Where Human Meets Technology – Cognitive Solutions in HRM

Where Human Meets Technology – Cognitive Solutions in HRM

For HR to have a strategic impact, cognitive computing technology can act as the enabler and can create unforeseen possibilities. With the efficient integration of cognitive computing with the human expertise cognitive solutions can improve HR decision making, augment expertise and transform the HR processes.

Recent research by Harvard Business Review Analytic Services finds that senior executives want a CHRO who is a strategic business partner and an HR organization that anticipates the talent capabilities required for a high-performance culture that achieves their business strategy and growth objectives. For HR to have a strategic impact, technology is the enabler and the systems are table stakes, says Dave Ulrich, Professor at Ross School of Business, University of Michigan and Partner at RBL Group.

Currently and going forward, CHROs need to increasingly understand the technology trends impacting people management. They need to prove the value of employee programs while ensuring they are not sucked into a black hole of overwhelming data. They have to be technologically savvy, with the ability to distinguish between value and fads and accurately anticipate the ROI (return on investment). This isn’t easy, especially given the rapid evolution in technology and its innumerable potential applications. This article talks about one such new technology called cognitive computing and its use in HR management solutions.

Cognitive Computing Defined

Interestingly, cognitive computing technology is inspired by human anatomy. We use our various senses as a means of gathering information to make decisions – we see a possible candidate at an interview and pass sub-conscious judgment on their fitment in our teams. We hear a question from a colleague and help them navigate through the company maze, based on our own past experience and learning. And so on.

A system that gathers information from multiple sources including video, audio, etc., learns from them, remembers and makes conclusions based on these inputs is a Cognitive Computing System. Cognitive computing systems have the following four defining characteristics:

They Understand: Cognitive systems can extract and process unstructured information in ways similar to humans. They understand language patterns and sensory inputs, including text, pictures, video and audio, and can comprehend, identify and extract contextual elements such as meaning, syntax, time, location, domain, task and goals. For example, a cognitive system can assess expressions via video interviews to identify emotions including whether a candidate is responding truthfully.

“Cognitive systems learn and improve through every data point, interaction and outcome, building a deep and
broad knowledge base that is always up-to-date. In the HR world, with a constant stream of changing policies and new regulations, this capability becomes critical.”

They Can Reason, Iteratively: Cognitive systems grasp underlying concepts, form hypothesis, and infer and extract ideas. They aid in defining a problem by asking questions or finding additional source inputs if a problem statement is ambiguous or incomplete. They “remember” previous interactions in a process and return information that is suitable for the specific application at that point in time. Consider the case of a manager who is looking to fill an internal role: A cognitive system could look at various data sources, including a candidate’s professional experience and previous performance, and then further analyze the candidate against the characteristics of other successful job holders to determine if he or she would be a strong fit for the organization.

They Learn and Adapt: System must learn as information changes, and as goals and requirements evolve, they must be engineered to feed on dynamic data in real time, or near real time. Cognitive systems learn and improve through every data point, interaction and outcome, building a deep and broad knowledge base that is always up-to-date. In the HR world, with a constant stream of changing policies and new regulations, this capability becomes critical.

They Interact: People can communicate and interact with cognitive systems using natural language and the systems must interact easily with users so that those users can define their needs comfortably. This feature single-handedly addresses a key concern of HR users that they are not ‘technologists’ since no specialized skills are required to query cognitive systems and derive insights.

So, Basically, It’s AI..Right?

Not quite. Artificial Intelligence is primarily concerned with enabling computers to solve complex problems. But it is about results, not specifically building machines or algorithms that can think as humans do. Systems that use cognitive computing harness machine learning and natural language processing, adapting based on the information they collect.

Cognitive computing is different from artificial intelligence in that it can learn and make suggestions using its knowledge base, but it doesn’t make the decisions for us. Cognitive systems are designed to solve problems the way humans solve problems, by thinking, reasoning and remembering.

The goal of artificial intelligence is to replace the need for human intervention and decision-making; cognitive computing’s role is described by IBM Watson CTO Rob High as “augmented intelligence”, giving suggestions for action, but leaving the decisions up to humans.

“Cognitive solutions are not intended to and will not replace human expertise or decision-making. Instead, they are designed to augment and aid the HR function with additional skill sets.”

So, cognitive computing is sort of a subset or member of the larger category of artificial intelligence. Let’s take an example. Imagine that both an AI and a cognitive system had to analyze a large number of applicants as potential candidates for an open position; in an artificial  intelligence system, the systems would have eliminated candidates and automatically provided the shortlisted candidates to the recruiter, whereas in cognitive computing, the system would provide information to help the recruiter decide.

Applying Cognitive Solutions Across The HR Continuum

So how does one apply these technology solutions in HR management? Are there any one or two specific areas where cognitive computing performs better or can be used more effectively? From the results of surveys on the experience of early adopters, there are four scenarios that comprise the “sweet spot” where cognitive solutions will have the most powerful impact, as listed below:

  • Complex Judgment When decisions are information-rich, requiring a wide variety of inputs from different data sources.
  • Highly Interactive Where a large number of users frequently interact, necessitating the interpretation and action on a variety of topics and in huge volumes.
  • Involves Varied Information Types With high volumes of unstructured data such as free-form text, images, videos and auditory cues, sensory data and so on.
  • Personal yet Global Needs When the outcome is expected to be customized and personalized to address the individual needs of a global and diverse workforce.

These scenarios operate through the entire life-cycle of human resource management, from core operations to strategic HR decisions such as employer branding, as shown in the graphic below:

Beyond Efficiency and Engagement: When Cognitive Technology Enables Real Inclusion

In a survey by the Human Resources Professional Association, researchers found that even when employers strive to be inclusive, they may subconsciously lean toward candidates who are most like them, or what they call “unconscious bias.” Another bias, language bias, has been discovered by a psychological tool called the Implicit Association Test (IAT) that shows that people’s subconscious word associations indicate bias. These biases find their way into job descriptions, as well as resume selections.

Technology inherently is free from bias. Decisions made by intelligent and cognitive solutions are based on data, patterns, statistics, rules and… ultimately… data. Algorithms can be designed to help employers identify and remove bias patterns in communication and include candidates who may have been screened out due to the human tendency.

From the Employees’ Perspective

Ultimately, technology is only as successful as its users make it be, through willing adoption. And in the case of cognitive HR systems one of the main users are the employees themselves. Understanding their point of view is critical for CHROs in the decision-making process. To determine the readiness of workers to engage with and derive insights from cognitive systems, the IBM Smarter Workforce Institute examined the responses of more than 8,600 employees to a series of typical HR-related scenarios. In each scenario, there was either a cognitive computing solution provided to support a decision, such as a mobile cognitive chatbot, or a more traditional source of information, for example, an e-mail exchange with a manager. The findings of this study indicate that the use of cognitive HR systems can have a positive impact on employees.

  • Employees make similar decisions regardless of source (cognitive or traditional). This suggests that they are able to glean appropriate information from cognitive systems.
  • Cognitive can offer informational advantages. When asked if they had sufficient information in the scenarios, respondents who received information from cognitive systems tended to answer “yes” more frequently than respondents given the traditional scenarios. This difference was especially pronounced for more complex decisions.
  • Cognitive is equally or more trustworthy in less personal situations. Whether respondents trusted the information being given varied by scenario. The findings suggest that for more complex and less personal decisions, information received from cognitive applications is equally or more trustworthy than information from traditional sources. However, in the more personally evaluative scenario (featuring feedback about the tone of voice), information from the traditional source was trusted more.

To Invest Or Not To Invest

One of the top questions that come to CHRO’s mind when evaluating any new technology – is this a fad or will it really work? According to a survey by IBM, a significant portion of HR executives viewed positively the role of cognitive HR solutions:

  • 46% consider that cognitive technology will transform their talent acquisition capability
  • 42% believe that cognitive technology will bring substantial operational efficiencies to talent acquisition
  • 49% of HR leaders believe that cognitive technology will transform their payroll and benefits administration
  • 39% report that HR processes are overly complex and will benefit from cognitive technology
  • 40% believe that cognitive technology is well suited to address the digital skill gap.

Cognitive solutions are not intended to and will not replace human expertise or decision-making. Instead, they are designed to augment and aid the HR function with additional skill sets.

It is about time that enterprises understand and appreciate the fact that cognitive solutions can fuel business growth, transform user experience and enhance employer brands, albeit with digital disruptions that require flexible and strategic CHROs.


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