In today’s highly competitive business landscape, organizations are constantly seeking ways to gain a competitive edge. One of the most valuable assets for any company is its talent pool. Companies that can attract, develop, and retain top talent are more likely to succeed in the long run. As per Gartner’s findings, in 2023, the workforce has emerged as one of the top three priorities for CEOs, highlighting a growing awareness among organizational leaders regarding the significance of talent strategy.

However, Gartner’s data reveals that only 32% of HR leaders report that their HR strategic planning process is fully integrated with the business’s planning process. This statistic highlights a significant gap in the alignment between HR strategies and broader organizational planning.

Moreover, based on Deloitte’s report, an alarming statistic reveals that only 10% of executives can effectively anticipate the skills they will require for their workforce over the next three years. This low level of foresight underscores a critical challenge faced by leaders: the lack of comprehensive workforce data necessary to make informed decisions about talent management and strategy.

This is where Talent Analytics comes into play. Talent Analytics can help organizations make data-driven decisions about their workforce, leading to better hiring, improved employee engagement, and increased productivity. However, to successfully implement Talent Analytics, several key components are required. In this article, we will explore what it takes to implement Talent Analytics effectively.

One of the foundational requirements for implementing Talent Analytics is a robust data infrastructure. This includes collecting and storing relevant data on employees, applicants, and the talent acquisition process itself. The data can come from various sources, such as applicant tracking systems, HR databases, performance reviews, and even external sources like social media and industry benchmarks. It’s essential to ensure data accuracy, security, and compliance with data privacy regulations (e.g., GDPR or CCPA).

Moreover, proactive data governance strategies, including regular audits and compliance checks, should be in place to maintain data accuracy, protect sensitive information, and adhere to evolving data privacy regulations. This meticulous attention to data infrastructure safeguards the reliability of insights derived from Talent Analytics, ensuring informed decision-making throughout the organization.

Effective Talent Analytics integration necessitates collaboration between HR and cross-functional teams, including finance, operations, and marketing, to align with broader organizational strategies. For example, when confronted with workforce turnover, this cross-functional collaboration empowers teams to analyze HR data alongside financial, operational, and market insights, leading to the development of comprehensive retention strategies in harmony with overall business goals.

In addition to the foundational data mentioned above, another critical component of Talent Analytics implementation is skills data. Understanding the skills possessed by employees, as well as the skills required for various roles within the organization, is paramount. This data enables organizations to bridge the gap between their current workforce capabilities and future skill needs, aligning talent strategy with business objectives effectively.

Skills data can be collected through skills assessments, training records, certifications, and performance evaluations, providing valuable insights into workforce competencies and areas for development. Integrating skills data into Talent Analytics enhances the ability to make strategic decisions related to skills development, succession planning, and talent acquisition, ultimately contributing to a more agile and competitive organization.

To harness the power of Talent Analytics, organizations need the right tools and technology. This includes specialized analytics software and platforms designed for HR and talent management. These tools should be capable of processing large datasets, conducting advanced statistical analysis, and generating meaningful insights. Cloud-based solutions can provide scalability and accessibility, enabling HR teams to access data and insights from anywhere.

One such platform is EDLIGO Talent Analytics, which stands as an innovative AI-powered solution poised to reshape talent management. With features that enable comprehensive competency assessment, stimulate a growth mindset, and maximize ROI from Learning and Development, EDLIGO empowers organizations to identify, retain, and develop top talent while enhancing the overall employee experience. Its seamless integration capabilities, coupled with a commitment to data privacy, ensure that HR leaders can harness the power of data and AI to make impactful talent management decisions, setting the stage for future-ready workforces aligned with business goals.

Having the right technology is essential, but it’s equally important to have a skilled workforce capable of utilizing Talent Analytics effectively. HR professionals need training and development in data analysis, statistics, and data visualization to make sense of the data generated by analytics tools. Additionally, data scientists and data analysts can play a crucial role in extracting actionable insights from complex data sets.

To gain essential expertise in Talent Analytics, you can explore courses and certifications available at AIHR Academy. AIHR Academy has partnered with EDLIGO, offering a 20% discount on their programs, which you can access through a provided link https://www.aihr.com/partner/edligo/. These courses cover a range of valuable topics in Talent Analytics, enabling you to enhance your skills and knowledge in this field.

One such offering is the People Analytics Certificate Program, designed to elevate your career by equipping you with the skills, knowledge, and practical experience required for successful People Analytics projects that drive pivotal talent and business outcomes. This comprehensive program covers a range of critical topics, including data-driven business impact, analytics implementation, basic statistics, self-service dashboards, and the art of storytelling with data.

Before diving into Talent Analytics, organizations must define clear objectives and key metrics. What are the specific talent-related challenges the organization wants to address? These could include reducing turnover, improving employee engagement, identifying high-potential employees, or optimizing the hiring process. By setting clear goals and key performance indicators (KPIs), organizations can measure the impact of their Talent Analytics initiatives.

Here are some of the most useful HR metrics that every company should consider tracking:

• Skills Gap Analysis: Identify the disparity between the skills employees possess and the skills required for their roles. This analysis can inform targeted training and development initiatives
• Skills Inventory: Maintain a comprehensive database of employees’ skills, competencies, and certifications to better match employees with projects and opportunities.
• Turnover Rate: Measure the rate at which employees leave the company voluntarily or involuntarily. This metric helps assess talent retention efforts.
• Employee Engagement Score: Evaluate employee satisfaction, commitment, and motivation, which directly impact productivity and retention.
• Diversity and Inclusion Metrics: Track diversity in hiring, promotions, and retention to promote a more inclusive workplace and diverse talent pool.

To learn more about HR Metrics, watch our webinar about HR Metrics and Analytics: Driving Business Strategy with Talent Data. Accomplished HR thought leaders and practitioners— Emma Smith (The Horsey HR Lady), Konstantin Tskhay, PhD (Tskhay & Associates, Inc.), and Reimund Nienaber (EDLIGO Talent Analytics and Learning Analytics)—will share how you can leverage HR Metrics and Talent Data to drive your business to its full potential.

As organizations collect and analyze employee data, ethical considerations and data privacy become paramount. It’s crucial to establish ethical guidelines and ensure compliance with data protection laws. Transparency and communication with employees about data usage and privacy are also essential to maintain trust and transparency within the organization.

Beyond regulatory compliance, addressing ethical considerations and data privacy also plays a pivotal role in mitigating risks and safeguarding the organization’s reputation. Instances of data breaches or unethical data handling can result in legal repercussions and severe damage to the company’s image. By prioritizing ethical data practices and maintaining transparent communication with employees, organizations not only uphold their legal obligations but also protect their brand integrity and trustworthiness in the eyes of both employees and the public.

Talent Analytics is not a one-time project; it’s an ongoing process. Organizations should continually monitor and refine their Talent Analytics initiatives based on the insights they generate. Regularly reviewing the effectiveness of talent strategies and adjusting them as needed will lead to better outcomes over time.

Continuous improvement in Talent Analytics is essential for organizations to stay adaptable in rapidly evolving environments. Market dynamics, technology advancements, and workforce preferences are constantly changing. By regularly reviewing and adapting Talent Analytics initiatives, organizations can remain agile and responsive. This adaptability enhances the organization’s ability to thrive in an ever-changing business landscape and secure a competitive advantage.

In the pursuit of maintaining ethical and responsible utilization of AI-powered Talent Analytics, it is imperative that we remain cognizant of the evolving legislative landscape. In March 2023, the European Union introduced the Artificial Intelligence Act, an all-encompassing framework for regulating AI. Updated in June 2023, it emphasizes data quality, transparency, and accountability across diverse industries. The Act classifies AI into four risk tiers, imposing strict regulations on high-risk applications while permitting low-risk AI with minimal constraints. Though contested by some European companies, the EU persists in its mission to establish a robust AI regulatory framework in line with European values.

Implementing Talent Analytics is a strategic move that can provide organizations with a significant competitive advantage in the modern business world. However, it requires careful planning, investment in technology and skills, and a commitment to ethical data practices. By incorporating Talent Analytics into their HR and talent management strategies, organizations can make more informed decisions, optimize their workforce, and ultimately achieve better business outcomes.

Moreover, AI-powered Talent Analytics supports the development of skills-based talent management in organizations, allowing them to precisely match employees’ skills with specific roles and projects. EDLIGO, with its advanced AI capabilities, can facilitate this process, enabling organizations to harness the full potential of their workforce and drive greater efficiency and innovation.

By Konstantin Tskhay, Ph.D. 

The world has changed.  

Over the last 6 months, we have seen an emergence of AI technology taking the average consumer by storm. Its applications do not stop at asking ChatGPT to provide us with a definition for a word we could find on Google anyway. AI can code, AI can create decks, and AI can integrate multiple images to create our LinkedIn headshots.  

The applications of AI are vast 

And new applications are emerging daily—life and work as we know it is changing.  

Indeed, Bain & Company recently released a study estimating that up to 40% of management jobs will be disrupted by AI. This means tasks you hated doing will disappear and become streamlined, allowing you to create more space for strategy, reflection, and thinking about improving businesses.  

This, of course, creates an interesting conundrum for People Analytics.  

On the one hand, People Analytics is a very, very new discipline designed to process data for strategic decision-making about human capital. On the other hand, because People Analytics is all about data; and AI can process more data and do it faster.  

So, what is the role of the People Analytics function, then? 

Think about it:  

As an executive, I don’t need to go to my people analytics leader and ask them for a dashboard to understand my turnover. I can ask my AI engine:  

“Draft a voluntary turnover chart using the data in our HRIS, annualize it, and create three scenarios for turnover for the rest of the fiscal year. Once done, break down the data by gender and level to help me understand whether we are losing people in certain groups more than others. Create graphs and interpretation of results in plain English and make action recommendations.” 

Voila.  

You look at your screen, and after a few seconds (or maybe minutes) of thinking, your chat produces a short, straight-to-the-point overview of turnover. With Graphs! With recommendations! 

Even more incredible is that your board of directors has access to the same technology, asking the same exact questions simultaneously, helping them advise you continuously versus reacting to what is presented in the quarterly meeting.  

What is the role of People Analytics, then? 

• Connect datasets? Data engineering can get this process done.   
• Analysis? AI is running all the predictive models and evaluates them.  
• Data storytelling? Perhaps, but here we are looking at consulting rather than technical skills.  

AI becomes your Technician. It takes the technical work off the hands of the People Analytics team.  

So, what is left then? 

Technicians can’t work in a vacuum; they need two other roles: direction and management.  

Thus, we are left with Entrepreneurs and Managers. Or put together product managers. These are the people who oversee the work of AI, ensure the high quality of the inputs and outputs, and think about new ways to use AI to drive business outcomes via strategic and effective deployment of your people.  

They are less interested in technical specs and more focused on the customer—the business.  

The role becomes less technical and less focused on the grind of delivery. It’s built around research, exploration, and entrepreneurship. It starts to attract different personalities. People who want to disrupt the status quo and create new solutions. It becomes a playground where all ideas are considered, and the best ones survive.  

But as we ponder this beautiful new future, can we still call this work People Analytics?  

Or should we call it something else?  

No, I don’t think that AI will exterminate People Analytics as a function.  

I do think that it will change it into something completely different from what we see today.  

Most organisations will use HR Metrics. They are things like sickness absence rates, employee turnover (how many people are leaving) and where our job applicants find out about our vacancies.

Fewer people are aware of ISO 30414:2018 – Human resource management – Guidelines for internal and external human capital reporting. This is a lengthy way of saying it’s a standard on HR Metrics and reporting. As an international standard, it brings with it a wealth of benefits, not least of which is an external certification saying you meet the standard.

But why am I interested in this?

Over the course of my career, I have contributed to or written entirely, HR reports that are provided to the Board, senior managers etc. I’ve built dashboards in Excel to make managing the reporting easier and worked with IT Directors to begin to use the business reporting mechanism.

In my experience, HR reports are a couple of lines of text and then some graphs highlighting some metrics. Yet they can be so much more! Metrics within HR interlink with each other but also with other departments and that is where the real power of metrics is, consider this from my experience:

A manager is constantly recruiting staff, using any agency that waves a CV in his email, using a test HR wasn’t allowed to see and planning a restructure (that HR wasn’t involved in). In a senior management meeting, I explained that the recruitment budget is gone. It has been wiped out 2 months into the financial year. The preceding slide to this was employee turnover. This manager had a 70% employee turnover rate in a team of 10. On average a new recruit to this team was about £10,000. The restructure was adding 4 more positions to the team to cover shift work.

There were low employee engagement scores, a low number of near-miss incidents being reported, an increase in accidents and poor reports from the agencies that said people wouldn’t work for the company.

The outcome of this was the Finance Director moved budget from the manager’s budget back to my budget so the rest of the organisation could use agencies that year, the entire recruitment process in the team was reviewed and improved, the team were re-briefed about near miss reporting and the manager was asked to attend some training to deal with how the team was run. It gave me a basis to start working with the other departments on how to better support them – one of those initiatives was to install an IT help desk system into the HR department to see the volume of work coming in and to automate some manual processes making them GDPR compliant in the process.

HR should be, in my opinion, at the heart of the organisation yet it is often seen as a cost centre. The HR team have a wealth of data at their fingertips and by linking with other departments, can really change how they are perceived in an organisation.

There is no reason that the HR team can’t share limited and/or anonymised data with other departments. Think about the following:

• Forecasting the number of leavers for the following financial year
  • to share with finance to determine the recruitment budget
  • to share with IT to arrange the necessary equipment
  • to share with facilities for a desk to be assigned
  • to share with H&S to arrange the necessary PPE
• Working with Sales & Marketing to see when promotions are going to happen to assess the workforce requirements
• Working with all the departments about any planned growth
• Looking at the skills of existing staff against what is needed to generate development/talent plans

In 2021, I was fortunate to be the first auditor to participate in an audit against the ISO30414 standard. I worked alongside the lead auditor and between us, we determined that the reporting both internally and externally met the standard. But what were we looking for?

We looked to see if the policies in place met with legislation and whether the reporting also covered what was required. This was an interesting part as the organisation operates in three different countries.

We determined whether the organisation should be measured against the SME requirements. This isn’t defined within the standard as it is left to the country to determine. In the UK for instance, I would look to the Companies Act for a definition. We talked about what information should be made public and what shouldn’t. The standard has guidelines for this.

We then looked at the metrics and worked through the documents provided to see what the organisation had already covered in their work and what needed further work.

The audit works on a Red/Amber/Green (RAG) process where red is not present, amber requires more work and green meets the standard.

After the initial audit, there were several places that were red or amber and we provided a list of HR consultants that the organisation could work with to move them on to a second and final certification audit.

The organisation has published part of its final report whilst keeping some sections as only for the organisation. You can see more at https://jetruby.com/iso/. Their HR Manager also wrote a testimonial for me:

“I worked with Emma during our auditing process to certify JetRuby according to ISO 30414 Human Capital Reporting and ISO 10018 People Engagement. Emma was our auditor together with David Simmonds. This was our first ISO audit. And, if I’m not mistaken, it was one of the first ISO 30414 audits in the world, since the standard was issued about a year before. It was a challenge for us. Emma carefully and thoroughly reviewed the pile of documents we provided. She was very helpful and attentive. She took care to answer our questions and to provide detailed feedback. We managed to complete the audit within three months and a lot of credit goes to Emma for that. I highly recommend Emma as a great HR expert and a dedicated professional.”

As part of my focus on #peopleanalytics, I partnered with Edligo having had a chat with them and seeing the software that they offer.

It is a fabulous #Talentanalytics platform offering competency, learning & development, performance management and workforce planning to larger organisations.

These four areas are going to be key over the coming years as the world of work continues to change as a result of economics, people entering and leaving the workforce, people taking charge of their own development rather than relying on the organisation to provide opportunities and of course, the shift from office to hybrid or fully remote working.

In today’s highly competitive business landscape, the performance of projects plays a pivotal role in determining an organization’s success. Successfully executed projects gave numerous benefits, including heightened efficiency, elevated customer satisfaction, and an enhanced reputation. Nonetheless, achieving superior project performance comes with its fair share of challenges.

Among the crucial elements influencing project success, the composition of the project team and their skill sets stand out as key factors. The right mix of skills within the team is essential for tackling project complexities and delivering results that exceed expectations. By recognizing the significance of skill diversity and actively addressing skill gaps, organizations can ensure a higher likelihood of achieving project objectives and staying ahead in the competitive market.

Skills-Based Project Staffing

Building project teams based on skills is a fundamental aspect of project management. When team members possess the right mix of expertise and knowledge, projects are more likely to be efficient and successful. The correct skill mix ensures that the team can handle various project tasks effectively, minimizing delays and potential roadblocks.

For instance, in a software development project, having a balanced team with experts in required programming languages, design, and testing can lead to faster development cycles and better-quality output. On the other hand, a team lacking the necessary skills may struggle to deliver on time and within budget.

Moreover, based on Deloitte, companies that match the right talent and skills to tasks effectively are 52% more likely to be innovative and 57% more likely to be agile.

Thus, a skills-based approach to project staffing can significantly contribute to an organization’s overall competitiveness and adaptability in today’s dynamic and rapidly changing business landscape. By aligning team members’ strengths and proficiencies with the specific demands of a project, organizations can not only enhance their project outcomes but also foster a culture of continuous improvement.

Identifying Skills for Project Requirements

To optimize the team’s skill composition, a thorough assessment of the required team’s abilities becomes imperative. The process involves identifying key skills that directly contribute to the achievement of project objectives—an essential and decisive phase.

This step is where AI-driven analytics can significantly augment the process. AI algorithms can scan through project requirements and analyze the skills needed based on keywords and contextual understanding. This involves comparing the skills mentioned in the project description with those present in candidate profiles, resumes, or employee databases. AI can quickly identify matches, helping to ensure that the right skills are available for the project.

Moreover, AI can perform semantic analysis to understand the nuanced skills required for a project. Semantic analysis empowers AI to go beyond simple keyword matching when identifying skills for project requirements. It enables understanding of skill context, recognizing synonyms and variations, mapping hierarchical relationships, and adapting to evolving industry trends. By comprehending implied skills, accommodating industry jargon, and considering complex skill combinations, semantic analysis ensures accurate skill-to-project matches, ultimately enhancing staffing decisions and project success.

Utilizing historical project data and performance metrics, AI algorithms can swiftly analyze the proficiency of individual team members in various areas, highlighting areas of strength and those that could benefit from reinforcement. This data-driven approach ensures that the selection of skillsets aligns precisely with the project’s demands, enhancing the overall capability of the team.

Optimizing Staffing for Project Success

Project staffing is the process of strategically assigning the right people to the right projects. According to Deloitte, 83% of leaders believe that leveraging employees’ skills data creates benefits for both the organization and its employees.

By considering each team member’s skill sets and experience, project managers can assemble teams that are tailor-made for specific projects. This not only improves project outcomes but also enhances employee satisfaction and engagement.

Additionally, taking into consideration employee availability and workload can prevent burnout and the inability to meet project deadlines. By factoring in these aspects, project managers can ensure a balanced distribution of tasks, promoting a healthier work environment, sustained productivity, and successful project completion.

In this era of technological advancement, AI and Talent Analytics can play a valuable role by providing data-driven recommendations for project staffing, considering individual skills, current workloads, and historical project performance. By factoring in these aspects, project managers can ensure a balanced distribution of tasks, promoting a healthier work environment, sustained productivity, and successful project completion.

Empowering Skills Development

According to Gartner, 64% of IT professionals consider the skills shortage to be the foremost challenge limiting the adoption of transformative technologies. Talent Analytics plays a vital role in bridging skill gaps.

By analyzing data on employees’ skills and experiences, organizations can identify potential candidates for projects based on existing or adjacent skills. For instance, if a project requires expertise in a specific programming language that the current team lacks, Talent Analytics can identify individuals with adjacent skills that can be quickly upskilled to meet the project’s requirements.

Sometimes, organizations may face a challenge where specific skills needed for a project are not readily available within the team. In such cases, it is crucial to empower employees through skill development initiatives. Investing in employees’ growth and upskilling not only meets project demands but also fosters a culture of continuous learning within the organization.

By providing training opportunities and resources, employees can acquire new skills that align with project requirements. Moreover, a culture that encourages skill development attracts top talent and retains skilled employees, making the organization more competitive in the long run.

Incorporating personalized learning initiatives further enhances the team’s capabilities. By offering tailored training opportunities and resources, employees can acquire new skills that precisely align with the specific project requirements. This personalized approach not only boosts individual growth but also fosters a culture that values skill development, making the organization more attractive to top talent. Moreover, when skilled employees are encouraged and supported in their professional development, it leads to higher retention rates, ensuring the company’s long-term competitiveness in the market.

Monitoring and Evaluating Project Performance

Setting measurable performance indicators for projects is essential to track progress and identify areas for improvement. Regularly monitoring project performance allows teams to make necessary adjustments and ensure that the project stays on track.

Talent Analytics comes into play once again when evaluating project performance. By comparing project outcomes with the skill sets of the team members and staffing decisions, organizations can gain valuable insights into the impact of skill development and staffing optimization on project success.

AI’s proficiency in aggregating and integrating data from diverse sources, including project management tools, collaboration platforms, and performance metrics, lays the foundation for comprehensive insights. Complementing this, Talent Analytics meticulously captures skill-related data, offering a panoramic view of project progress and creating a synergistic approach that informs strategic decision-making.

AI’s capabilities extend to anomaly detection, where its algorithms identify deviations in project performance to predict and mitigate risks. This proactive identification of anomalies enables taking timely actions to ensure that projects maintain their trajectory. The collaboration of AI and Talent Analytics transforms project monitoring and evaluation, offering predictive insights and skill-driven decisions that elevate project outcomes.

Achieving superior project performance requires a proactive approach to skill development and staffing optimization. By assembling project teams based on skills, identifying essential skills, and leveraging Talent Analytics to bridge skill gaps, organizations can significantly enhance project efficiency and success.

Investing in skill development empowers employees and ensures the availability of necessary expertise for future projects. Continuous learning contributes not only to individual growth but also to the overall growth of the organization.

EDLIGO Talent Analytics helps organizations assess the impact of skill development and staffing decisions on project outcomes. The platform’s analytics provide actionable insights into project performance, allowing businesses to identify trends, strengths, and weaknesses. With this data-driven approach, organizations can continuously improve project management strategies and enhance overall project performance.