In our previous blog, we talked about organizations reimagining employee experience to create a more engaged and productive workforce. With evolving technology, employees expect personalization in every aspect of their lives, including their experience at work. While smaller companies may find it easier to maintain an open and connected culture between their employees, HR, and the leadership team, it is hard to maintain such personalized relationships as businesses scale up.
Fortunately, modern-day organizations can leverage AI and machine learning to improve employee experience through digitization. Reduced duplication and avoiding repetitive tasks, and efficient employee touchpoints lead to honest, unbiased, and productive interactions. However, this is just the tip of the iceberg in the employee experience evolution. With the recent advances in data analytics and data management, the next step in employee experience would see AI shape the behavior of employees by harnessing the massive digital data generated by them in the course of their work – say, what they express during a meeting or their performance in an e-learning course or the feedback received during their annual appraisals.
The Evolution of Employee Experience – From Paper to AI
Today, companies are increasingly focusing on improving employee experience to improve their retention rates and productivity. But how we reached this stage in employee experience makes for an interesting study that can be divided into four key stages:
If we go back by about three decades or so, employee experience was mainly utility-based, and HR operated manually, depending entirely on paperwork to conduct employee interactions.
In this second stage, digitization was introduced for better management of information and employee records, that marginally improved employee satisfaction owing to lesser mistakes in data management.
Increasing competition made companies realize that their employees are key assets, and this led to the third stage, i.e., increased employee engagement. Here, automation was introduced to a larger extent, and data began to be used for improving productivity and creating a connected work environment. In fact, this is the stage that most organizations are experiencing today.
With AI already being leveraged by many organizations to improve productivity, the next stage of employee experience would see a futuristic platform that uses employee-generated data to modify employee behavior by sending nudges at pre-identified moments. We believe this can be realized only by integrating the data present in siloed and disparate employee record systems under one integrated platform, that can process and provide these personalized experiences.
At Zensar, this fourth stage forms the basis of our upcoming Humané platform that focuses on curating AI-enabled experiences based on psychographics. Such an experience aims to trigger behavioral changes in employees to help them behave in a more engaged and goal-oriented manner for both employee and organizational success.
Making the Shift from Rule-Based AI to Behavior-Tracking
As mentioned in the previous sections, most organizations leveraging AI for improving experience are presently in stage three, which can be explained as rule-based AI for introducing automation to boost productivity.
The future, however, would see a shift to behavior tracking for executing a higher degree of personalization in various employee touchpoints. Of course, such behavior tracking will be done within the gambit of GDPR, POPI, US DataPrivacy, etc, to protect the personal data of employees. It would actually be an assessment of the traces left by employees in their day to day work. Some examples could be email interactions with peers and clients, appraisal feedback, past personality assessments, completed pieces of training, etc. The AI-platform would pick up all these traces to design a personalized employee profile to give custom recommendations for increased engagement – just like Amazon gives you item suggestions based on your past purchases.
For example, an employee may receive a notification generated by AI on the fly-by, analyzing their current role, KRAs, mail exchanges, and other sets of discussion he or she might have done with digital systems. Based on these parameters, AI can trigger a highly personalized short term learning that would help the employee complete his or her current work efficiently.
Another aspect of AI that genuinely changes the behavior is constant real-time feedback. Each click and feedback by a user at the right moment helps AI in identifying their true personality and tailor itself to adjust their behavior in line with the organizational goals.
Such personalized nudges may be impossible for human teams to curate, but AI can crunch millions of data points in seconds to transform employee experience by suggesting the right actions at the moments that matter.
Incorporating AI in your Employee Experience Strategy
AI has emerged as a gamechanger for end-customers as well as in enhancing employee experience. Besides handling repetitive queries and improving productivity, we soon envision the next trend in AI will be to shape the behavior of people by crunching the massive digital behavioral data generated at work.
One can say that AI will improve the end-to-end employee lifecycle through behavioral nudges that will transform small moments that matter into a larger set of immersive and involved experiences. Thus, the use of AI will go beyond a mere productivity tool in enterprises. It will bring in the right changes in employee behaviour, in the right context, for realizing the benefits of a highly engaged and goal-oriented workforce.
To understand this better, let’s start by dividing the employee lifecycle from hire to fire in five distinct stages:
• Talent management
• Career progression
• Learning and development
• Exit management
Now, to transform employee experience at each stage, you need to identify what’s important to your employees at every stage. For example, many employees who leave an organization within the first six months blame it on poor training or communication, which reflects a gap in the onboarding process. A Gallup State of the Global Workplace report adds that 85% of employees are either not engaged or actively disengaged at work. Another Gallup study found professional career growth to be a top priority for both millennial and non-millennial workers.
As you can see, employees have different priorities at different stages in the employee life cycle, and it is essential to consider these points before implementing any solution to improve your employee experience. At Zensar, we depend on the living AI strategy to use AI as an accelerator to deliver the right intelligence at the right moment and help achieve personalization at scale.
To help other organizations replicate this success, we have identified the following key tenets to inform their employee experience strategy:
• Mapping the hire to retire chain
• Mapping Industry Context to Employee Work Behavior
• Creating a culture of openness
• Design-centric experience and role-based personas rather than hierarchy
• Agility to break out of organizational silos and work with increasing amounts of data
• Responsible and secure handling of data by training AI systems for unbiased results
Using AI to collect and analyze behavioral data for curating personalized employee journeys is sure to improve employee satisfaction and productivity. However, with more data comes the responsibility of processing it securely within the framework of existing laws to prevent any threat to individual privacy. Additionally, as AI is a technology that is known to improve with usage, it makes sense to start with smaller nudges in processes like onboarding and learning and development before moving to aspects like talent management and career progression.
If you wish to know more about AI-enabled employee experience, get in touch with us at email@example.com. To learn more about our Humané platform that is focused on creating highly engaged and personalized experiences for employees across industries, visit https://humane.zensar.com/