Cognitive Automation is the Immediate Future of Team Management
Cognitive Automation is the Immediate Future of Team Management
For all the anticipation of increased automation at work, commentators have spent a lot of energy trying to convince people it can only handle easy, repetitive processes. It’s time to finally confront the truth: Per the McKinsey Global Institute, today’s robots can handle up to a quarter of the average CEO’s job and 35% of management tasks.
While robotic process automation refers to using robots to speed up concrete processes, cognitive automation takes a more advanced version of the same underlying tool set and applies it to more conceptual, judgment-based tasks — what we now call “knowledge work.”
Using specific AI techniques that approximate the way our brains work, cognitive automation helps us make better decisions, complete tasks faster, and meet goals more easily — and it’s swiftly gaining traction.
KPMG predicts spending on intelligent automation will hit $ 232 billion by 2025, up from $ 12.4 billion in 2018.
Of course, we’re a long way off from managerial jobs being fully automated, but these findings indicate that automation can — and should — play a bigger role in how we lead the 21st-century workforce.
Where Cognitive Automation Fits Into the Workforce
At Exela Technologies, our managers wouldn’t be able to support our global workforce of more than 22,000 employees without the help of cognitive automation. Among other things, this technology enables us to obtain information from scattered sources, conduct deep analysis, and collaborate more easily.
We’re not the only ones, either. Deloitte found that increased reliance on cognitive automation in the insurance industry improved firms’ recruitment and development processes, removing much of the heavy-lifting that human managers once performed.
Business leadership has a lot to gain from cognitive automation. Here are some ways managers can take advantage of it.
1. Capture and dissect data.
Intelligent systems can gather more data than manual processes, then analyze that data more effectively to uncover trends, detect anomalies, and produce predictive models.
One sector where we see this technology emerging rapidly is healthcare. AI technology can now compare a patient’s medical history with established guidelines for common illnesses to help identify gaps in care and specific opportunities for improved treatment. When done by a human, this analysis could take hours. When done by a machine, it takes seconds.
Attended cognitive automation — where humans work alongside automated systems — enables great advances in accuracy and productivity.
Another area in the healthcare ecosystem where we see cognitive automation adding significant value is clinical documentation improvement and the prevention of fraud, waste, and abuse. On the provider side, intelligent automated data processing systems are capable of reviewing large volumes of healthcare records to identify potential information gaps and coding errors so providers are more likely to be paid in full and on time. On the payer side, cognitive automation can help flag anomalous transactions to detect potential fraud, waste, and abuse to limit overpayment.
At Exela, we build and deploy systems such as these to perform services for our healthcare industry partners. We also created similar tools that assist with other areas of our business. As part of the sales lead generation process in our legal arm, for instance.
We monitor federal and state court activity for business opportunities, such as large class-action settlements. Given that there are tens of thousands of daily updates to case files, it’s nearly impossible for our employees to efficiently differentiate between the “good” and “bad” leads.
To address this, we developed an AI system that uses machine learning based on exposure to an initial sample set and iterative tuning using continuous feedback. The system detects “trigger events” from thousands of regular updates.
These trigger events are then classified, (e.g., complaint, dismissal, etc.), and the content summarized, it alerts stakeholders and integrates with our existing CRM systems to automatically log the newly acquired data.
Thanks to automation, much of the heavy-lifting is done long before a human enters the picture.
Within your own organization, you can use an automated data management system to compile, classify, and clearly display data from disparate sources. You can not only process vastly more data this way, but you’ll also gain a fuller understanding of current market conditions and historical trends as well as the trajectory of key indicators.
When you have smarter tools at your disposal, you can generate much better forecasting and develop a much clearer picture of circumstances that are most important to your business. Moreover, you can do so without investing so much time and energy into manual processes.
2. Regulate culture and improve convenience.
Per Deloitte, employees may respond negatively to the introduction of automation, and this holds true for other big changes affecting long-standing processes. Rather than allowing negative employee sentiment to fester, rely on automation tools to help you anticipate sentiment changes in real time so these developments can be addressed before they get out of hand.
One Kansas-based company is using smarter HR tools to glean more accurate information from employee survey responses.
By feeding these responses into AI-powered systems, leaders can learn far more about their workers’ perception of management and the primary reasons for those views.
Another important element of employee satisfaction is based on work amenities and convenience — and cognitive automation has a lot to offer here as well. For example, an employee might need to change her flight while on a business trip in order to attend an important last-minute meeting.
AI-powered tools that use natural language processing make it possible to quickly and easily rebook a flight, regardless of where in the world your employee is or what time of day the request is made.
Intelligent chat systems can also assist with day-to-day business workflows. Employees often need specific information to continue moving forward on a project. Rather than tracking down a manager or subject matter expert, you can engage an AI-powered chatbot to share information.
With no pause in regular work operations, this enables work tasks to continue without the need for a busy manager to drop what she is doing to get involved. This way, productivity and job satisfaction can both be increased.
3. Create and coordinate teams.
Cognitive automation tools can now optimize task management quite effectively. This is a valuable development, given that 70% of people across the globe telecommute at least one day a week, and a little over 10% of the U.S. workforce now works as independent contractors.
Managing across time zones adds another layer of difficulty in ensuring, for example, that a project timeline is on schedule. But according to research from PwC, upcoming cognitive tools will be able to handle even the finest details of project scheduling and coordination.
By analyzing real-time data, machine learning systems will soon alert managers to issues with ongoing projects — before they occur.
That is, predictive AI will soon empower managers to step in and help their teams before team members even know they need assistance.
At Exela, we’ve seen how automation can improve collaboration across teams. Our employees live and work around the world and our teams are often comprised of members in many different locations. Additionally, we don’t always establish firm working groups, so employees have to be flexible about their team structures.
Collaboration can be a challenge when people are in different countries and when team members can’t communicate face to face. We use automation technology to aid us in our collaborative process.
These systems monitor changes to group workflows and automatically inform associated stakeholders:
- when a status changes
- when a workflow element has been completed
- when their attention is needed to resolve a bottleneck.
To implement this strategy at your company, feed your network of available workers and their respective expertise into an intelligent software system capable of creating optimal working groups.
Ensure that the system can connect members of those groups via communication networks, divide tasks among them, and assist with task handoffs and quality control notifications.
As a manager, these are functions that likely take up a large chunk of your time. However, with the right tools, you can put all those hours spent poring over productivity spreadsheets and timelines into developing your top talent and enhancing your team’s final output.
As these new capabilities make clear, automation is not limited to simple, repetitive processes or basic computation. We’re now at the beginning of the next stage of automation within which you will work side by side with AI to effectively lead dispersed teams across a host of challenging projects.
As management decisions at the highest and lowest levels begin to be supported by dynamic, flexible cognitive automation, employees from top to bottom will benefit from the change.
Image credit: Marvin-Meyer-unsplash
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