The Future of Work

 The Future of Work


 By Kris Fitzgerald

Modern business operations have fundamentally changed over the last 100—and even the last 20— years.

Terms that were once buzzwords for a select few—like “automation,” “Internet of Things,” “machine learning” and “artificial intelligence” (AI)—have become cornerstones of the evolving business landscape. Today, executives must understand how to incorporate the latest technology into the everyday workforce, regardless of whether they lead a tech-focused organization.

All businesses now must play in the digital space to remain competitive, integrating information security, the customer experience and IoT to improve productivity and workflow processes. The next evolution to optimize the information technology (IT) experience for the company is properly leveraging data and business intelligence while also strategically leveraging automation.

Naturally, the first thing we envision when considering automation or AI is robots, and usually the scary ones designed to overthrow the human race. The good news is we are far from a hostile takeover. In reality, automation, AI and robotics will continue to make our jobs easier.

There are three main categories of automation solutions:

  1. Virtual agents automate person-to-machine interactions so we can work smarter together.
  2. Autonomics are rules- or algorithms-based solutions that require no human or robotic intervention.
  3. Robotic Process Automation (RPA) is composed of software robots or “bots” designed to automate and perform tasks that require access to multiple systems.

By leveraging automation solutions, businesses and workers can achieve more. Business intelligence and advanced analytics enable machine learning and autonomous bots to help humans make more informed decisions, work more efficiently and achieve better outcomes. All while giving the human worker additional time for activities the bots are unable to accomplish.

To deliver sustainable value and succeed with automation integration, consider the following guidelines:

Evaluate The Impact On People

This is the elephant in the room that has many worried. Automation can impact the number of employees a company needs, and some roles may be eliminated during implementation. However, consider shifting those personnel to other, more fulfilling roles that have a positive impact on the business.

Automation technologies supercharge the workforce. Focus on how automation can increase the value of each team member, as less manual activity means more time to perform high-level, cognitive analysis.

Additionally, increased adoption will create new roles around the development and management of automation technologies. Executives can create a workforce that thinks more strategically as opposed to simply completing repetitive tasks. Robots empower humans—they aren’t battling us.

Power Actions By Data And Intelligence

Businesses work smarter, not harder, when they have the right data and analysis to solve problems. Automation coupled with machine learning algorithms can become part of a virtuous improvement cycle, constantly analyzing interactions to improve performance and accuracy.

For example, consider using a virtual assistant in the customer support center. The virtual assistant can gather critical data from the customer using speech recognition and a database of knowledge, even analyzing the customer’s sentiment and responding with suggestions to address the issue. Having used automation to gather background information, the human agents are already well equipped the first time they speak to the customers. Furthermore, while the virtual agent gathers necessary information, human workers are available to speak with other customers.

The data collected will help solve customers’ problems more efficiently and provide analytics to streamline workflows. The assistants can also monitor agent calls to provide objective performance analyses for training purposes and KPI indicators.

Implement The Right Ecosystem

As mentioned, there are several types of automation solutions, and finding the right ecosystem to meet your business objectives is key. Too often, people start by looking for the best individual tool for each problem, but these different tools may have different approaches to modeling new process and identifying solutions. Rather than looking for individual tools for individual problems, savvy tech leaders look for entire ecosystems, or sets of tools that work together to improve the end-to-end process.

Aim to create a unified visualization system to manage all of the actors across a business process, including the live, virtual and robotic agents. And make sure to implement robust security. At a minimum, all virtual systems and robotic actors should be encrypted and tested regularly for vulnerabilities and compliance.

Understand The Business Impact

While incorporating automation can seem daunting in the boardroom and the break room, the business impact can’t be ignored.

Naturally, cost benefits are always top of mind, and the cases vary. In some cases, once the initial investment is made, a company will begin to save money as it operates more efficiently and reduces some overhead expenses. The ROI may not be immediate, but it will be significant in the long term. In other cases, the savings are so large that automation quickly becomes self-funding.

In many cases, the biggest business impact is the improved customer experience, which leads to greater client retention. Not only can machine learning identify new trends in customer data, but it can also analyze digital experience and purchase patterns. By leveraging this information, enterprises can work smarter and deliver new solutions that meet customer demands.

Enable The Full Life Cycle

Just as businesses progress through levels of maturity from seed to an enterprise, the life cycle of automation also evolves. Just a few years ago, automation technologies were based on macros and scripts assigned to specific tasks or procedures. There was no intelligent thinking or ability to process complex problems. Today we have a myriad of advanced machine learning algorithms integrated into the systems we work with, enabling us to be dramatically more productive.

It is critical for companies that integrate automation into the workforce to be flexible and dynamic enough to work through the life cycles of automation and make it a key component of their systems development life cycle.

We must shift our mindsets from “robots versus humans” to “robots with humans” as we work together to achieve business objectives.

Kris Fitzgerald is Chief Technology Officer of Dallas-based NTT DATA Services.


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