HPI
Modeling
The Risk-Frequency Matrix:
Applications for Performance Improvement
The Matrix
The Risk/Frequency Matrix tool is not a traditional Human Performance Improvement (HPI) tool; I will briefly explain it here. It was developed by Graham (2016, p. 9) using a decades old classic risk/frequency chart, which he adapted to define and illustrate the importance of “core critical tasks”. As shown in Figure 1, the chart consists of a simple quadrant matrix, with Risk as the vertical axis, and Frequency as the horizontal axis. The abbreviations stand for high risk (HR), low risk (LR), high frequency (HF), and low frequency (LF).
Figure 1. Gordon Graham’s Risk-Frequency Matrix
It is a simple concept, as Graham (2016) explains, “some things you do are high risk (meaning if they go bad, the consequences are big), and some are low risk (meaning if they go bad, the consequences are relatively low). Some things you do a lot, and some things you do rarely” (p. 9).
The bottom two quadrants are LR. Organizations and employees who happen to perform poorly when performing LR tasks may incur consequences, but the consequences will not be severe. Most likely not severe or “important” enough to justify the cost of an HPI intervention.
The right two quadrants are HF. Organizations and employees rarely perform poorly when performing HF tasks. They are good at them. The tasks are routine, common, and supported by policy, procedure, training, and experience – day to day business. Most likely an incidental HR/HF task failure will be easily diagnosed and addressed by referencing, adjusting, or reinforcing the established policy, procedure, training, and experience. Although “important,” the scope of the performance issue may or may not trigger the need for an HPI intervention. It will be up to the practitioner or the organization.
Why Things Go Right/Wrong
Watch Gordon Graham explain why things go wrong in public safety
Why Things Go Right/Wrong
Watch Gordon Graham explain why things go wrong in public safety
The performance concern lies in the HR/LF quadrant. Infrequent unfamiliar HR tasks demand HPI attention. “When you or your people get involved in a low-frequency event (particularly one high risk in nature) I get very worried” (Graham, 2016). Graham modified the HR/LF quadrant to include two sections: NDT and DT. “Some tasks need to be done immediately (NDT — non-discretionary time)…some give us time to think (DT — discretionary time)”(p. 10).
Responding to a HR/LF/NDT need or event is a “core critical task.” It may not happen often, but when it does employees had better be skilled, knowledgeable, and proficient enough to handle it without calling a stakeholder meeting, asking the boss, or looking up the policy. HR/LF/NDTs are a top priority for an HPI intervention. “Your role is making sure that you and all of your people…are adequately trained for the NDT events” (Graham, 2016, p. 11). Remember, although the nature of HR/LF/NDT events may be somewhat predictable, their actual occurrence is often unpredictable. The appropriate HPI response should be immediate, and it will, far more often than not, include training.
Models like Pavlov’s (2017) Mager & Pipe adaptation present the opportunity to consider skill and knowledge deficiencies earlier in the HPI process than the original Mager & Pipe model and many other methodologies. The right side pathway of the model still allows for organizational, environmental, and motivational factor analysis, which can be accomplished as time allows, either with or subsequent to addressing an immediate training issue. (See Figure 2).
Using a risk-frequency analysis as part of the initial determination of the importance of addressing the performance gap can help quickly identify critical training needs.
The weakness of a model like this is that Yes/No decision-making processes can funnel attention away from concurrent or causal factors – so the process should be applied iteratively until all pathways are explored (skill, knowledge, and organizational/environment). The strength of this model in the case of HR/LF/NDTs is the opportunity to avoid calamitous performance failures by expediting the identification of critical training needs.
Figure 2. Adapted Mager & Pipe Model
Models like Pavlov’s (2017) Mager & Pipe adaptation present the opportunity to consider skill and knowledge deficiencies earlier in the HPI process than the original Mager & Pipe model and many other methodologies. The right side pathway of the model still allows for organizational, environmental, and motivational factor analysis, which can be accomplished as time allows, either with or subsequent to addressing an immediate training issue. (See Figure 2).
Using a risk-frequency analysis as part of the initial determination of the importance of addressing the performance gap can help quickly identify critical training needs.
The weakness of a model like this is that Yes/No decision-making processes can funnel attention away from concurrent or causal factors – so the process should be applied iteratively until all pathways are explored (skill, knowledge, and organizational/environment). The strength of this model in the case of HR/LF/NDTs is the opportunity to avoid calamitous performance failures by expediting the identification of critical training needs.
Figure 2. Adapted Mage & Pipe Model
HPI models and philosophies which deprioritize training as a solution and advocate exhaustive explorations of organizational or environmental causes and solutions before considering and implementing training, will result in high-risk task failure should the HR/LF/NDT event reoccur before individuals’ knowledge and skills meet the performance need.
High Risk / Low Frequency
Watch Gordon Graham explain the significance of HR/LF/NDT, and the need for training
High Risk / Low Frequency
Watch Gordon Graham explain the significance of HR/LF/NDT, and the need for training
The use of the Risk/Frequency Matrix as an analysis tool immediately after the identification of the performance gap is a prudent practice to prevent unnecessary delay in implementing a needed training solution.
So, what about Job Aids?
Job aids are a topic for full discussion for another time. But briefly – In Gilbert’s Behavioral Engineering Model (BEM), are they a resource (organizational/environmental), or are they training (skills/knowledge)? Hartt, Quiram, and Marken (2016) grappled with this question in their study of where “most” performance issues originate. As cited in Hartt et al. (2016), performance technologists “Harless (2002) and Binder (1998) specifically mention job aids as a skill or knowledge intervention” while “Gilbert (2007) does not mention job aids” (p. 45). In the context of risk and frequency, the question of “where” in the BEM job aids fit, matters less than “how often” the task is performed; so, decisions about when to include them as an intervention shouldn’t completely be dictated by which BEM box a performance technologist picks. Also, some job aids like complex checklists and flowcharts may hamper NDT performance, while others, like painting an emergency shut-off lever bright red, tend to enhance NDT performance. Look for more on that from me in the future, guaranteed.
So, what about Job Aids?
Job aids are a topic for full discussion for another time. But briefly – In Gilbert’s Behavioral Engineering Model (BEM), are they a resource (organizational/environmental), or are they training (skills/knowledge)? Hartt, Quiram, and Marken (2016) grappled with this question in their study of where “most” performance issues originate. As cited in Hartt et al. (2016), performance technologists “Harless (2002) and Binder (1998) specifically mention job aids as a skill or knowledge intervention” while “Gilbert (2007) does not mention job aids” (p. 45). In the context of risk and frequency, the question of “where” in the BEM job aids fit, matters less than “how often” the task is performed; so, decisions about when to include them as an intervention shouldn’t completely be dictated by which BEM box a performance technologist picks. Also, some job aids like complex checklists and flowcharts may hamper NDT performance, while others, like painting an emergency shut-off lever bright red, tend to enhance NDT performance. Look for more on that from me in the future, guaranteed.
The Enhanced Risk-Frequency Matrix
Expanding the utility of the tool for HPI in general
Because risk and frequency are non-binary (not just high or low) in more complex contexts, and to support non-doomsday HR/LF/NDT and lesser critical core task performance, I added a “moderate” (M) category element, resulting in nine event/task categories.
I created NDT/DT-type divisions in four additional event/task categories, two MR and two HR, indicated by color variations. Each color correlates to a set of considerations to aid in appropriate HPI intervention selection. These enhancements provide more versatile guidance for HPI analysis in general, and create opportunities to account for perishable skills, recognition primed decision making (RPDM), and experience.
Anyone who’s heard me speak about, or has discussed with me, the question of “What is training?” has heard my philosophy/mantra that “Everything is training.”
Developing tools and practices that harvest data from actual event responses and task performance can help build skills and knowledge within the context of real-world experience. Managed properly, moderate and low frequency performance of moderate and high risk tasks are valuable sources of training.
The draft matrix (under revision) appears in Figure 3. As my work continues, I am developing training and non-training support strategies for multiple performance dimensions.
Figure 3. Enhanced Risk-Frequency Matrix
So, how does it work?
For more information, or to discuss the application of the Enhanced Risk-Frequency Matrix for performance improvement contact Vic McCraw.
References
Graham, G. (2016). Some Thoughts on Real Risk Management [Lecture notes]. Retrieved from https://www.urmma.org/wp-content/uploads/2016/03/Gordon-Graham-2016-Handout.pdf
Hartt, D., Quiram, T., & Marken, J. A. (2016). Where the performance issues are and are not: A meta‐analytic examination. Performance Improvement Quarterly, 29(1), 35-49. doi: 10.1002/piq.21213
Pavlov, Yuri (2017). Mager & Pipe’s HPT model [Blog post]. Retrieved from https://pavlovsyracuse.files.wordpress.com/2017/06/modelmagerpipe.pdf