#hrtechseries

Catch this HRTech Talk by HRTech Series featuring Holly Grogan, Chief Experience Officer, Appspace where we discuss the nuances around HRTech adoption patterns and why tech brands need to align better on using HRtech to drive both, the customer and employee experience

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About the HRTech Talk Series:

A chat series featuring HRTech founders, HRTech innovators, HRTech product specialists and other HRTech executives who have an extensive presence in the global HRTech Realm.

About Appspace:

Hi Joanna. Welcome to our Interview Series. Please tell us a little bit about your role and responsibilities in your current company. 

Hello, Sudipto!

As Chief Human Resources Officer at Elastic, I collaborate with our teams to make sure that our business has amazingly talented people developing our products and serving our customers, and that Elasticians have a great experience working with us. That includes everything from recruiting to compensation to learning, DEI and workplaces and much more.

How has the role of a CHRO evolved in the AI era? 

The role of the CHRO is really about using data-driven insights to ensure our talent strategies deliver on our business priorities, while also creating the culture and conditions for people to perform their best.

I don’t think the core of the CHRO role changes in the AI era but I think the skills a CHRO needs now include understanding how we can responsibly leverage the capability of AI to deliver more effectively, efficiently and with a better employee experience.  I’m really excited to get started on this journey alongside my teams to see where we can go with AI.

What are the profound changes you witnessed in the HR landscape since the onset of the COVID-19 pandemic?

I think, we’ll continue realizing the impact of the COVID-19 pandemic for years to come. It started what is becoming a dramatic shift in how we define work and the workplace. It’s still changing how people think about work in their lives and priorities. From an HR perspective, these changes are enabling us to demonstrate a new agility and even a new creativity in how we approach supporting our employees and the larger business needs.

Please tell us about your HR Tech stack and how you plan to expand the scope of AI and automation for your HR department?

As with many growing companies, Elastic has fantastic tools in place to support our work and teams, including familiar platforms such Workday, ServiceNow, Monday.com and Greenhouse.

We’re now turning our focus on integration and workflow automation. How can we create integrated, personalized experiences for employees to help them get their questions answered and resources accessed? AI will certainly be vital in this journey.

Could you tell us about the toughest decision that you had to make in your HR career?

I led the COVID-19 response at my prior company.

The decisions that we had to make in the early part of 2020 were challenging. Some of our essential employees could not work from home. We had to prioritize the health and safety of our employees while ensuring we continued to deliver for clients who depended on our solutions to keep their businesses going. In some cases their businesses were in turn critical to keeping economies afloat and delivering healthcare or other critical infrastructure during the pandemic. This was at a time when the data about how COVID spread was evolving every day. Luckily I worked with exemplary colleagues who brought expertise and empathy to making these decisions.

How can organizations benefit from having an employee-first approach to growth and collaboration? 

I like to think of it as employee-centric.

Keeping your people in the center doesn’t mean losing sight of your customers or business objectives, but means constantly asking how you can achieve those objectives in a way that works for your people too. It means asking if there’s a way to get the same result while giving your people more support or flexibility. Sometimes very small adjustments in how something gets done make a huge difference for your employees – and those are the things people remember.

What are the major challenges of tapping good talent and retaining them within an organization?

At Elastic, we have a very compelling value proposition when approaching good talent. We have great technology that is going to be essential to customers in their AI/ML journeys, great people, and a great culture. My advice to other CHROs is to be clear about what your employee value proposition is – and what it isn’t- and stay true to that.  For me, retaining good talent means focusing on your people managers.

Do they provide feedback?

Remove roadblocks?

Help their team members grow and develop?

The ROI on having great managers is huge.

Why are so many startups failing despite paying significantly above average compensation to their employees? 

If a company’s premise starts with compensation and assumes product and business success will follow, they probably have it backwards.

Fundamentally you need to have a product or service that customers want and need (and will pay for)! Then pay appropriately to attract the talent you need. It’s important to recognize that compensation is an important part of the total employee value proposition, but it’s not the only part, or the most important part in my experience.

What kind of leadership development program would you recommend to the HR leaders?

Even more than ever, HR Leaders are looked to for leading through change and uncertainty.  This means how to bring clarity to the issue and outcomes, and how to lead people effectively through situations that can initially seem destabilizing. I would recommend leadership development that focuses on building these skills as well as personal resilience.

Your take on the future of AI-powered apps for employee experience management and performance review across industries:

AI definitely has the power to enhance employee experience by serving up more relevant information, assisting transactions, and making recommendations. When it comes to performance reviews, I think the highest quality feedback is going to come from a person, to a person, in service of helping that person develop and grow. We can’t lose sight of the fact that this is about people at the end of the day.

Lighter notes:

Coffee, or Tea?

Coffee

Your favorite Elastic people management initiative that you want everyone to know about?

Attracting, engaging, and retaining top talent requires a strategic approach. Enter Artificial Intelligence (AI), a game-changer in the realm of talent management. AI-powered solutions are revolutionizing the way organizations handle talent management; automating mundane tasks, and creating a more personalized and positive candidate experience.

Understanding AI in Talent Management

Artificial Intelligence (AI) has become a transformative force in various industries, and talent management is no exception. AI in talent management refers to the application of machine learning algorithms, natural language processing, and other AI technologies to streamline, enhance, and optimize the processes involved in attracting, developing, and retaining talent within an organization.

Recruitment and Hiring

One of the most prominent applications of AI in talent management is in recruitment and hiring. AI-driven tools can automate the initial stages of the hiring process, significantly reducing the time and effort required. For instance, AI can be used to scan and evaluate resumes, identifying the most suitable candidates based on predefined criteria. This not only speeds up the process but also helps eliminate unconscious bias, ensuring a more diverse and inclusive candidate pool.

Chatbots and virtual assistants are increasingly being employed to engage with candidates, answer their queries, and schedule interviews. These AI-powered tools provide a seamless and efficient communication channel, enhancing the candidate experience and freeing up HR professionals to focus on more strategic tasks.

Talent Development

AI also plays a crucial role in the development of talent within organizations. Personalized learning and development programs can be created using AI to analyze individual performance data, learning preferences, and career aspirations. AI-powered learning management systems (LMS) recommend courses, training modules, and career development resources tailored to the needs of each employee. This personalized approach ensures that employees are continually growing and developing their skills in alignment with both their personal goals and the organization’s objectives.

Furthermore, AI can facilitate mentoring and coaching by matching employees with mentors who have the appropriate expertise and experience. By analyzing data on skills, career trajectories, and interpersonal compatibility, AI can create more effective and impactful mentor-mentee relationships.

Performance Management

AI is also significantly impacting performance management. Conventional performance evaluations often suffer from subjectivity and bias. AI-driven performance management systems provide a more objective and data-driven approach. These systems can continuously monitor and analyze employee performance using a variety of metrics, such as productivity, engagement, and goal attainment.

Real-time feedback mechanisms enabled by AI allow for continuous performance improvement rather than annual reviews. Managers receive actionable insights and recommendations based on data analysis, helping them support their teams more effectively. This approach fosters a culture of continuous improvement and growth.

Retention and Employee Engagement

Many organizations face the crucial challenge of retaining their top talent. AI can help identify employees who are at risk of leaving by analyzing factors such as job satisfaction, engagement levels, and career progression opportunities. Predictive analytics can provide early warnings, allowing HR teams to intervene proactively with retention strategies such as career development opportunities, role changes, or other incentives.

AI also enhances employee engagement by enabling more personalized and responsive communication. Sentiment analysis tools can gauge employee morale and satisfaction through regular surveys and feedback mechanisms, providing valuable insights that help shape a more engaging and supportive work environment.

Ethical Considerations and Challenges

While the benefits of AI in talent management are substantial, it is essential to address ethical considerations and challenges. Ensuring data privacy and security is paramount, as is the need to mitigate bias in AI algorithms. Transparent and ethical use of AI requires continuous monitoring and adjustment to prevent any form of discrimination and to promote fairness and equity in all talent management processes.

Catch more HRTech Insights: HRTech Interview with Keith Bigelow, Chief Product Officer, Visier

Automating Talent Management 

 One of the most significant advantages of AI in talent management is its ability to automate various tasks, freeing up HR professionals to focus on strategic initiatives.

Resume Screening and Candidate Shortlisting

Traditionally, resume screening is a time-consuming process. AI-powered tools can analyze resumes in seconds, identifying the most qualified candidates based on predefined criteria. These tools use NLP to understand job descriptions and match them with the relevant skills and experiences listed in resumes.

Interview Scheduling

Coordinating interviews involves multiple communications between candidates and interviewers. AI-driven scheduling tools can automate this process by finding suitable times for all parties, sending calendar invites, and managing rescheduling requests. This not only saves time but also improves the candidate experience by reducing wait times.

Employee Onboarding

AI can streamline the onboarding process by automating paperwork, training schedules, and compliance checks. Virtual onboarding assistants can guide new hires through the initial stages, answering their questions and providing necessary resources. This ensures a smooth transition and helps new employees become productive faster.

Performance Management

AI tools can continuously monitor employee performance by analyzing data from various sources such as project management software, feedback systems, and communication tools. This allows for real-time performance evaluations, identifying top performers, and highlighting areas needing improvement.

Enhancing Candidate Experiences with AI 

Creating a positive candidate experience is essential for drawing in and keeping top talent. AI enhances this experience by providing personalized, efficient, and engaging interactions throughout the hiring process.

Personalized Communication

AI can analyze candidate data to personalize communication at every touchpoint. This includes:

Tailored Job Recommendations: Based on a candidate’s profile and past applications, AI can suggest job openings that align with their skills and career aspirations.

Customized Email Content: AI tools can craft personalized emails, addressing candidates’ specific interests and questions, which improves engagement and satisfaction.

Efficient Processes

AI-driven automation ensures that candidates are not left waiting for responses. This includes:

Instant Application Acknowledgement: AI can send immediate acknowledgments upon receiving applications, setting clear expectations for the next steps.

Real-time Updates: Candidates can receive real-time updates on their application status, interview schedules, and feedback, keeping them informed throughout the process.

Engaging Interactions

AI-powered tools such as chatbots can engage candidates in real-time conversations, answering their questions and providing information about the company culture, benefits, and more. This level of engagement helps candidates feel valued and informed, enhancing their overall experience.

Case Studies and Industry Examples 

Unilever’s AI-Driven Recruitment Process

Unilever, a global consumer goods company, has successfully implemented AI in its recruitment process. By leveraging AI-powered gamified assessments and video interviews, Unilever has reduced its hiring time by 75%. The AI tools analyze video interviews for facial expressions, word choice, and speaking patterns to assess candidates’ suitability, providing a more comprehensive evaluation than traditional methods.

Hilton Worldwide’s Chatbot for Candidate Engagement

Hilton Worldwide uses an AI-driven chatbot named “Connie” to enhance candidate engagement. Connie interacts with candidates, answering their questions and providing information about job opportunities. This has significantly improved the candidate experience by offering instant responses and personalized interactions.

IBM’s Predictive Analytics for Talent Management

IBM employs AI-powered predictive analytics to manage its talent pool effectively. By analyzing employee data, IBM can predict potential turnover, identify skill gaps, and plan for future workforce needs. This proactive approach helps IBM retain top talent and ensure a skilled workforce.

Challenges and Ethical Considerations 

While AI offers numerous benefits, it also presents challenges and ethical considerations that organizations must address.

Bias and Fairness

AI algorithms can unintentionally reinforce biases found in their training data. This can lead to unfair hiring practices and discrimination. Organizations must ensure that their AI tools are trained on diverse datasets and regularly audited for bias.

Data Privacy

AI systems require access to vast amounts of personal data, raising concerns about data privacy and security. Companies must implement robust data protection measures and comply with relevant regulations to safeguard candidate and employee information.

Transparency

The insurance industry, while financially robust, is often criticized for its slow and paper-centric processes, lack of transparency, and vulnerability to fraud. InsurTech, the marriage of insurance and technology, has emerged to address these concerns by leveraging digital solutions. However, a new wave of innovation is on the horizon, driven by blockchain technology.

Blockchain, a distributed ledger technology, offers a secure, transparent, and immutable record-keeping system. This has the potential to revolutionize the way insurance companies operate and interact with their customers. Blockchain, with its inherent characteristics of immutability, transparency, and decentralization, presents an enormous potential to reshape the insurance landscape.

Transforming Traditional Insurance Processes with Blockchain

Traditional insurance processes often suffer from inefficiencies, opacity, and fraud risks. Manual paperwork, cumbersome claims processes, and lack of transparency have long plagued the industry. Blockchain technology, however, offers a solution by fundamentally transforming these processes.

Streamlining Claims Processing: One of the most significant pain points in traditional insurance is the lengthy and complex claims process. Blockchain can automate claims processing through smart contracts—self-executing contracts with the terms directly written into code. When a claim is submitted, the smart contract automatically verifies the claim’s validity by cross-referencing with policy details and other relevant data stored on the blockchain. This automation reduces processing time, minimizes human error, and ensures that claims are handled efficiently and transparently.

Enhancing Underwriting Accuracy: Underwriting, the process of assessing risk and determining premiums, relies heavily on accurate and comprehensive data. Blockchain’s immutable ledger allows insurers to access a vast amount of verified data from multiple sources, including IoT devices, health records, and financial information. This data aggregation leads to more accurate risk assessment and personalized pricing, benefiting both insurers and policyholders.

Improving Fraud Detection: Fraud is a major concern in the insurance industry, leading to significant financial losses. Blockchain’s transparency and immutability make it an effective tool for combating fraud. All transactions recorded on the blockchain are time-stamped and cannot be altered, providing a reliable audit trail. This transparency deters fraudulent activities and makes it easier to detect and investigate suspicious claims.

Facilitating Regulatory Compliance: Insurance companies must comply with a myriad of regulations that vary across regions. Blockchain can simplify compliance by providing a transparent and tamper-proof record of all transactions and interactions. Regulatory bodies can access this immutable ledger to verify compliance, reducing the administrative burden on insurers and ensuring adherence to legal requirements.

Key Applications of Blockchain in Insurtech

The integration of blockchain into InsurTech is not limited to theoretical benefits; practical applications are already emerging across various segments of the insurance industry.

Peer-to-Peer (P2P) Insurance

Blockchain enables the creation of P2P insurance platforms, where groups of individuals can pool their resources to insure against specific risks. Smart contracts, which are self-executing contracts with the terms of the agreement directly written into code, manage these insurance pools. When a claim is filed, the smart contract verifies the claim against pre-set conditions and processes the payment automatically. This reduces the need for intermediaries, lowers administrative costs, and enhances trust among participants, as all transactions are transparent and immutable.

Microinsurance

In many developing regions, traditional insurance products are either unaffordable or inaccessible. Blockchain technology supports the development of microinsurance solutions, which offer low-cost, scalable insurance tailored to low-income populations. Smart contracts automate the issuance and management of these policies, significantly reducing administrative costs and making insurance more accessible. Blockchain also ensures transparency and accountability, which are crucial for gaining the trust of underserved communities.

Parametric Insurance

Parametric insurance is an insurance model that triggers automatic payouts when predefined conditions or parameters, like natural disasters or severe weather events, are satisfied. This differs from traditional insurance, which requires a loss assessment before payment. Blockchain, combined with IoT devices, can monitor real-time data (e.g., weather conditions) and trigger smart contracts for instant payouts when predefined criteria are met. This provides quicker financial relief to policyholders and reduces the need for lengthy claims processes.

Identity Verification and KYC

Know Your Customer (KYC) processes are essential for preventing fraud and ensuring compliance with regulations. However, traditional KYC procedures are often cumbersome, repetitive, and costly. Blockchain can streamline KYC by storing verified identities on a secure, immutable ledger. Insurers can quickly and efficiently access this information, reducing onboarding times and costs while enhancing security. This shared digital identity system can also help reduce identity theft and fraud.

Reinsurance

Reinsurance involves insurers transferring portions of their risk portfolios to other parties to mitigate the risk of large claims. Blockchain facilitates more transparent and efficient data sharing between insurers and reinsurers. Smart contracts can automate the execution of reinsurance agreements, ensuring that data is consistent and accurate across all parties. This reduces administrative overhead, speeds up the process, and enhances trust between insurers and reinsurers.

Fraud Detection and Prevention

Fraud is a significant issue in the insurance industry, leading to substantial financial losses. Blockchain’s transparency and immutability make it a powerful tool for fraud detection and prevention. All transactions and claims recorded on the blockchain are time-stamped and cannot be altered, providing a reliable audit trail. Insurers can use this data to detect patterns indicative of fraudulent activities and investigate suspicious claims more effectively.

Claims Management

The claims process in traditional insurance is often slow and inefficient, involving multiple intermediaries and manual verifications. Blockchain can streamline claims management by automating the entire process through smart contracts. When a claim is submitted, the smart contract verifies the claim’s validity against the policy terms and triggers the payment automatically. This reduces processing times, minimizes human error, and ensures transparency throughout the claims process.

Policy Administration

Blockchain can also enhance policy administration by providing a single, immutable record of all policy details. This simplifies the process of updating and managing policies, ensuring that all parties have access to the most current information. It reduces administrative burdens and enhances the accuracy and reliability of policy data.

Read More On Fintech: Uncovering The Biggest Hidden Insider Risk For The Financial Industry

Benefits and Potential of Blockchain for Insurtech