Why Do I Need to Know About Cognitive Computing?
AI and machine learning are propelling the next generation of software. In fact, it’s not hard to envision a near future where these technologies, collectively known as cognitive computing, become “must-haves” in LOB applications.
AI and cognitive computing are new fields, and their definitions and boundaries are still in flux. However, the semantics are less important than the impact this technology will have on your organization. If you are tasked with supporting or purchasing an HCM solution, it’s worth looking ahead to see if it delivers cognitive computing, or if this functionality is on the product roadmap.
Artificial intelligence uses algorithm processing and massive data sets to uncover patterns and trends in data. The same can be said for cognitive computing, however cognitive systems focus on the way AI interfaces and assists us. It promises to help us both by arriving at data insights and by automating complex, time-consuming processes.
Here are a few ways that HCM systems could be transformed by cognitive computing:
Cognitive Computing and the Hiring Process
Businesses face a shortage of skilled workers, and the pressure to fill vacancies often leads to poor hiring decisions. And changing technologies makes it increasingly difficult for HR professionals to determine the right skill set and fit for a position. As a result, small businesses lose thousands on the wrong hire, and larger organizations lose millions.
Data-driven decision making for hiring isn’t a new concept, but cognitive computing offers new ways of helping recruiters make the right decisions for their organizations.
Existing AI technology can comb through thousands of applicants to identify the right person for the role. But a cognitive system could also identify relevant information that is missing from an application or resume, then directly reach out to ask for it from applicants. It could suggest the optimal platform to recruit applicants, and perform deeper analysis based on different roles, for example, parsing social media activity for customer facing roles, while looking at Github and forums for technical ones.
Cognitive Computing and Employee Onboarding
Getting new employees up to speed is always a frustration. Organizations have tried to creatively meet this challenge with solutions like intranet forums and video training. Recently, companies have begun deploying chatbots to answer questions from employees. However, chatbots function more like animated FAQ pages, using answer trees that require programming. It’s a good start, but chatbots aren’t able to develop and implement best practices based on the data they collect.
Cognitive computing could take new employee engagement a step further. For example, cognitive systems could predict and proactively address employee questions, provide onboarding services like device provisioning, or suggest training topics based on employee history.
Cognitive Computing and Performance Management
Conducting performance evaluations is one of the most unpleasant tasks for management. On top of this, poor performance management practices can pose a risk to an organization, by exposing them to lawsuits for unfair treatment of employees, or from self-destructive promotion practices (like those that helped destroy Enron.)
Cognitive systems could help by removing some level of bias from performance decisions to provide a better assessment of the true impact of an employee’s work. Often the value of an employee’s contribution can be difficult to gauge. For example, how do you credit the work of an engineer who keeps company databases up and running? Cognitive systems could also use streams of sociometric data from IoT devices like smart badges to better assess the interactions of employees in an organization. And they could also help predict optimal training or career paths for employees.
Employee retention is another pressing issue for organizations. At the very least, it costs one third of an employee’s annual salary to find a replacement. AI systems can parse employee metrics and sentiment analysis to predict which employees are most like to leave a position. They could help identify problems that cause employee turnover and suggest early stage interventions to prevent attrition.
Adapting and Learning
At heart, cognitive systems do more than process information — they also learn and adapt. Every data point collected by HR can be used to inform the next set of decisions. HR systems become the collective memory and set of best practices for an enterprise at every step, from an initial application through to yearly evaluations and beyond.