Identifying talent that can deal with job complexity

Job complexity refers to the information-processing demands placed on employees (Hunter et al., 1990).

Levels of work or the competency hierarchy associated with formal leadership are associated with greater complexity due to the demands placed on leaders to gather, integrate, and make sense of several pieces of information, while also coming up with creative solutions to new problems (Judge et al., 2004).

The Stratified Systems Theory (Jacques, 1989) holds that as employees move up the ranks in organisations, they will be faced with increasing levels of complexity and challenges in decision-making. This would require that employees have the necessary skills and cognitive ability to deal with this increasing complexity. However, the information-processing demands associated with jobs are much broader than what is often articulated with levels of work. Some areas of specialisation, independent of the level of work, are highly complex. For example, the work of a physicist might be just as, if not in some respects more complex than that of an executive (National Center for O*NET Development, 2021). Job complexity is, therefore, a construct that is broader than just levels of work.

Historically, organisations wanted to identify talent that can deal with complexity for succession planning or leadership development. In the changing world of work, we however see complexity as a function of many different levels within organisations and the need arises for organisations to identify talent that can effectively manage complexity across different levels. Various aspects of the new world of work, like job automation, cross-functioning teams, project-based contracting, and hybrid organisations impact on the complexity of the tasks that employees must perform in their daily work. We can no longer assume that complexity will only increase along a staircase career trajectory. Indeed, the Covid-19 pandemic has shown us that employees across all levels had to adapt to new and unfamiliar challenges rapidly (Deloitte, 2021). In fact, organisations that will continue to thrive in unfamiliar and changing circumstances are those that can rely on the ability of their talent to make effective decisions and can anticipate future trends (Deloitte, 2021).

Meta-analytical evidence suggests that job complexity moderates the relationship between cognitive ability and job performance (Salgado et al., 2019). Stated differently, high cognitive ability greatly enhances employees' training and job performance (Schmidt, 2016) when daily tasks require the ability to:

• make sense of complex information,

• derive connections and patterns from seemingly unconnected pieces of information,

• be comfortable with unfamiliar information or situations,

• evaluate different pieces of information and different approaches to problem solving to identify the most appropriate course of action, make quick and effective decisions,

• analyse the outcomes of their decisions, and

• enjoy solving difficult problems.

Whether organisations are selecting applications or determining existing employees’ suitability for specialist or managerial track roles, they stand to benefit from knowing prospective high-potential employees' cognitive ability, which in turn provides evidence of their ability to deal with complexity.

Introducing The Hogan Business Reasoning Inventory

The Hogan Business Reasoning Inventory (HBRI) is an assessment that identifies how well candidates can work with pieces of information to solve problems.

The information is oftentimes new and unfamiliar and provides an indication of how well a candidate can make links between pieces of information in solving problems. Generally, persons who score higher on business reasoning:

Are comfortable working with wide arrays of data and information

Consider their options and gather additional information where needed

Quickly come up to speed with problems

Show a willingness to revise their opinions when new data becomes available

Resist rushing to decisions and rather focus on effectively solving problems

Higher scorers on qualitative reasoning (one of the assessment’s two primary scales) seem able to find meaning in seemingly messy data, while higher scores on quantitative reasoning (the other primary scale) can understand the essential aspects of a problem quickly.

The assessment also indicates a person's cognitive style – i.e., how they think about and solve problems. Those who score high on both qualitative and quantitative reasoning are considered critical thinkers and they tend to contextualise problems correctly in terms of the short- and long-term benefits of their solution, and then solve them effectively.

The HBRI in action

In a study that JVR conducted within the financial industry (N = 123 leaders) we correlated scores on the HBRI with scores on the Cognitive Processing Profile (CPP), an assessment oftentimes associated with levels of work and used when selecting people for complex roles. We observed that persons who score higher on the HBRI will be able to effectively investigate new information and broadly examine situations or problems (r = .44). They are likely to effectively structure the information in such a manner that they can form alternative hypotheses about problems and adapt these hypotheses as new information becomes available (r = .44). They likely also grasp new information quickly and can effectively conceptualise the outcome of their decisions (r = .43).

In a case study that Hogan conducted with a client in the pharmaceutical arena (Hogan Assessment Systems, 2019), leaders (N = 93) who scored high on the HBRI were better at making the right decision (r = .29), solving problems (r = .26), showed more initiative (r = .26), and had stronger accounting (r = .39) and financial forecasting skills (r = .36).

For another Hogan case study (Hogan Assessment Systems, 2019), within the healthcare supply manufacturing arena, job performance and HBRI data were collected for 328 sales representatives. Those participants who scored higher on the HBRI were more likely to be rated higher for dealing with complex concepts (r = .17), effectively gathering and compiling information from a variety of sources (r = .15) and making good decisions (r = .15).

We can therefore see that an assessment like the HBRI can provide insight into whether your talent can:

• effectively deal with complex information,

• see the interconnections between pieces of information and make sense of these,

• identify different approaches to problem solving to choose the most appropriate course of action,

• make quick and effective decisions,

• evaluate the appropriateness of their decisions, and

• adjust their course of action appropriately.

When used in combinations with a personality assessment, one could also identify how comfortable your talent will be in dealing with unfamiliar or new situations, how open they would be to new approaches in doing their work, and to what extent they would enjoy being faced with difficult challenges.

References:

Deloitte. (2021). 2021 Deloitte South Africa Human Capital Trends: The social enterprise in a world disrupted – Leading the shift from survive to thrive. /us/en/insights/focus/human-capital-trends/2021/social-enterprise-survive-to-thrive.html

Hogan Assessment Systems (2019). Hogan Business Reasoning Inventory – Technical manual. Hogan Assessment Systems.

Hunter, J. E., Schmidt, F. L., & Judiesch, M. K. (1990). Individual differences in output variability as a function of job complexity. Journal of Applied Psychology, 75(1), 28–42. /10.1037/0021-9010.75.1.28

Jaques, E. (1989). Requisite organization: The CEO’s guide to creative structure and leadership. Cason Hall.

Judge, T. A., Colbert, A. E., & Ilies, R. (2004). Intelligence and leadership: A quantitative review and test of theoretical propositions. Journal of Applied Psychology, 89(3), 542–552. /10.1037/0021-9010.89.3.542

National Center for O*NET Development. (2021). O*NET OnLine. /

Salgado, J.F., Otero, I., & Moscoso, S. (2019). Cognitive reflection and general mental ability as predictors of job performance. Sustainability, 11(22), 6498. /10.3390/su11226498

Schmidt, F. (2016). The validity and utility of selection methods in personnel psychology: practical and theoretical implications of 100 years of research findings. Working Paper. /publication/309203898_The_Validity_and_Utility_of_Selection_Methods_in_Personnel_Psychology_Practical_and_Theoretical_Implications_of_100_Years_of_Research_Findings