AI tools can automate the process-oriented tasks by immediately filtering the people who are available for a meeting at a particular slot.
Imagine a tool that predicts which employee is most likely to put down papers. That’s a critically important insight at hand since 17% of employees left their jobs within the first 6 months of joining. Solving employee attrition is hard and what makes it harder is the lack of organization’s will to address personal issues at work. And when these crucial metrics are left unattended, it is the productivity that suffers and hence the overall growth of an organization.
See also: Robotic Process Automation Implementation Choices
Appreciatively, technology has found solutions to complex issues within the human resources ecosystem so that individual productivity can be enhanced. Some processes are committed to bring down the manual tasking and utilize the resources in more productive areas while AI is at the helm of the vision.
Here’s a quick run through 4 important ways AI tools can raise the productivity quotient in all employees.
By keeping the employees happy and satisfied
More than just impressive remuneration, employees look forward to the quality of life at work. Given the increasing job-hopping rates, organizations have finally woken up to the importance of employee happiness quotient and want to experiment with everything that claims to address the issue.
Enters automation! AI-enabled tools, if programmed well can help to understand the workforce morale, their strengths (& weaknesses), and ambitions while providing intuitive suggestions to leave an impact.
For example, some project management software can crawl the conversations across communication channels including those chat boxes with the help of AI, identify the emojis most likely used and hence, predict whether the employees are cheerful or irritated. Similarly, word patterns can also be identified by crawling specific keywords that reflect the individual mood.
Imagine what if ‘unfair’ is identified as the most commonly used word? Further contextualizing these words, phrases, and emojis, the overall sentiment on the floor, whether positive or negative can be gauged. According to the popular report published by Josh Bersin, ADP has effectively used the technology to upscale its management by effectiveness by 40%.
Fundamentally, pointed feedback can be shared with managers to enhance the work experience of all employees.
By eliminating unnecessary meetings
Pointless meetings are no less responsible for affecting employee productivity. At times, managers schedule meetings as per their availability while least concerned about the status of others. And those assigned in multiple projects, are left in a deadlock situation. Unsurprisingly, in 2019, US companies drained USD 399 billion in unnecessary or failed meetings.
Imagine the level of unproductivity due to everyone browsing calendars and trying matching their timings with others. Therefore, not inviting everyone to all meetings requires a smart assistant that can instantly recommend those who are most likely available to join.
AI tools can automate the process-oriented tasks by immediately filtering the people who are available for a meeting at a particular slot. Moreover, employees based on their central location, specific designations, experience, etc. can also be included or excluded.
Delegating such tasks to a tool can produce productive outcomes by enabling everyone in the team to focus on their core job roles. Simple yet effective implementation!
By encouraging more employees to take up interim training programs
In house learning & development initiatives are finally accepted as gospels across organizations. There is a swathe of opportunities available for everyone to learn and grow in newer areas. However, it is the random placement of resources in different training programs that needs attention. Currently, they haven’t been a great success in striking a balance between the needs of the company and the interest of the candidate.
Using AI, managers can perform apt mapping of the available courses versus the availability of interested candidates. For example, every employee can be asked to submit 3 courses of their interest. Accordingly, the AI algorithm can pick the most relevant candidates for every course. Not to miss, certain qualifying criteria such as experience and potential can also be taken into consideration. Ultimately, chatbots (machine learning) can be used to notify an employee every time the desired course is available.
By simplifying the employee onboarding experience
Restricting employee onboarding to a mere recruiting new talent is an unfair assessment. Highly process-oriented, it includes educating the employee with the organization regulations, detailing the assigned role for increased accountability at the workplace, introducing them to the work culture and finally assisting them to build first-hand relationships with the staff. Given so many tasks to complete at length, onboarding deserves the right mix of automation and human verification.
Starting candidate screening, recruiters must utilize AI platforms to filter the most appropriate candidates. Not only it saves time but it also establishes clearer expectations of post recruitment. And then there’s Natural Language Processing (NLP), an AI technology that can quickly generate offer letters, contracts and other essential documents using unstructured data from emails and other sources. And yet again, chatbots are of great help in simplifying the induction process. After consuming the initial introduction about the company, new joiners can ask any questions in the chatbots and seek instant answers. This saves time, frees the resources to form tiring engagements and provides the liberty to the employee to seek information as and when needed.
AI is going to transform the world more than anything else in the history of mankind and employee engagement is just one of those simple use cases. Henceforth, every organization should unlatch the potential and improvise their process verticals.
