THE VIRTUAL BEHAVIOR ENGINEERING MODEL: 6 BEHAVIOR INFLUENCE FRAMES FOR A REMOTE WORKFORCE
The virtual behavior engineering model builds off Gilbert’s original behavior engineering model and Chevalier’s updated model and integrates user experience qualities. While the user experience typically refers to technology, its qualities are relevant to all facets of remote work. By analyzing each of the six influence frames, we can get better insight into root causes and their relationships. This improved understanding will help us prioritize and design better solutions to close a given performance gap.
What causes performance gaps in a virtual workplace? Is it technology? The people? A lack of training? When something goes wrong or we get unexpected results, organizations and leaders often look for something, or someone, to blame. With remote work, technology, people, and training are easy scapegoats. But the underlying causes for performance gaps are often more complex and intertwined with the ultimate responsibility lying with leadership and the management system in an organization.
CAUSE ANALYSIS
A cause analysis is how we can surface problems to find out what is really going on in the workplace. It is one of the International Society for Performance Improvement’s (ISPI) 10 Performance Standards and is defined as investigating “to find out why a gap exists between the current and desired performances” (International Society for Performance Improvement, n.d.). By following consistent, evidence-based processes to collect and analyze data, we can systematically diagnose underlying causes of performance gaps. This helps us to view gaps systemically to better understand relationships between causes and how they impact performance.
In terms of the overall performance improvement process, cause analysis is a part of the performance analysis phase of performance improvement and the link connecting the gap analysis to intervention selection (Dessinger, Moseley, & Van Tiem, 2012). Once we have assessed the need and identified a gap between desired and actual performance that is worth closing, our root cause analysis gives us the information we need to design meaningful solutions. While there are many cause analysis models, the behavior engineering model is one of the most widely used by practitioners (Giacumo & Breman, 2021).
GILBERT’S BEHAVIOR ENGINEERING MODEL
Since Thomas Gilbert (1978) first introduced the Behavior Engineering Model as his third leisurely theorem, countless practitioners have successfully used it to engineer worthy performance. Worthy performance, as Gilbert (1978) described, is when the value of accomplishments exceeds the cost of the behavior. His original behavior engineering model, as shown in Table 1, provides a systematic way to identify environmental and personal behavior influencers. Each frame gives us a different lens to view performance gaps. By focusing on frames we have more influence over (e.g., data, resources, and incentives), we can create the greatest leverage (Gilbert, 1978) for engineering worthy performance.
CHEVALIER’S UPDATED BEHAVIOR ENGINEERING MODEL
In his article “Updating the Behavior Engineering Model,” Roger Chevalier (2003) adapted the model, as shown in Table 2, to be more comprehensive and scalable. Using his own extensive experience as a practitioner and feedback from his students, Chevalier (2003) updated language to better align with how we often speak about performance, reordered individual causes, and added elements not included in the original model. These additions included emphasizing the psychological work environment and the need for job enrichment, among others.
ENGINEERING WORTHY PERFORMANCE THROUGH THE DIFFUSION OF EFFECT
The behavior engineering models help us maximize the overall impacts of the interventions we select (Chyung, 2008). As Gilbert (1978) described, changes to a condition often have widespread effects on others. For example, positive feedback may also serve as both an incentive and motivator. Likewise, increasing an individual’s knowledge may improve their self-efficacy and, in turn, increase motivation. He coined this as the “diffusion of effect.”
One of the most notable differences between Gilbert’s behavior engineering model and Chevalier’s updated model is the sequence for personal behavior causes (Winiecki, 2015). In this respect, Gilbert (1978) puts knowledge as the fourth position and motives as the sixth while Chevalier (2003) puts motives as fourth. This reversal in turn places capacity before knowledge and skills, consistent with social cognitive theory, which posits that an individual must have the capacity to reproduce a behavior before they can learn it (Bandura, 2004).
Chevalier’s reordering of the behavior engineering model gives us the opportunity to create more leverage by focusing on motives and capacity before we invest in a more costly training or learning solution. This ensures we not only create valuable performance; we also engineer worthy performance.
LEADERSHIP'S ROLE IN PERFORMANCE MANAGEMENT
Management’s ability to develop people and provide an environment conducive to performance underlies all performance improvement techniques (Chevalier, 2007). Gilbert (1978) referred to the behavior engineering model as the Management Theorem because the ultimate responsibility for environmental and personal behavior deficiencies lies within the management system, as shown in Figure 1.
Citation: Performance Improvement Journal 62, 5; 10.56811/PFI-23-0002
People themselves are not the cause of performance deficiencies. Rather, it is how well organizations manage the dynamics of, and relationship between, the people and their environment (Rummler, 1972). The management system itself extends beyond a single manager or group of leaders. While individual managers can have a tremendous influence on individual and team performance, it is leadership’s collective effectiveness at meeting people’s expectations that drives business performance.
Anderson & Adams (2015) refer to the expectations people have for leadership as universal promises:
1. Setting the right direction and creating meaningful work,
2. Engaging all stakeholders and holding them accountable for performance,
3. Ensuring that processes and systems facilitate focus and execution, and
4. Leading effectively by maintaining relationships of trust (Anderson & Adams, 2015).
The Leadership Expectations Iceberg
The universal promises of leadership encompass both explicit and implicit expectations. Explicit expectations are the responsibilities that can usually be found in a leader’s job description (Anderson & Adams, 2015) and often relate to environmental behavior influences. For example, setting expectations and providing feedback to create performance accountability. Implicit expectations, on the other hand, are more closely associated with people’s behavior influencers, such as increasing motivation through alignment and trust. Implicit promises are not expressly stated and may be harder to define but are nonetheless important.
Leadership expectations are behavior influencers that leaders have control over or responsibility for. As shown in the Leadership Expectations Iceberg (Figure 2), these expectations form an iceberg of both explicit and implicit expectations. When any one of these expectations are not met, it erodes trust and often negatively affects performance. When these expectations are collectively met by leaders, employees can better understand what is expected of them, find more meaning in their work, and have the resources, incentives, and environment they need to perform effectively. This in turn leads to better performance and business outcomes.
Citation: Performance Improvement Journal 62, 5; 10.56811/PFI-23-0002
THE USER EXPERIENCE & ITS INFLUENCE ON BEHAVIOR
The virtual workplace centers around technological systems, our interaction with them, and our connections to others through them. To diagnose performance gaps involving remote work, we have to look beyond the physical environment. We must also assess how the overall technological user experience affects performance.
Similar to the behavior engineering model, Peter Morville’s user experience honeycomb (2005), as shown in Figure 3, highlights qualities that influence the user experience and how users interact with a product. This includes usefulness, desirability, accessibility, credibility, findability, and usability, all centered around value. Each of these qualities gives us different lenses to frame and understand the user experience.
Citation: Performance Improvement Journal 62, 5; 10.56811/PFI-23-0002
Unlike the behavior engineering model, the user experience honeycomb is not a troubleshooting sequence. In a given situation, we must consider the unique user needs and context to determine which user experience qualities take priority (Morville, 2004). For example, with a Knowledge Management System, we may prioritize findability, usability, and accessibility. For communication, it could be the sender’s credibility and the usefulness of the information shared. Incentives would likely focus on desirability and usefulness.
THE VIRTUAL BEHAVIOR ENGINEERING MODEL
Value is the core of the user experience. While the user experience traditionally refers to technology, content, or products, these qualities are relevant to all facets of remote work. To engineer valuable experiences that support performance, the management system must provide the necessary environment and people support.
The virtual behavior engineering model, as shown in Table 3, includes three environment and three people influence frames. These build off the original (Gilbert, 1978) and updated (Chevalier, 2003) behavior engineering models and integrate user experience qualities (Morville, 2005). This adaptation better reflects the realities of remote work and needs of a diverse, geographically dispersed workforce.
ENVIRONMENT INFLUENCE FRAMES
Remote work has undoubtedly changed how we assess environmental performance gap causes. We rarely have the option to observe the physical environment or see how work is being performed without some form of technological support. Likewise, remote employees have experienced similar changes. They depend more than ever on technological systems and connections, team communication and collaboration is all done virtually, and their workspace is often within their own homes (Hill, Jones, & Corbridge, 2020).
The virtual behavior engineering model environment influence frames include:
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Communication
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Resources & Technology
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Incentives
Each of these environment frames encompass different elements that influence behavior. Environment in the context of a virtual workplace can include the physical, psychological, and technological environments.
Communication Influence Frame
We often use terms like communication, information, and data interchangeably. While similar, they are not one in the same. Data is a collection of facts and can come in many forms such as numbers, text, and images. Data can also be our personal observations. Information is how we bring meaning to the data after analysis. Communication is how we share that meaning with others.
Information brings awareness while communication creates alignment (Hill & Jones, 2021). It is an interactive process that not only requires us to relay information, but also ensures the receiver understands the message and can discuss or clarify information. Substituting the word “communication” helps prompt additional thinking about how well information and data are presented and understood when we assess these elements.
Communication Channels & Messaging
In the digital age, we have access to more data and information than ever. Technology has enabled hyper-communication and we can easily share information with the touch of a finger. With the abundance of information available, it has become increasingly harder for employees to decipher what is important and relevant. The numerous communication channels available (e.g., email, virtual meetings, intranet articles) can also be problematic. When we assess communication related causes, these can stem from either the communication itself or the communication channel or platform used.
For example, if a manager sends an employee expectations via email, it can be easy to misunderstand the tone, urgency, or importance. Depending on the manager’s communication skills, the expectations may also be misinterpreted, or the email may simply go unread as many do. On the other hand, if expectations are solely delivered in a virtual meeting and notes are not taken, employees may misunderstand, forget, or entirely miss the message if they did not attend.
Virtual Communication Barriers with a Diverse Workforce
In a virtual workplace, communication gaps often occur. Even with synchronous communication, like a video call, it can be difficult to interpret body language and facial expressions. Digital communication that is not accessible can also pose challenges for individuals who have a disability. With an increasingly globally distributed workforce, it is increasingly important that we are mindful of language barriers and cultural aspects that may impact communication.
Technological System Communication
In a physical workplace, communication and feedback usually come from management, colleagues, or customers. In a virtual environment, communication also comes from the technological systems or software employees use to complete processes or access data and information. For example, if an employee misses a required data entry field, the system should respond appropriately. Likewise, the system may provide task instructions or show examples of how to enter information.
When the technological system is designed to support performance and the user experience, the system itself becomes the job aid. It can communicate expectations, alert users to potential mistakes, provide guidance about completing a job task, and provide feedback for errors. A system that communicates well with users can prevent the need for separate instructional job aids, guides, or performance support.
Team Norms
For data and information related causes, we typically look at feedback, performance expectations, and guidelines. However, with remote work, information sharing and team collaboration are other communication elements to consider. Since remote colleagues often miss out on informal information sharing, mutual understanding of team norms can help support performance.
Team norms are the expected behavior patterns team members have for each other (Chevalier, 2007). These can either be formal, documented norms and standards or informal, unofficial expectations that have developed over time within a group. For formal team norms, these often come in the form of team agreements, meeting rules, or project charters. These serve to clarify how team members will work with one another, how technology is used to interact, and collaboration expectations.
Informal norms develop based on group members' experience interacting with each other. For example, an informal norm may emerge that cameras can be off for certain meetings. Or that important requests should not be made on Friday because many employees have flexible schedules and are off work. In these cases, employees either learn by observing others’ behavior and feedback they receive, or they learn through trial by error. When it comes to norms, informal team norms often influence performance more than formal norms do (Chevalier, 2007). To fully support performance, the two need to align with each other.
Resources & Technology Influence Frame
Resources in a virtual workplace can include both the tools and instruments needed to do the job and the environment where work is performed. This broadly encompasses technological systems, work equipment and resources, the physical and psychological environment, and the connection between each.
Technological Systems & Digital Content
In the United States, about one in four adults report they have some type of disability (Okoro, Hollis, Cyrus, & Griffin-Blake, 2014). With an ever-growing reliance on technological systems and digital content, accessibility is crucial. This includes ensuring content and systems are perceivable, operable, understandable, and robust (W3C, 2019). While accessibility focuses specifically on making content more accessible to individuals with disabilities, it also creates a more usable, inclusive virtual workplace for everyone. For example, an Oregon State University research study found that 71% of students without hearing difficulties used captions at times (Linder, 2016).
In addition to accessibility, the overall user experience of the apps and platforms impacts how well these support performance. Too many disconnected apps or systems can be problematic, especially if multiple logins and passwords are required. Likewise, if a job aid is not findable because it is buried on an unorganized intranet site or not clearly labeled, it is unlikely employees will use it. Table 4 provides examples of problematic user experience areas for technology systems and digital content.
Remote Work Equipment & Tools
When we first transitioned to remote work, many employees had makeshift office spaces. While some may have had dedicated desk space, others were (and many still are) working from a kitchen counter or bedroom. Although employees may be in a virtual environment, their physical environment and how the connection to the virtual workplace is made also impact performance.
While we may not be able to control all aspects of a home office environment, there are many within our control. This can encompass work from home equipment and how well it supports the work being done. In a remote workplace, some examples include the number of monitors provided, sit/stand desks, and the quality of headsets and web cameras. It can also include internet access, virtual private network connections, and other technological elements that impact performance.
Although many organizations provide employees with basic technological equipment, this is not always the case. As we analyze the impact of resources and technology on performance, we may consider whether employees use personal devices. Personal devices like personal computers, tablets, and cell phones may not have the capacity of company-provided equipment.
Time & Distractions
Time is a resource that can influence behavior (Chevalier, 2002). Just like in the physical workplace, it also affects performance in the digital workspace. Distractions are also something to be mindful of. With remote work, there are three primary types of distractions employees face: Work, digital, and personal (Venkataramani, 2021). Although distractions may seem like an infrequent interference, they can add up. For complex tasks especially, minimizing employee distractions and task-switching can increase accuracy and speed. This may include dedicated work time for complex tasks, turning off email and messaging notifications temporarily, and status updates to prevent unscheduled calls.
Incentives Influence Frame
Similar to a physical workplace, incentives in a virtual workplace can directly influence both motivation and performance. In Chevalier’s updated behavior engineering model, he identified the need for a positive work environment and reinforcing positive work (Chevalier, 2003). Rather than focusing on consequences for inadequate performance as the go-to solution, we can instead remove unintended negative consequences for desired behaviors and provide meaningful incentives. While there may be natural consequences for inadequate performance (e.g., upset customers or rework), these often serve as feedback rather than punishment.
Job Enrichment & Ownership
While incentives are often associated directly with performance, they do not have to be. By providing regular opportunities for recognition, employee growth, and autonomy, employees become more responsible for their work (Chevalier, 2007). This type of job enrichment helps establish ownership with employees. If these elements are not present, employees may feel more disconnected from the work, which can contribute to performance gaps.
Inclusive, Meaningful Incentives
For incentives to work, they must be meaningful to the employee and inclusive. What one employee considers to be a positive incentive, another may consider negative (Rummler, 1972). If incentives are provided inconsistently or are not desirable or relevant to an individual, their value degrades. Likewise, if employees do not believe they have an equal opportunity for career advancement or growth, this can deter performance. How incentive systems are designed and implemented will influence whether they support all employees' performance.
PEOPLE INFLUENCE FRAMES
Today, it is rare for an employee to work without collaborating or interacting with another individual. Technology and remote work have accelerated the growth of geographically dispersed teams. Individuals now make up several types of interdependent teams. This includes core work teams, work groups, cross-functional teams, and project teams, among others. Although team members do not share the same physical space, they share a virtual workspace.
When performance gaps arise, the people doing the work are not the problem. Nor is it entirely about the environment or what people bring to the job. Leadership must also design systems and manage in a way that leverages, supports, and enhances what people bring to the table. The collectiveness of individuals, teams, and leadership comprise the half of the virtual behavior engineering model. The people influence frames include:
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Motives & Belonging
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Capacity
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Knowledge & Skills
Motives & Belonging Influence Frame
Individual & Team Motives
Our motivation is what invigorates us. It is what drives us to turn intention into action while also supporting our persistence to sustain action over time (Clark, 2005). In the context of a virtual environment, while an individual’s motives influence behavior and performance, collective team motives and alignment also affect them.
As individuals, we have our own priorities, values, and goals. When these do not align with those of the team and organization or the consequences of performance, motivation and performance often declines. At the team-level, motivation and successful performance hinges on mutual respect, accountability, and certain shared beliefs within the team (Clark, 2005). At the organizational level, having a clearly defined mission or purpose, effectively communicating it, and taking actions that support it can help employees find more purpose in their work (Anderson & Adams, 2015).
Elements in other frames also often indirectly influence both individual and team motives. This is especially true for incentives like a positive work environment and job enrichment (Chevalier, 2007) and team-directed incentives (Condly, Clark, & Stolovitch, 2003). Even though the cause may be related to motives, we often have the greatest effect by influencing motives through indirect means (Gilbert, 1978).
Belonging
Remote work has increased the need for community and belonging in the workplace. A lack of belonging often leads to a sense of disenfranchisement (Hill & Jones, 2021). An employee’s sense of belonging has been shown to influence behavior and performance and has a strong connection to social workplace relationships, employee empowerment, and inclusion (Fawcett, Brau, Rhoads, Whitlark, & Fawcett, 2008). This can also influence whether employees give feedback to leadership, take ownership for mistakes, and share concerns.
Designing a workplace that allows people to develop a sense of belonging takes more than facilitating feel-good team building exercises or mandatory virtual social hours. It requires trust, transparency, diversity at all levels of the organization, allyship, and inclusivity, among others. Past actions are often the best predictors of future ones and affect employees' perception of leadership's credibility and how connected they feel in the workplace.
Reasonable Expectations
Expectations can either serve as driving or restraining performance forces (Chevalier, 2003). While realism centers on whether expectations are achievable given the environment and people supports available, reasonableness is the fairness of the request. To effectively support performance, expectations need to be both realistic (an element of capacity) and reasonable.
With expectations, there are often two ends of the spectrum. On one end are the official expectations we have for employees often identified in job descriptions or considered key job responsibilities. On the other end are the additional tasks and roles employees take on outside of their official job duties. Some examples include working on a special project, filling in for a coworker, or taking on higher level duties. While the latter may be realistic, depending on the context, they may not be reasonable.
Alignment is the core of ensuring expectations are reasonable. Expectations should be mutually beneficial and provide value for both the individual employee and the organization. By providing meaningful incentives for performance outside of employees’ official job duties, these additional expectations can serve as motivators and drive performance. If this alignment does not happen, employee engagement, relationships, and performance often deteriorate.
Capacity Influence Frame
Capacity is often thought of as an individual's physical or cognitive ability to learn or do the job. From this perspective, aside from hiring for capacity, it may seem there is little we can do to influence behavior. Instead, by taking a holistic view of capacity, we can better identify underlying causes at both the individual and team level.
Realistic Expectations
Realistic expectations are a key element of capacity. If a job is poorly designed or encompasses too many responsibilities, we cannot realistically expect employees to meet our expectations. Likewise, if we do not provide the appropriate guidance, feedback, or resources, it is not realistic that employees will perform as expected.
Emotional Well-Being
The COVID-19 pandemic has accelerated our awareness of the connection between employee well-being and individual capacity. Stress, stemming from both the workplace and personal life, has been on the rise and employees’ well-being is in decline. Globally, workers reported they felt more stress in 2021 than they did in 2020 (Gallup, 2022). Uncertainty and adverse employment environments also have led to worsened psychological conditions and burnout (Giorgi, Lecca, Alessio, Finstad, Bondanini, Lulli, Arcangeli, & Mucci, 2020).
To help organizations build a workplace that supports mental health, the United States Surgeon General outlined essential elements for workplace mental health and well-being (2022). This includes:
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Protection from harm
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Connection & community
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Work-life harmony
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Mattering at work
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Opportunity for growth
Many of these elements tie directly to, or closely with, other frames of the virtual behavior engineering model. This includes the job enrichment and career growth elements of the incentives frame and elements of the motives and belonging frame, among others. In this respect, improvements to elements in each of these frames may also improve capacity.
Work-life harmony is especially notable because it does not directly link to other virtual behavior engineering model frames of influence. Work-life harmony is our ability to manage our personal and professional responsibilities and demands. This comes down to autonomy over work, flexible and predictable schedules, access to paid leave, and clear boundaries (United States Surgeon General, 2022).
Organizations often have a tendency to value labor and hard work over accomplishments (Gilbert, 1978). This is particularly prevalent with the virtual workplace where management cannot physically see what employees are doing. Often, this mindset can lead to increased monitoring and digital tracking software. While some productivity tools have a place, micromanaging employees has little positive impact on their accomplishments. Rather, it can increase stress, negatively impact relationships, and decrease overall well-being and capacity (Chambers, 2009).
Team Capacity
The overall team capacity and how well leadership manages it often influences performance as much as individual capacity. Within any given team are diverse individuals with different skill sets, abilities, interests, and availability. Staffing levels, job placement, and work distribution are some of the key inputs for assessing and managing team capacity. Leadership also should be mindful of how elements of environment frames impact team capacity. For example, improving processes can increase team capacity, as can performance supports that allow for cross-role coverage.
Inclusive Recruitment & Selection for Capacity
As a society, especially in the workplace, we often place value on knowledge for knowledge's sake (Gilbert, 1978). Many times this manifests in employee recruitment and hiring when academic degree requirements are arbitrarily used as qualifiers. Inclusive recruitment and hiring, on the other hand, focuses more on the accomplishments, abilities, and capacity required to do the job. It also encompasses accessibility and mitigating biases to widen the applicant pool and ensure the applicants are equitably selected and have the capacity to learn and become exemplary performers.
Sidebar: Implicit biases can affect the perception of an employee’s capacity. These biases can be particularly influential when a particular gender, racial, or ethnic group is traditionally associated with a profession (Interagency Policy Group on Increasing Diversity in the STEM Workforce by Reducing the Impact of Bias, 2016). There is also the common stereotype that older workers lack the capacity or motives to learn new technology (Ivan & Cutler, 2021). By following systematic processes to collect data and speaking directly with those who do the work, we can avoid generalizations that misjudge an employee’s capacity.
Knowledge & Skills Influence Frame
From eLearning courses to webinars and everything in between, training is a go-to solution for many organizations when there are performance problems. This demand for training is often twofold. Sometimes leadership pushes training as a quick fix to solve a problem. Other times learners themselves may drive the demand because they want to perform well but may not have the ability to influence real change.
Jumping to training as a solution is not new. This has been a challenge since well before Gilbert (1978) first introduced the behavior engineering model. What is new, especially in the virtual workplace, is that it is easier and faster than ever to create training content at a relatively low cost. With access to dozens of free or inexpensive authoring tools, video software, and more, even a novice can put together and publish a course. We also have the ability to curate numerous types of generic, skill-based learning content. But, as many instructional designers know, not all courses deliver the expected results. This is especially true if knowledge is not the real source of a performance gap.
The true cost associated with training often goes beyond development or procurement costs. It also encompasses learner time, opportunity cost, maintenance costs, and the potential impact on our learning and development team's credibility with learners. By targeting root causes, we can ensure learning solutions, if necessary, support interventions that better enable performance.
Knowledge & Skills to Support Performance
Knowledge and skills are almost instinctively associated with training. However, while training may be a potential solution, it is just the means to an end. Knowledge and skill related gaps can relate to any combination of the other influence frames at both the individual performer or leadership level. For example, an individual performer may have gaps relating to a technological system, technical knowledge to complete a process, or industry standards that set expectations. A manager may have a knowledge gap for creating meaningful incentives, providing effective feedback, or managing team capacity.
With the diffusion of effect (Gilbert, 1978), we can often leverage other frames to minimize knowledge and skill deficiencies. Not all tasks and activities require in-depth knowledge of the subject or a high skill level to produce desired outcomes; some may only require an awareness level (Wallace, 2020). In these cases, a job aid or communication may be an appropriate solution. Likewise, we will likely see more return on investment if we simplify a complex process, increase awareness of natural consequences, or address other environmental influencers first.
Emotional & Cultural Intelligence
Emotional intelligence encompasses many areas including identifying, using, understanding, and regulating emotions and has been found to be linked at every point of workplace performance (Kannaiah & Goleman, 2015). Cultural intelligence, or the ability to function effectively in intercultural settings, includes four primary factors: Knowledge, drive, strategy, and action (Livermore & Van Dyne, 2015). In a virtual environment with a diverse workforce and customer base, emotional and cultural intelligence are crucial for individuals and leadership alike.
Emotional and cultural intelligence can influence the effectiveness of communication, team cohesiveness, alignment, and more. However, a generic or broad effort to increase emotional or cultural intelligence will likely have little influence closing performance gaps. A more effective approach is to map specific skills and/or knowledge found in these intelligence domains to both desired behaviors and outcomes.
Like any type of knowledge or skill, when it comes to developing emotional and cultural intelligence that supports performance, training is just the surface. Once training is over, a student will only be as good as the environment they go back to (Boise State OPWL, 2015). The actual application is what influences performance along with how well the work environment and others in it enable new skills.
Job Placement & Assignments
Within a team, each individual brings a unique combination of experience, knowledge, and skills to the workplace. To ensure the team is able to perform effectively and efficiently, leadership must be able to assign jobs and place team members in positions that will best utilize their strengths, or provide intentional opportunities for them to develop their existing skills. This requires understanding both the individual’s and the team’s collective knowledge and skill set, and the skills and knowledge required to successfully complete the assignment.
CONCLUSION
Remote work centers on technology, our interaction with it, and connections to others through it. But technology alone does not influence behavior. Nor does the individual performer. Causes that contribute to performance gaps are often complex and intertwined. The virtual behavior engineering model features six behavior influence frames for a remote workforce. These build off the original (Gilbert, 1978) and updated (Chevalier, 2003) behavior engineering models and integrate user experience qualities (Morville, 2004). By analyzing each of the six virtual behavior engineering model influence frames, we can get better insight into root causes and their relationships to prioritize and design more effective and efficient solutions.
The Management System & Behavior Deficiencies
Note. The management system’s relationships to behavior repertory and environmental support related causes. Adapted from Human Competence: Engineering Worthy Performance (p. 89), by T. Gilbert, 1978, New York: McGraw-Hill.
Leadership Expectations Iceberg
Note. Iceberg showing explicit and implicit leadership expectations and their connections to various elements within the behavior engineering models. Created based on concepts in Human Competence: Engineering Worthy Performance, by T. Gilbert, 1978, New York: McGraw-Hill; Mastering Leadership: An Integrated Framework for Breakthrough Performance and Extraordinary Business Results (1st ed.), by R. Anderson & W. Adams, 2015, Wiley; “Updating the Behavior Engineering Model,” by R. Chevalier, 2003, Performance Improvement, 42(5).
Morville’s User Experience Honeycomb
Note. Morville’s user experience honeycomb centered on value. Qualities include useful, desirable, accessible, credible, findable, and usable. Adapted from User Experience Design, by P. Morville, 2004 (http://semanticstudios.com/user_experience_design/).
Contributor Notes
KAMBRIA DUMESNIL is a Management Analyst with the Washington state government. With a master's degree in Organizational Performance and Workplace Learning and a Graduate Certificate in Instructional Design from Boise State University, Kambria blends academic knowledge with hands-on experience to apply evidence-based frameworks to solve modern problems. She has several years of experience with organizational knowledge management and leading technology-based projects to transform workflows and improve communications and performance. Beyond her professional role, Kambria is the founder of the AI Innovation Lounge and an active member and volunteer of the International Society for Performance Improvement (ISPI), contributing as a member of the Technology and Communication Committee.
