Automating employee query management at KEC International using Leena AI: A case study
KEC International is one of the world’s biggest infrastructure Engineering, Procurement and Construction (EPC) companies and has undertaken infrastructure development projects in more than 100 countries. The company has over 4,000 employees working in diverse teams and verticals all over the world. However, one recurring HR challenge was promptly resolving employee queries and requests regarding leaves, payroll and company policies. KEC International teamed up with Leena AI to create Electra – a customised HR chatbot. Let’s take a closer look at the process of implementation and its impact.
The Challenge: High Employee Query Resolution Time
One of the prominent challenges was the fact that several information systems and portals were working in isolation and were in use simultaneously. Naturally, this increased the amount of time spent by employees in looking for relevant information on the right system. Similarly, the process of solving simple, yet similar, employee queries – like finding out their remaining leaves, applying for leave or getting a copy of their payslip – required high manual effort and time. Put together, both these factors meant that the time taken to resolve employee queries was high. The lack of an effective query-resolution framework also meant that employees were frequently reaching out to the already overstretched HR Business Partners (HRBPs).
Since a majority of the employee queries were similar in nature, Leena AI integrated the chatbot with KEC International’s HRIS – SF, which helped in automating the leave application and approval system. Next, a considerable effort was made to understand and record the different colloquial ways in which employees refer to company information and policies. This helped in automating the answers to frequently asked questions by the bot using Natural Language Processing (NLP). However, in the case of highly-personalised and complex queries, the bot raised a ticket to HRBPs for resolution, thus, ensuring that no employee grievance went unaddressed. As an added functionality, the bot was integrated with KEC International’s twitter handle and other relevant news websites to regularly share the latest company information, updates and news with employees.
The Impact: Seamless and Timely Access to Relevant Information
By integrating the different information systems and automating the employee query resolution management, Leena AI created one-point access to obtain relevant company information that was available round the clock. Nearly 90% of all employee queries and issues are now resolved by the chatbot, which means that the employee query resolution time has reduced by 80% and helped the company by saving more than 5000 HR hours in the just one quarter. In other words, employee queries are resolved in one-fifth of the time taken previously, and the company has been able to enjoy a 9X return on investment within the last quarter. However, that’s not all – since employees are continuously receiving the latest company announcements, news and information directly, their engagement levels have also gone up in the last few months.
Somraj Samin Roy, HR Head – KEC International, says, “As a truly ‘Global’ organization, KEC International has striven to be on the forefront of ‘agility’ especially by leveraging digitalization across its value chain. This has helped us in our constant endeavour of Unlocking the potential while offering bespoke experiences to our multiple stakeholders. ELECTRA – our very own chatbot has been one such medium through which we have pushed the borders by offering seamless, real-time service to our employees, resulting in enriching their HR service experience.”
The impact created by Leena AI has changed that way employee queries and requests were managed at KEC international. The case study proves that AI-driven tools can be leveraged by HR leaders and professionals to automate repetitive tasks that require high manual effort and save valuable time and resources in the process.
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