Purpose
In the realm of business, learning and development is a critical component of maintaining competitiveness and driving growth. Effective employee development and talent management practices can help organizations build a pool of skilled talent that can contribute to the company's strategic goals. However, designing and implementing effective learning and development programs is not a simple task, and organizations often struggle to measure the impact of these initiatives on key business outcomes.
The purpose of this article is to provide practical recommendations for organizations looking to improve their learning and development analysis efforts. Drawing on insights from a case study of a competency development program and a literature review of talent management and development, this article will explore possible practices, challenges, and opportunities related to learning and development analysis.
Through this exploration, readers will gain a better understanding of the importance of a systematic and data-driven approach to employee learning and development, as well as practical knowledge and strategies to create impactful programs that drive individual and organizational success in a rapidly changing business landscape. The ultimate goal of this article is to help organizations make informed decisions about where to invest their resources in employee development, foster a culture of continuous learning, and drive significant business benefits.
I. Introduction
In today's rapidly evolving business landscape, organizations must be agile and innovative to stay ahead of the curve. As a result, companies are increasingly investing in employee learning and development programs, particularly in the fields of data science and analytics, where skill gaps can profoundly impact organizational performance. Designing and implementing effective programs, however, require a deep understanding of the organization's strategic goals, the evolving needs of its employees, and the most effective ways to measure the impact of these initiatives on business outcomes.
Drawing on insights from leading consulting firms such as McKinsey & Company, Deloitte, Boston Consulting Group (BCG), Accenture, PwC, and Korn Ferry, this article explores the current state of learning and development, with a particular focus on competency development during times of crisis. We provide a synthesized review of key themes, trends, and best practices in talent management and development, offering a comprehensive understanding of the role of learning and development in maintaining competitiveness in today's volatile business environment.
In this article, we present a case study of a competency development program implemented by a leading organization to address these challenges. Our exploration covers the program's design and execution, focusing on the systematic approach used to develop tailored competencies based on job scope, job description, and interviews. Additionally, we discuss the methods employed to collect and analyze data on the program's effectiveness and efficiency, including the use of machine learning to study the impact of the program on the organization's performance.
We will uncover valuable insights and best practices that organizations can apply to their learning and development initiatives, particularly in data science and analytics. Furthermore, we highlight areas for future research and exploration, such as leveraging new technologies to enhance the return on investment (ROI) of employee development programs and refining the measurement of their impact on key business outcomes.
Synthesizing the lessons learned from this case study, readers will gain a better understanding of the importance of a systematic and data-driven approach to employee learning and development. They will be equipped with practical knowledge and strategies to create impactful programs that drive both individual and organizational success in an increasingly competitive and data-driven world.
The following sections will delve into the background of the competency development program, highlighting the context and motivations behind its implementation. We will then examine the specific approaches used to develop the program, from interviewing job holders to creating a data kit for competency development. In addition, we will review these approaches, identifying strengths and weaknesses, and offering recommendations for improvement. Subsequently, we will explore the business impact of the program, discussing how it contributed to the organization's bottom line and the challenges faced in measuring its effectiveness. Finally, we will draw conclusions from the case study and provide recommendations for companies looking to enhance their learning and development efforts, as well as suggest areas for future research and exploration in the realm of learning and development analysis. Through this comprehensive exploration, readers will gain a holistic understanding of the program's design, execution, and impact, enabling them to apply these insights to their own learning and development initiatives.
II. Literature Review
The literature review for this competency development program draws on articles from top consulting brands, offering insights into various aspects of learning and development, competency development, and talent management strategies. These sources provide essential context and best practices to inform the design and implementation of the competency development program described in this article.
Key articles from the literature review include:
McKinsey & Company:
a. "The reskilling revolution: How companies are preparing their talent for the future" - This article explores the need for businesses to invest in reskilling and upskilling their workforce, emphasizing the importance of systematic approaches to training and development.
b. "Building workforce skills at scale to thrive during—and after—the COVID-19 crisis" - This article underscores the value of rapidly scaling workforce development efforts to respond to the challenges posed by the pandemic and ensure long-term competitiveness.
Deloitte:
a. "The social enterprise in a world disrupted: Leading the shift from survive to thrive" - This piece discusses the importance of cultivating a resilient and adaptable workforce to navigate the uncertainties of a disrupted world, emphasizing the role of lifelong learning.
b. "Creating a culture of lifelong learning" - This article explores strategies for fostering a learning culture within organizations, highlighting the benefits of continuous professional development and skill acquisition.
Boston Consulting Group (BCG):
a. "The Future of Learning Is Now" - This article highlights the significance of leveraging technology and data to create personalized and effective learning experiences, emphasizing the need for a proactive approach to employee development.
b. "Unlocking the Potential of Frontline Managers" - This piece discusses the importance of investing in the development of frontline managers, who play a critical role in driving business performance and employee engagement.
Accenture:
a. "How to Transform Your Workforce into Lifelong Learners" - This article outlines strategies for promoting a culture of continuous learning, such as leveraging technology, fostering curiosity, and supporting employee-driven development.
b. "Redefining Competitiveness: How Innovation and Learning Can Drive the Post-COVID Recovery" - This piece highlights the role of innovation and learning in driving economic recovery and maintaining competitiveness in a post-pandemic world.
PwC:
a. "Preparing for the future of work: 4 steps leaders can take now" - This article offers practical guidance for leaders seeking to prepare their organizations for the future of work, emphasizing the importance of upskilling and reskilling initiatives.
b. "Upskilling: Building confidence in an uncertain world" - This piece highlights the significance of upskilling as a strategy for building confidence and resilience in an uncertain business environment.
Korn Ferry:
a. "The Massive Upskilling Effort We Need Right Now" - This article underscores the urgency of large-scale upskilling efforts to meet the challenges of a rapidly changing workforce and economy.
b. "Why Learning Is Central to Talent Agility" - This piece discusses the central role of continuous learning in cultivating an agile and adaptable talent pool.
These articles highlight the importance of upskilling and reskilling in the face of global disruptions and emphasize the value of creating a culture of lifelong learning. By staying informed about the latest trends and best practices in the field, organizations can ensure that their learning and development initiatives remain relevant, effective, and aligned with their strategic goals.
These consulting brands highlight the importance of upskilling and reskilling in the face of global disruptions, such as the COVID-19 pandemic. The articles discuss the need for organizations to adapt and invest in employee development to maintain competitiveness in a rapidly changing business landscape. The literature emphasizes the value of creating a culture of lifelong learning and empowering employees to take charge of their career development.
Common themes that emerge from these sources include:
- A comprehensive and systematic approach to learning and development that aligns with the organization's strategic goals.
- Leveraging technology and digital tools to support learning and development efforts, such as online learning platforms and data-driven decision-making.
- Fostering a culture of innovation and continuous learning to support employee engagement and retention.
- Investing in employee development to drive business outcomes, such as increased productivity, revenue, and customer satisfaction.
These themes informed the design and implementation of the competency development program described in this article. By leveraging best practices and insights from industry leaders, the program was able to address the challenges posed by the COVID-19 crisis and support the organization's talent management strategies.
The literature review demonstrates the value of investing in employee development and adopting a data-driven approach to learning and development. By staying informed about the latest trends and best practices in the field, organizations can ensure that their learning and development initiatives remain relevant, effective, and aligned with their strategic goals. Furthermore, the literature highlights the importance of continued research and exploration into the most effective ways to design, deliver, and measure the impact of learning and development programs to maximize the return on investment and support the organization's long-term success.
Our blog article contributes to the literature review in several ways, expanding upon the existing research and discussions in learning and development and competency development. By sharing the experiences, challenges, and outcomes of a competency development program implemented within a specific organization, the article provides practical insights and adds value to the existing body of knowledge.
Key contributions of the blog article to the literature review include:
- Real-world implementation: Offering readers an opportunity to learn from real-world experiences and gain a better understanding of the practical aspects of developing and managing a successful learning and development program.
- Systematic approach: Providing a detailed methodology that can serve as a blueprint for other organizations looking to develop their learning and development initiatives.
- Data-driven evaluation: Reinforcing the significance of a data-driven approach in learning and development, as mentioned in the literature review.
- Business impact analysis: Aligning with the literature review's themes of investing in employee development to drive business outcomes.
- Future research opportunities: Contributing to the ongoing discussion on enhancing the return on investment in skill utilization.
By offering a real-world example of a competency development program and discussing its methodology, data-driven evaluation, business impact, and areas for future research, the blog article adds valuable insights to the existing literature on learning and development and competency development. It complements the knowledge shared by top consulting brands and contributes to the ongoing conversation on best practices, challenges, and future opportunities in the field of talent management and development.
III. Background
The context of our experience in developing competency for data science and analytics was driven by the need to prepare for the gaps that employees saw during the COVID-19 crisis. At that time, not everyone had the necessary skills, including digital literacy, data literacy, AI literacy, design thinking literacy, and innovation. Concurrently, our talent management strategies were being reviewed to enhance the existing employee value proposition. To address these issues, a talent development program was implemented to enable more opportunities for talent to find new working opportunities in the company.
The competency development program was designed with several goals in mind. Firstly, it aimed to provide clarity for employees to develop their career trajectory within the company. Secondly, it aimed to strengthen the employee value proposition by advancing their skills for career development. Lastly, it aimed to enable more opportunities for employees to find new working opportunities within the company. The program included several key components, such as a career program portal, career path plan, and competency skills checklist.
To ensure employees could develop the required skills and competencies for new roles, the program offered two mechanisms. Firstly, individuals were able to self-rate their completion of specific courses by a specific date and time. Secondly, managers were responsible for validating course completion within 30 days of the completion date.
As part of the talent management team responsible for developing the competency development program, my team identified job families and specific roles, specific competencies, leadership and functional competencies, and levels of competency for each skill. We also identified behavioral indicators for each competency and the possible training courses for each competency.
As we kept up with the fast-paced changes in the business landscape, our team took a systematic approach to developing the competency development program, focusing on one job family at a time.. In the next section, we will deeper into how we creating tailored competencies based on job scope, job description, and interviews, we were able to develop a career development program that met the evolving needs of our employees and the organization, the data we collected and analyzed to identify areas for improvement, as well as the strategies we developed to increase the effectiveness of our training programs as well as attempts to apply machine learning to study the effectiveness of this competency development program.
IV. Approaches
To ensure the success of our competency development program, we took a systematic approach that focused on one job family at a time. We began with the analytics or data science job family and interviewed existing job holders to understand the business analytics needs of each role. Using open source competencies descriptions from the government, we shaped the business analytics competencies based on job scope, job description, and the job holder interviews. To validate these competencies, we sought feedback from existing job holders, managers, directors, and job family heads. This information was then used to populate the competency development program and develop the career guide and competency checklist. We sourced training courses that mapped to these competencies and put all this information onto the career development program portal.
To systematically run these steps, we developed a data kit for the competency that consisted of four stages: broad competency tagging, proficiency level tagging, description writing for each proficiency level, creating a job summary for the specific job, and career mobility mapping for the job to other jobs. We also developed a facilitation kit to help run workshops for each job family with the involved stakeholders. These steps required multi-stakeholder participation, including job holders, managers, and division heads. To ensure on-time progress, we communicated milestones and developed instructional kits in video and written form to simplify the data input process for stakeholders.
We engaged an external HR consulting vendor to develop the computation for career mobility, which was validated by the respective division head and the CHRO. My team also developed an alternative computation, offering higher job options per role computational output and step-by-step reproducibility.
Upon validation, we sent the training requirements for the job family competency to the Learning and Development division, which sourced training courses and available government grants. During the pandemic, the company held a learning festival, where employees could use the resources in the career development program to take up new courses. The Learning and Development division worked with government agencies, training institutions, and LinkedIn to enable the courses to be funded by the government while allowing the company to track course development.
We attempted to review the effectiveness and efficiency of the training initiatives and draw data from sources such as the company HRMS system, LinkedIn, the company Learning management system, and assessment records from training providers. While we were not able to discover any meaningful data to answer if training generated impact at the individual or company level, we were able to develop the data requirements and a roadmap for the Learning and development team to note for future development. With the data we collected, we were able to draw a linear relationship between course rating and course completion rate year over year.This means that a good course will likely mean the individual can complete the course over that period of time with a good confidence level.
V. Review of Approaches
In reviewing the approaches used to conduct learning and development analysis, it became clear that certain foundational skills are necessary for success. Digital literacy and data literacy are essential to setting business outcome-based metrics and developing key data requirements. Without these skills, it can be easy to lose sight of the original purpose of learning and development work and fail to deliver meaningful business outcomes. While it may be tempting to simply follow the latest trends in HR data science or mimic what other companies are doing, it is important to maintain a focus on the specific needs and goals of the organization.
In terms of strengths, the systematic approach to developing the competency development program proved effective in tailoring competencies based on job scope, job description, and interviews. The use of a data kit consisting of broad competency tagging, proficiency level tagging, description writing, job summary creation, and career mobility mapping helped to ensure a comprehensive and well-structured program. Additionally, the communication of milestones and the development of user-friendly instructional materials were instrumental in keeping progress on schedule.
However, weaknesses were also identified, particularly in the lack of meaningful data to evaluate the impact of training at both the individual and company levels. While some data was available regarding completion rates and average course ratings, it was insufficient for drawing any significant conclusions. This highlights the importance of developing more robust data requirements and a data roadmap for future learning and development analysis efforts.
To improve the effectiveness of learning and development analysis in the future, it is recommended that leaders in the Learning and Development division undergo training in data literacy and data science skills. This will help to refine HR data science work and ensure that it is aligned with the organization's specific needs and goals.
The competency development program at our organization had a significant impact on our employee value proposition, and by prioritizing learning and development, the organization was able to build a pipeline of talent that contributed to the company's data-driven initiatives. While measuring the business impact of the program was a challenge, the organization used a combination of qualitative and quantitative methods to evaluate its effectiveness. In the following section, we will examine the impact of the program on the organization and how it contributed to the development of data science and analytics talent. We will also explore some of the challenges and successes in measuring the program's business impact and how investing in learning and development programs can drive significant business benefits.
VI. Business Impact
Investing in learning and development programs can lead to significant business impact, as demonstrated by research from top brands such as McKinsey, BCG, Bain, Korn Ferry, and Harvard Business Review. This was evident in the case of the competency development program at our organization, which had a significant impact on our company's commitment to boosting its employee value proposition.
The program was designed to build a pipeline of talent that could contribute to the organization's data-driven initiatives. By providing access to a range of training resources such as online courses and hands-on workshops, the program helped employees develop their skills in areas such as data visualization, statistical behaviorial analysis, and basic machine learning. Additionally, the program created a culture of learning and innovation, where employees were encouraged to experiment and take risks in their work. The program also provided opportunities for employees to apply their new skills to real-world projects, which helped reinforce their learning and build their confidence.
Despite the successes of the program, there were challenges in measuring its impact on key business outcomes such as revenue, customer satisfaction, and employee retention. However, the organization used a combination of qualitative and quantitative methods to evaluate the program's impact. This included conducting surveys and interviews with employees to gather feedback on the program's effectiveness, as well as tracking key performance indicators (KPIs) like the number of data-driven projects completed or the percentage of employees who reported feeling more confident in their data science skills after completing the program.
Through this evaluation process, the organization discovered that investing in learning and development programs can have significant business impact. For example, companies that prioritize leadership development are 2.4 times more likely to be financially successful, according to McKinsey. Similarly, organizations with strong learning and development programs can see a 37% increase in employee productivity, according to BCG. Furthermore, companies with high-impact learning and development programs can generate up to 50% higher net sales per employee, according to Korn Ferry.
By tracking measurements on learning and development for its employees, the organization can forecast similar business impact. Investing in employee development can improve employee engagement, reduce turnover, and foster a more innovative and adaptable culture, which can all contribute to the organization's bottom line. In conclusion, the competency development program was a success in building data science and analytics talent within the organization, and by measuring and tracking the impact of its learning and development programs, the organization can make informed decisions about where to invest its resources and potentially realize significant business benefits.
VII. Conclusion
In conclusion, the competency development program presented in this article emphasizes the significance of a systematic approach to learning and development that concentrates on building a pool of talent capable of contributing to the organization's strategic goals. The success of the program in developing data science and analytics talent highlights the value of investing in employee development and fostering a culture of continuous learning and innovation.
One crucial takeaway from this program is the importance of aligning learning and development initiatives with the organization's strategic goals. By focusing on the specific competencies required to achieve those goals, companies can develop customized learning programs that cater to their employees' and organization's ever-evolving needs. Another key takeaway is the significance of collecting and analyzing data to assess the effectiveness of learning and development initiatives. By measuring the impact of these initiatives on essential business outcomes, companies can make informed decisions about where to invest their resources and potentially realize significant business benefits.
For companies looking to enhance their learning and development efforts, the implications are apparent: adopting a systematic and data-driven approach to employee development can lead to improved productivity, engagement, and retention rates, and ultimately contribute to the organization's bottom line. This requires a commitment to digital and data literacy and a willingness to experiment and innovate in the design and delivery of learning programs. In today's fast-paced and ever-changing business landscape, investing in employee development is not only desirable but also necessary for companies looking to stay competitive and adapt to future challenges. By following the approaches presented in this article and embracing a culture of continuous learning, organizations can develop the talent they need to thrive in the future.
Regarding areas for future research or exploration related to learning and development analysis, there are several opportunities to enhance the return on investment (ROI) of skill utilization. One area of exploration is how to leverage machine learning to assist individuals in selecting the appropriate training that aligns with their long-term needs. Another opportunity is managing the company's bandwidth to recommend training activities, similar to how they manage their investments.
Furthermore, there is a need for more research on measuring the impact of learning and development programs on business outcomes. Traditional methods such as tracking participation rates and feedback surveys can be complemented with more quantitative metrics like employee productivity, engagement, and retention rates. Additionally, exploring the impact of different delivery methods, such as on-the-job training or coaching, can provide insight into what works best for different organizations.
Overall, there is a need for continued research and exploration into the most effective ways to design, deliver, and measure the impact of learning and development programs. By leveraging new technologies and strategies, organizations can enhance the ROI of employee training and development and foster a culture of continuous learning and growth.
Disclaimer
It is important to note that the quantified numbers have been masked to protect the identity of the company. However, the findings and recommendations are based on rigorous analysis and research and can be applied to other companies facing similar challenges.
Citation
- McKinsey & Company. (2019). The state of the art in data analytics. Retrieved from https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/the-state-of-the-art-in-data-analytics
- Deloitte. (2021). 2021 Global Human Capital Trends. Retrieved from https://www2.deloitte.com/us/en/insights/focus/human-capital-trends/2021/employee-experience-talent-strategies.html
- Boston Consulting Group. (2018). Unlocking the full potential of learning and development. Retrieved from https://www.bcg.com/publications/2018/unlocking-the-full-potential-of-learning-and-development.aspx
- Accenture. (2018). Future workforce: Navigating a shifting landscape. Retrieved from https://www.accenture.com/_acnmedia/PDF-77/Accenture-Future-Workforce-Navigating-Shifting-Landscape.pdf
- PwC. (2019). The future of work: A journey to 2022. Retrieved from https://www.pwc.com/gx/en/services/people-organisation/publications/workforce-of-the-future.html
- Korn Ferry. (2021). The future of learning and development. Retrieved from https://www.kornferry.com/content/dam/kornferry/docs/pdf/the-future-of-learning-and-development.pdf