Chatbots powered by Natural Language Processing for better Employee Experience

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Artificial intelligence is making great strides in our day-to-day life and chatbots like ChatGPT are simulating human conversations quite fluently. While enterprises are still grappling with security concerns on ChatGPT, there are a good number of solutions and technologies that are available in the market that offer traditional chatbots for enterprises to use (like Google Dialogflow and Microsoft Azure Language Understanding). This article describes how Chatbots could be used for better Employee Experience (EX).

In the new world of Enterprise, the focus is more holistic than the traditional approach and EX encapsulates everything the employee thinks, feels and sees. Employees expect 24×7 availability of HR information of their immediate need at their desktop and mobile. With ever changing policies and continuous adoptions of new frameworks like diversity, equity etc. the HR systems are becoming more complex and a big maze for employees to navigate through.

The challenge is no less on the HR organization itself which is a custodian of the HR policies. The team needs to continuously get trained on new policies and benefits and continuously upgrade all impacted HR systems to keep them current. The organization also needs to have a strong communication group to disseminate the information to all its employees on a regular basis through various channels. In most of the enterprises, this is leading to Information overload and employees feel an extensive amount of irrelevant information is flowing to them.

To address this problem, most of the enterprises are building HR Chatbots which act as Virtual HR agents available to employees 24×7 on their device of choice. Chatbots are basically designed to simulate and process human conversations and engage with users to provide the information they would typically get from a HR expert. The Chatbots provide the contextual information required and thus enable the employees make their decisions immediately.There are several benefits that Enterprise can leverage from Chatbots:

  • Significant Return-on-Investment: As per Gartner, by 2023, as many as 75% of HR queries globally will occur through HR chatbots. HR organizations which are adopting chatbots are able to save close to 12,000 work hours annually and it is only growing to increase.
    Also, as per Juniper Research, HR and recruitment chatbots saved approximately $8 billion in 2022 for the multiple industrial sectors.
  • Free-up HR Leaders’ time to spend time in more strategic initiatives of the organization by handing off routine tasks to Chatbots [As per reports, only 27% of HR Leaders’ time is spent on strategic business initiatives].
  • Efficiency gain in the workplace by building workflows for process automation (e.x. scheduling reviews]
  • Identify areas of employee concerns better with a proper analytics built on the data gathered from chatbots

Employee Life-cycle and Chatbots

Chatbots can be effectively used across all aspects of the Employee Life cycle (see below) – from recruiting, onboarding, tenure and finally offboarding. There are several commercial solutions available in the market that address some or most part of this lifecycle.

Three key criteria to consider in selecting a chatbot that is well suited for your organization –

  1. Most of the enterprises use industry standard Human Capital management (HCM) Solutions like – Workday, ADP, SAP Success Factors. Some of these HCM solutions like Workday provide their own Chatbot solutions. However, they are restricted to only Workday suite of products.
  2. Some of the enterprises tend to use commercial chatbots for the specific requirements like recruitment, time-sheet management.
  3. Large enterprises have more than 20+ systems to address various aspects of the HR ecosystem – Recruitment Management, HCM solution, Learning Management Systems, Succeeding Planning, Contractor Management, Reference checks Management etc. In this context, it is worthwhile to build a custom chatbot internally that will integrate into all these systems and provide a rich employee experience. Standard frameworks like Google Dialogflow and Microsoft Azure Language Understanding could be leveraged to build an in-house conversational Chatbot.

Case study:
An utility company which has more than 20,000 employees spread across its affiliate companies with each company having its own HR organization. There were central policies and policies specific to each affiliate, a common scenario in today’s corporate world. They had more than 20 HR systems from third-party vendors to address various aspects of the Employee lifecycle. Microsoft’s Azure Cognitive solution was effectively used to build a chatbot framework that could easily integrate into all the different systems and provide a comprehensive employee experience.

Solution:
The HR Chatbot solution makes use of a suite of Microsoft Cognitive Services offerings to deliver a simple and scalable solution for Chabot.
Below is the reference architecture from Microsoft for a typical chatbot:


  1. User access Chatbot either through Teams or a portal as Web Chat after Authentication with Azure AD (SSO)
  2. Chatbot client connects to Azure Bot Service to start conversation
  3. Azure Bot Service uses Conversational Language Understanding (CLU) to identify intent and entities. This helps in navigating between 4, 5 and 6.
  4. Chatbot Service connects to Question Answering Azure System to find answers for FAQ questions/intents
  5. Chatbot Service connects to external systems using REST APIs
  6. Chatbot Service logs unanswered question to a database
  7. Admin use Web portal to review feedback/unanswered question and enhance knowledge base (Azure AD SSO)
  8. Admin portal feeds enhanced knowledge base to Question Answering (via REST APIs) to train the Chatbot.

This architecture provides a simple yet robust solution to build a chatbot with a capability to enhance the knowledge base of chatbot continuously and monitor the trends. Using the Natural Language processing capabilities of CLU, the implementation can easily integrate with other systems. For ex. If the question is related to vacation, CLU will identify the intent and we could build plug-ins to connect to the time management system of the enterprise to fetch the details regarding vacation details for the employee..

Key success factors:

  1. Successful Chatbots understand the intent of the Employees rather than just being a Question-and-Answer bot. Continuous training of the system with variants of questions helps the bot to learn and be a truly conversational system.
  2. A robust Knowledge base that is continuously monitored for updates – A small team of SMEs which act as a governing committee periodically monitors the un-answered questions and enhances the knowledge base for better success ratio. The self-training of cognitive service systems combined with periodic human interface ensures higher employee experience and significant ROI for the enterprise.
  3. Omnichannel experience – The Chatbot needs to be offered through various channels that the employees typically use (sharepoint, Teams, Pop-up applications on the portal etc.).
  4. The HR IT organization needs to ensure the various in-house and third-party systems have rich API capabilities that Chatbot can leverage. The coverage and depth of Chatbot’s capability could be enhanced with integrating with additional systems (e.g. Time-keeping systems, Recruitment management system, Payroll system etc.) through these APIs.
  5. In the absence of rich interfaces from the systems involved, Chatbots could provide detailed steps on how to achieve a specific task.

The progress in Natural Language Processing (NLP) continues to facilitate the development of stronger cognitive models, which in turn makes it possible to create highly intelligent HR chatbots. These chatbots are changing the way businesses communicate with their employees, resulting in improved workforce management efficiency and effectiveness. This advancement is revolutionizing the HR landscape, generating more successful and productive enterprises that offer next-generation employee experiences.

Raghavendra Swamy
Raghavendra is a senior IT business leader with global experience over 3 decades - in Digital transformation, strategy and technology consulting, IT services, Global Delivery and Practice/Offering management. Currently, as a Managing Director at Concentrix, Raghavendra has been defining and executing transformation journeys for key clients in Healthcare, Auto and Energy and Utilities sector. He has been spearheading the Cloud transformation and Application Modernization programs that is positioning Concentrix as a Global Leader in Digital Customer Experience.

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