South Africa is short of academic statisticians: why and what can be done

South Africa faces a shortage of academic statisticians due to various factors including limited funding, inadequate training programs, and brain drain. To address this challenge, initiatives such as enhanced education funding, curriculum reforms, and retention strategies are essential in nurturing and retaining skilled statisticians to meet growing demand and support national development.

Statisticians are able to assess and analyse data, crucial skills in today’s world. Solstock

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463 exabytes of data will be created each day globally – that’s the equivalent of 212,765,957 DVDs per day.

Absolutely, data's value is unlocked by experts who can collect, analyze, and interpret it effectively. Statisticians play a vital role in this process, as they are trained to make sense of complex datasets. Their analyses serve as invaluable guides for organizations and governments, informing sensible policy decisions.

It's noteworthy that both "data scientist" and "statistics lecturer" are recognized on the South African government's critical skills list. This underscores the significance of statistical expertise in today's data-driven world. With the exponential growth of data, there's an increasing demand for skilled analysts. Consequently, there's also a growing need for academic statisticians to train the next generation of data professionals.

However, there's a challenge: the surge in industry demand for skilled analysts often draws graduates away from academia. This presents a dilemma, limiting academia's capacity to produce more statisticians and meet the rising demand for statistical expertise.

Addressing this challenge requires concerted efforts to attract and retain statisticians in academia. This could involve incentivizing careers in academia, offering competitive salaries, providing opportunities for research and professional development, and fostering collaboration between academia and industry to ensure that academic programs remain relevant to the workforce's needs.

By investing in the development of academic statisticians, South Africa can strengthen its capacity to meet the growing demand for statistical expertise. This will not only support the country's data analysis needs but also drive innovation and progress in decision-making processes.

A consortium of academic statisticians representing South African universities has produced a comprehensive discussion paper aimed at tackling the capacity crisis within academic statistics. Through meticulous analysis, the group has pinpointed key contributors to this crisis, highlighting the absence of collaboration among academics across diverse statistical disciplines. Furthermore, the paper outlines a strategic framework designed to enhance both the caliber and quantity of doctoral candidates in various statistical fields. This initiative promises to fortify statistical education and research in South Africa, fostering a new generation of skilled professionals poised to address complex challenges in the field.

What’s in a name?

In academia, a multitude of "statistical" fields have emerged, encompassing operations research, data science, business mathematics, econometrics, and biostatistics, among others. However, a notable division has developed over time between researchers and lecturers specializing in applied statistics and their counterparts in mathematical or theoretical statistics.

This schism reflects differing focuses within the discipline, with applied statisticians often directing their efforts toward practical problem-solving and real-world applications, while those in mathematical or theoretical statistics delve into the fundamental principles and mathematical underpinnings of statistical theory.

This divide, while reflecting specialization and divergent research interests, can also present challenges, such as limited collaboration and interdisciplinary exchange between practitioners in different areas of statistical inquiry. Bridging this gap and fostering greater interaction and collaboration across various statistical fields could lead to valuable insights and advancements in statistical theory, methods, and applications.

Statistics departments in South African universities are situated within diverse faculties, including commerce, natural science, engineering, and health sciences. In some cases, they operate as stand-alone entities, such as biostatistics departments within health sciences or psychometrics departments within social sciences. Additionally, certain institutions opt to amalgamate statistics departments with related disciplines like operations research, data science, mathematics, or actuarial science.

This varied organizational structure reflects the interdisciplinary nature of statistics and its application across a wide range of fields. While the specific placement of statistics departments may differ from one university to another, they play a critical role in advancing statistical research, education, and application within their respective academic domains.

As highlighted by a discussant in our paper, it is imperative for statisticians to transcend disciplinary boundaries and instead focus on identifying commonalities across their respective fields. By doing so, academic statisticians can forge stronger connections and collaborations, fostering a network of expertise that transcends imagined divisions. This collective effort can provide invaluable support for the development of young academics, enabling them to benefit from a rich tapestry of knowledge and experience across various statistical disciplines. Ultimately, by coming together in this manner, statisticians can amplify their impact and drive innovation in statistical research and education.

The sentiment expressed by the array of statisticians consulted, including those working outside academia in diverse industries, echoes the importance of breaking down disciplinary barriers within the field. One practitioner noted that the naming conventions of degrees might inadvertently restrict the pool of industry professionals capable of offering valuable guidance and mentorship to PhD candidates in statistics. For instance, a doctoral candidate specializing in econometrics might not recognize the potential for support and mentorship from a biostatistician, despite their wealth of relevant expertise. This underscores the need for greater awareness and recognition of the broad spectrum of skills and knowledge within the statistical community, enabling fruitful collaborations and mentorship opportunities across different specialties.

Assessment

In our discussions, we also recognized the necessity of standardizing assessment criteria for statistics PhD programs in South Africa. Presently, each university establishes its own set of criteria, leading to inconsistencies in evaluation methods. While some may argue that standardizing assessment for inherently creative outputs, such as novel and innovative ideas, could be overly prescriptive, we contend that a semi-flexible assessment rubric is essential.

Implementing a semi-flexible assessment framework would not only facilitate the development of high-quality doctoral graduates but also provide early-career supervisors with clear guidelines for setting appropriate goals for their students. By establishing a common framework, universities can ensure consistency and rigor in the evaluation process while still allowing room for creativity and innovation among PhD candidates. This approach aims to strike a balance between standardization and flexibility, ultimately enhancing the quality and relevance of statistics PhD programs in South Africa.

Absolutely, an assessment rubric serves as a crucial tool for formative assessment in statistics PhD programs. It provides students with clear expectations regarding the criteria for evaluation, enabling them to monitor their progress effectively. Moreover, a standardized assessment rubric promotes consistency and fairness in the assessment of statistics research, ensuring that all candidates are evaluated using the same criteria.

By adopting a standardized and transparent rubric, institutions across South Africa can maintain consistent standards for their statistics PhD candidates. This not only enhances the quality and integrity of the assessment process but also facilitates the mobility of graduates across institutions and industries throughout the country. Graduates equipped with a common understanding of evaluation criteria are better prepared to transition seamlessly between academic and professional environments, thereby contributing to the advancement of statistical research and practice nationwide.

Supervisor-student relationship

Indeed, the support and mentorship provided to both PhD candidates and their supervisors play a critical role in the success of a doctoral program. Research across disciplines underscores the significance of the relationship between a PhD candidate and their supervisor. However, gaps exist in how this relationship is nurtured and supported.

Early-career supervisors may lack the necessary guidance and resources to foster a healthy supervisor-student relationship. They may not fully comprehend the complexities involved in this dynamic, nor possess the skills required to effectively mentor their students. This gap in mentorship can hinder the professional and academic development of both PhD candidates and supervisors.

Addressing this challenge requires targeted support and training initiatives aimed at equipping supervisors with the tools and knowledge needed to cultivate productive and supportive relationships with their students. Providing resources, workshops, and mentorship programs can empower supervisors to navigate the intricacies of mentorship effectively, ultimately enhancing the quality and outcomes of the doctoral experience for all involved.

Collaboration is undeniably vital, especially for early-career academics, including those who supervise postgraduates. In South Africa, many seasoned supervisors are approaching retirement or have already retired. It's imperative to establish networks that enable newer supervisors to support each other and glean insights from experienced counterparts while they remain available to offer assistance. Such networks not only facilitate knowledge exchange but also serve as avenues for identifying external examiners for students' work and for fostering research networks within specific fields of expertise.

Moreover, an identified issue is that doctoral candidates and their early-career supervisors may struggle to navigate available funding opportunities due to a lack of expertise. Here, the importance of networking and collaboration becomes even more pronounced. By connecting with peers and experienced professionals, both candidates and supervisors can tap into available resources more effectively. These collaborative efforts not only enhance access to funding but also promote knowledge sharing and skill development, ultimately enriching the academic and research landscape in South Africa.

Next steps

It's commendable that you've developed a guiding rubric for early-career supervisors in statistics, particularly after consulting with a diverse range of stakeholders including senior supervisors, young academics, and industry statisticians. As far as you're aware, this initiative marks a pioneering effort in the field of academic statistics.

This rubric stands out for its approach, as it's not meant to be prescriptive. Instead, it serves as a flexible guide encompassing criteria deemed crucial for the development of new researchers. While some supervisors may opt to utilize the entire rubric to support various aspects of their role, others, who are more experienced, might selectively use specific sections, such as the assessment criteria.

By offering this adaptable framework, you're empowering supervisors to tailor their mentorship approach to suit their own preferences and the needs of their students. This flexibility ensures that the rubric remains a valuable resource for a wide range of supervisors across different stages of their careers, ultimately fostering a nurturing and supportive environment for emerging researchers in the field of statistics.

Source: theconversation