades away from robots taking over, if ever. The future of work in 2017 and beyond will centre on using increasingly capable technologies to improve our productivity to the point where we can focus on the creative, value-add business issues that only humans can solve. What will you do when technology enables you to have 40 percent more time to innovate? It's time to start answering that question because the future of work is near.