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Rethinking Performance Management for Post-Pandemic Success

Organizations serious about high performance must rethink performance metrics.

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Will dispersed, distributed, and remote workforces become the post-pandemic new normal? It may be too soon to say. Much clearer is how misleading and unhelpful legacy metrics are for assessing work-from-home performance. Pre-COVID-19 workplace analytics are no longer fit for purpose. They don’t capture the disjointed realities of digital workflows. Stressed, separated, and challenged to do better with less, people need greater insight into how they’re doing. Productivity now demands more aggressive and actionable measures.

Recalibrating key performance indicators (KPIs) is essential to ensuring that remote work actually works. Enterprises that want the best from their workers — and for their customers — innovatively invest in digital accountability, but these efforts must acknowledge and respect newly blurred distinctions between work and home life. Digitally colonizing people’s homes is not an option; workforce mood and morale matter. Thoughtful leaders grasp the need for a healthy coexistence.

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Without trust and transparency, remote workforce monitoring appears intrusive and exploitative. With transparency and trust, tracking can authentically be branded and experienced as data-driven workforce support . Increasingly, monitoring and measuring morale — qualitatively, as well as quantitatively — matters. But soft skills deserve hard numbers, too. Emergent post-pandemic dashboards embrace affective metrics as firmly and fairly as effective ones.

That means that leading companies must renovate their data-driven dashboards to better inspire people and project teams and promote positive outcomes. They must automatically capture and analyze, and explicitly communicate, their high-performance criteria. The most important takeaway: High-performance management depends on high-performance measurement. The digital future of one depends on the digital future of the other.

Redefining and remeasuring high performance may prove to be the true disruptive opportunity for post-COVID-19 growth.

At one global professional services company, for example, top management dramatically accelerated project delivery schedules for its newly remote teams. This forcing mechanism deliberately inspired greater communication, coordination, and collaboration expectations for team members. At the same time, however, the company created a complementary buddy system to help ensure that more isolated and/or introverted employees felt connected. Tech support migrated from a back-office help-desk function to a digital project facilitator and enabler for global teams with demanding deadlines. The number of pulse surveys monitoring employee engagement and morale increased from fortnightly to every few days. Top management is tracking what‚ and who — delivers value well.

A senior global research project manager at Adobe programmed his laptop to display a personalized end-of-day dashboard visually summarizing — with pie charts and graphs — how he spent his time, whom he contacted, messages sent and received, documents exchanged, appointments scheduled, commitments made, and to-do list items accomplished, along with the top three items for the following day. He started sharing this dashboard with his team and is now wondering whether he should nudge — or require — colleagues to create comparable dashboards. “Should we be visible to each other in this way?” he asks. He says that such “dashboard transparency” has sparked cross-functional exchanges he’d never had before.

At least two global banks seek to capture remote-working lessons and best practices for internal discussion and sharing. Looking ahead, they’re rethinking whether they really need all the commercial office space they currently possess. They’re now reviewing with IT how significantly having a dispersed workforce alters their process automation road maps. Consequently, IT and its business process owner counterparts now track and map dispersed workforce workflows with a new remote automation strategy in mind.

Using Data to Better (See and Communicate) Performance

Mandatory remoteness quickly obsolesced executive truisms like “management by walking around,” and “under management’s watchful eye,” along with the concept of an “open-door policy.” Disrupted organizations soon learn just how little they know about how well — and how poorly — their people and teams work together. Virtually every serious organization now grasps that some meaningfully measurable form of real-time monitoring is essential to value orchestration and oversight.

For some, this quest for transparency translates to “Trust but verify”; for others, the mantra is “Verify but trust.” Either way, trust is core. “Do I trust my people? Yes,” says one investment banking lead. “Do I now need to be able to see how they spend their time? Yes. They need to trust me, too.”

Proactive enterprise communication is central to this cultural shift. When a Fortune /Adobe survey asked CIOs what has proved to be the biggest challenge in facilitating their companies’ remote work, only 20% said hardware, and 21% tech tools. Over half — 53% — said the hardest issue was getting employees to effectively communicate with one another. Why is that so seemingly hard? There’s certainly no shortage of smart messaging tools. As the COVID-19 crisis reveals, companies overwhelmingly depend on them.

Yet, most companies lack real-time metrics or measures assessing team and/or process communication effectiveness. Typically, those indicators are bundled into performance management reviews. That helps explain an accelerating managerial trend: greater reliance on performance management systems to better orchestrate and upgrade team performance. This emergent application of performance management systems ensures more communication and conversations about performance.

Unsurprisingly, next-generation performance management depends on digital monitoring and tracking platforms to generate real-time analytic insights. Those workflow and process insights can be prescriptive and predictive, as well as descriptive. High-performing leaders embrace this practice. Dispersed, technologically enabled enterprises seamlessly converge people, process, and technology into performance management systems.

With improved dashboards, leaders can see which teams best add value to what processes. They can observe which workflows invite consolidation, automation, and/or professional development . Leadership now has the data and analytics necessary to refine what high performance should mean for people and what it could mean for machines. These insights are indispensable. The more repeatable, replicable, and scalable the high-performance workflow, the better its candidacy for automation and/or machine learning. Correlating and connecting instrumented workflows with KPIs lets organizations turn the “remoteness from COVID-19”-imposed bug into a high-performance-enabling feature.

We see this in law firms, logistics providers, customer contact centers, and even health care providers. From telemedicine to texts about a customer’s arrival for curbside pickup, organizations are repurposing and instrumenting their performance management platforms in ways that measurably redefine high performance.

For example, colocated contact centers have been forced to geographically disperse. This has brutally disrupted legacy work patterns and forced a performance management reevaluation. Chatbots prioritize and route inquiries; support workers more easily message or transfer callers to colleagues; automated follow-ups with relevant links attached are readily sent. Response time, Net Promoter Score, and customer satisfaction KPIs retain pride of metrics place. But better analytics orchestration lets management track the digital blends of process and performance ingredients best correlated to desired outcomes. The resultant data highlights touch points best suited for automation and those where human contact best improves outcomes. The new constraints and opportunities imposed by remoteness and automation have transformed how the contact centers have chosen to align performance assessment, efficiency, and customer response.

Similarly, a “remote-ified” Silicon Valley law firm quickly and effectively deployed transcription-as-a-service to convert every Zoom-based client and partner meeting into editable documents. Instant transcripts dramatically changed how legal teams collaborated with each other and with clients. Measuring value-added revisions to those documents — and how those revisions were included in filings and client communications — immediately emerged as an essential workflow monitoring challenge. Version management governance became a new driver for decision-making. Partners now track their time-and-version ratios between simultaneous and asynchronous review. For some partners and associates, ROI effectively means return on iteration — in other words, which lawyers and legal teams have the biggest productive impact editing, annotating, and converting transcripts into desired client deliverables.

These examples show that successful leaders can use performance management analytics as portal and platform to convert new capabilities and constraints into new value. Data-informed performance management invites and inspires more productive workforce exchanges.

These interim COVID-19 findings represent genuine business applications of conclusions reached by our 2019 research report “ Performance Management’s Digital Shift .” That report anticipated the disruptive dominance data-driven workforce communication would enjoy. “The biggest cultural and organizational impact of next-generation performance management systems,” we observed, “will be feedback time, tempo, and impact. Instead of annual, quarterly, or impromptu reviews, talent- and accountability-oriented enterprises will encourage and enable near-constant feedback.”

Feedback — actionable, constructive, trackable, and influential — is the informational and motivational coin of the digital realm in the post-pandemic distributed workforce. Feedback — data-enriched, KPI-aligned — simultaneously promotes situational awareness and self-awareness. Feedback is how people get better at getting better. High-performance systems require high-performance feedback. Better-quality feedback means better-quality outcomes. This simple management — and leadership — truth is being rediscovered and reconfigured in light of COVID-19.

To cultivate healthy returns from a healthy — if remote and distributed — workforce requires leaders to treat data and analytics as nutrients for people, not just fuel for economic growth. That means leaders need to do the following:

Commit to a continuous feedback culture. Much as individuals use Google Maps or Waze to manage expectations around travel, employees and associates need dynamic visualizations to manage their expectations around work. Performance management platforms must facilitate ongoing feedback on professional progress, growth, and development opportunities. Executives must define the feedback experience for their people. Doing so forces leaders to define and develop a shared perspective about what high performance means.

Commit to clarity between assessment and development. Managers should make clear when feedback targets performance assessment versus cultivating new capabilities and skills. Development matters. Especially for remote workers and distributed teams, human resource policies must balance assessment and the safe cultivation of new skills and capabilities.

Commit to transparency. Post-pandemic performance management credibility and trustworthiness depend on transparency. People must be able to see that their contributions to meetings are recognized and/or that their blown deadlines cost the company a big client. This requires significant shifts in data governance: Connecting and aligning feedback transparency to data collection must become a core cultural value and practice. In short, transparency is the foundation for a performance culture that can also literally be seen as a fair and equitable culture.

Related Articles

Commit to performance management and KPI alignment. Aspiration and expectation require quantification. There is no meaningful performance management without measurable KPIs. High-performance accountability requires clear and concise KPIs or key results. Linking performance management to KPIs or objectives and key results is the strategic duty and obligation of serious leadership. Managers, not HR, ensure that performance management activities support measurable, valuable business outcomes.

There will always be tensions — and opportunities — between managing high-performance people, high-performance machines, and high-performance systems. Innovatively confronting those challenges will be the most important leadership challenge this global pandemic creates.

About the Author

Michael Schrage is a research fellow at the MIT Sloan School of Management’s Initiative on the Digital Economy, where he does research and advisory work on how digital media transforms agency, human capital, and innovation.

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Partner center.

In the spotlight: Performance management that puts people first

In volatile times, companies are under outsize pressure to respond to economic, technological, and social changes. Effective performance management systems can be a powerful part of this response. They’re designed to help people get better in their work, and they offer clarity in career development and professional performance. And then there’s the big picture: companies that focus on their people’s performance are 4.2 times more likely to outperform their peers, realizing an average 30 percent higher revenue growth and experiencing attrition five percentage points lower (see sidebar, “About the research”). Companies that focus on their people and organizational health also reap dividends in culture, collaboration, and innovation—as well as sustained competitive performance. 1 Alex Camp, Arne Gast, Drew Goldstein, and Brooke Weddle, “ Organizational health is (still) the key to long-term performance ,” McKinsey, February 12, 2024.

Today, company leaders lack full confidence in most performance management systems—despite these systems’ importance and value—citing fragmentation, the existence of informal or “shadow” systems, misalignment, and inconsistency as common challenges. What sort of systems fit the company’s needs? Should rewards focus on individual or team goals? Where are limited resources best spent?

About the research

The insights in this article draw from a comprehensive review of industry best practices, including the experiences of more than 30 global companies across sectors, as well as research by the McKinsey Global Institute (MGI) into how companies gain a competitive edge and deliver top-tier financial results. Specifically, MGI studied more than 1,800 companies with revenues of greater than $100 million. 1 Performance through people: Transforming human capital into competitive advantage ; MGI, February 2, 2023. The article’s author team also completed a study of more than 50 companies’ performance management practices, aiming to provide a nuanced understanding of how organizations approach and execute performance management.

An understanding of the four basic elements of performance management—goal setting, performance reviews, ongoing development, and rewards—provides a foundation for answering these questions and more. Of course, the right performance management system will vary by organization. Leaders who embrace a fit-for-purpose design built on a proven set of core innovations can build motivational and meritocratic companies that attract and retain outstanding employees.

How leading companies approach performance management

Our research across a set of global companies found that despite widespread agreement about certain performance management best practices—such as offering regular feedback outside of an annual review—many companies remain stuck in old ways of working. There are many design choices that can determine the characteristics of a performance management system, but some are more critical than others (Exhibit 1). These decisions—and how they interact with each other—will help determine how the performance management system maps onto the company’s overarching strategy.

Goal setting

Two critical design decisions relate to goal setting: the number of performance management systems used and whether to prioritize individual or team performance goals.

Degree of differentiation. The simplest and best option for many organizations is a single performance management system to address the needs of all employees. However, in more-complex companies with several employee groups, more than one system might be necessary. Manufacturing companies, for instance, may employ three performance management systems with few commonalities: one for sales, in which sales agents are provided direct incentives for the number of goods sold; one for production, with a monthly rhythm focusing on improving core production KPIs; and one for executives, in which the focus might be related more to annual objectives and leadership behavior.

Considerations for these choices often revolve around the nature of the work and the ease of quantifying outputs. For roles in which performance can be easily measured through tangible metrics, such as sales and production, a system emphasizing quantifiable outcomes may be more suitable. On the other hand, for roles involving tasks that are less easily measured, such as those in R&D, a performance management system should be designed to accommodate the nuanced and less tangible aspects of their contributions.

The nucleus of performance. Many organizations have traditionally placed a strong emphasis on individual performance, rooted in the belief that individual accountability drives results. In recent years, there has been a noticeable shift toward recognizing the importance of the team in achieving overall organizational success.

At a large European online retailer, for instance, the focus of performance management has been put on the team rather than the individual. Goals are set for the team, feedback is given to the team, and the performance appraisal is conducted for the team. Example performance metrics for teams can include project completion timelines, cross-functional collaboration success, and the achievement of collective milestones. On an individual level, the company assesses performance using a sophisticated model that prescribes skills and behaviors for 14 job families, each with up to four hierarchies.

Another prominent company in the automotive industry underscores the team as the cornerstone of performance. The teams could be defined along both functional and organizational lines—such as the division or the business line—and the company linked the organizational lines’ performance to the individuals’ compensation.

Performance reviews

Performance reviews raise the question of how to balance the individual objectives and their appraisal with respect to the “what” and the “how,” as well as whether review responsibility should lie primarily with managers, committees, or a combination of both.

Performance formula: What versus how. The balance between setting objectives and assessing what employees accomplish and how they go about their work is the central focus here. To measure the “what,” reviews have traditionally used KPIs, concentrating on quantifiable metrics and specific targets and emphasizing measurable outcomes and achievements. 2 For more on metrics best practices and how they can help leaders avoid pitfalls in their performance management systems, see Raffaele Carpi, John Douglas, and Frédéric Gascon, “ Performance management: Why keeping score is so important, and so hard ,” McKinsey, October 4, 2017.

However, for many roles and in many segments of the company, the work is complex, multifaceted, and fast-paced and can be difficult to capture with rather static KPIs. Consequently, many companies have reverted to using objective key results (OKRs) to link results to defined objectives. The objectives represent the qualitative, aspirational goals an individual or team aims to achieve, while the key results are the quantifiable metrics used to measure progress toward those objectives. The objectives provide context and direction, capturing the broader strategic intent behind the measurable key results.

Companies that explicitly focus a portion of performance reviews on the “how” consider qualities such as collaboration, communication, adaptability, and ethical decision making. Considering behavior and conduct, in particular, can help assess leaders whose teams’ outcomes are hard to measure—such as long-term projects, complex initiatives, or qualitative improvements that may not have easily quantifiable metrics. About three in five companies in our sample look at a mix of both what and how, which can equip managers with a more comprehensive understanding of not only tangible results but also the underlying approach and mindset that contributed to those outcomes.

Review responsibility. In structuring accountability for conducting performance reviews, companies tend to lean on managers, committees, or a combination of both.

Managers should play a central role, and their discretion should be a significant factor in performance assessments because they can judge the context in which an employee has been working. For example, when evaluating performance, it’s crucial to consider the headwinds and tailwinds that the business, team, or employee faced during the evaluation period. External factors, market conditions, and organizational dynamics can significantly affect an employee’s ability to achieve their goals, and considering them helps provide a fair and contextual assessment.

In this context, another design question emerges: whether to appraise employees against OKR fulfilment or the effort they put into achieving the desired outcome. Particularly in many large digital players, OKRs are set as “moonshot” goals—objectives so ambitious they are difficult to achieve. Managers can help ensure that, at the end of the performance cycle, an employee is assessed against not only OKR fulfillment but also—and to an even greater degree—how hard they tried given the resources available to them.

Managers’ points of view, formed with knowledge of the circumstances that produced employees’ performance, produce richer assessments that are sensitive to context—given that managers work closely with their team members and have firsthand knowledge of the challenges, workloads, and specific situations that each employee encounters.

Committees, meanwhile, bring diverse perspectives and can mitigate biases that might arise from individual managers’ subjectivity. Committees can provide a checks-and-balances system, promoting consistency and standardization in the evaluation process.

A combination of these two approaches can be an effective solution. Senior managers and high performers across hierarchies could be discussed in committees, while the rest of the workforce could be evaluated by their direct managers. This integrated approach leverages the contextual insights of managers while also incorporating the diverse viewpoints and standardization that committees offer, particularly for more-senior or high-impact roles.

Regardless of the review responsibility structure, it’s worth noting that more and more managers, committees, and employees are using generative AI (gen AI) to aggregate and extract information to inform performance reviews. For example, some employees may toil to define clear, specific, and measurable goals that align with their career aspirations; gen AI can help create a first draft and iterate based on their role, helping the employee focus on their specific growth areas as well as gauge improvement on an ongoing basis. Managers and committees, meanwhile, used to spend a lot of time gathering performance metrics from different sources and systems for employee evaluation. Gen AI can aggregate input from various sources into a consolidated format to provide managers with a more comprehensive starting point for reviews.

Beyond employees’ formal professional-development opportunities, their managers’ capability to set goals, appraise performance fairly and motivationally, and provide feedback is one of the most critical success factors for an effective performance management system. As a result, many companies have pivoted to invest in focused capability building.

Ongoing development

Another key aspect to consider when designing a performance management system is the focus of the assessment: will it evaluate past performances, or will the emphasis be placed on creating an understanding and foundation for further growth?

A backward-looking assessment will focus on fulfillment of the what and how objectives to create a fair basis for ranking and related consequences. However, many companies are pivoting to complement this assessment or are even focusing entirely on a developmental appraisal. In this approach, the focus is on truly understanding the strengths and weaknesses of the individual as a basis for further development, capability building, and personal growth.

Against that backdrop, rather than concentrating solely on top performers, an inclusive developmental system should cater to the growth needs of employees across all levels and backgrounds. McKinsey research emphasizes the importance of ongoing development for all employees, including—crucially—efforts tailored specifically for women 3 Women in the Workplace 2023 , McKinsey, October 5, 2023. and other underrepresented groups. 4 Diversity matters even more: The case for holistic impact , McKinsey, December 5, 2023. Such development programs not only foster a more equitable culture but also help unlock the full potential of the entire workforce.

Traditionally, many companies have used relative ratings to compare and rank employees against one another, often resulting in a forced distribution or curve. Employees are placed into categories or tiers based on their relative performance, with a predetermined percentage falling into each category (for example, top 10 percent, middle 70 percent, and bottom 20 percent).

Many companies today are simplifying their ratings systems so employees understand where they stand while shifting toward development approaches tailored to individuals’ strengths and weaknesses. The goal is to identify areas for growth and provide targeted support to help employees enhance their capabilities and skills.

While assessing performance remains important, the emphasis should be on using those assessments as a starting point for identifying developmental opportunities, with an understanding of both strengths and weaknesses and the specific development needs to improve performance. The focus shifts from mere evaluation to understanding the underlying factors that contribute to an individual’s performance, be it skills gaps, mindsets, or environmental factors.

Four reward categories—compensation, career progression, development opportunities, and recognition—remain the core pillars of an effective performance management system. Most leading companies provide individual rewards (as opposed to team- or corporate-driven ones), with equal relevance given to short- and long-term incentives, looking at impact holistically and balancing investment in all four reward categories.

Under certain circumstances, it may make sense to emphasize financial rewards, particularly in sales functions or other roles where monetary incentives are highly valued. Indeed, some organizations may double down on monetary compensation, offering significantly higher pay packages to their top performers, because money is seen as a key motivator in these roles.

In other cases, it may be more effective to take money off the table and emphasize nonfinancial rewards, such as recognition, flexibility, and career development opportunities. While base pay may remain the same across the firm, high performers can be rewarded with faster career progression, more recognition, and better development opportunities. A 2009 McKinsey survey found that “three noncash motivators—praise from immediate managers, leadership attention (for example, one-on-one conversations), and a chance to lead projects or task forces” were “no less or even more effective motivators than the three highest-rated financial incentives: cash bonuses, increased base pay, and stock or stock options.” Furthermore, “The survey’s top three nonfinancial motivators play critical roles in making employees feel that their companies value them, take their well-being seriously, and strive to create opportunities for career growth.” 5 “ Motivating people: Getting beyond money ,” McKinsey Quarterly , November 1, 2009. More than a decade later, McKinsey research found that managers and employees remain misaligned: specifically, employers overlook the relational elements—such as feeling valued by a manager and the organization and feeling a sense of belonging—relative to how important these factors are to employee retention (Exhibit 2). 6 “ ‘ Great Attrition’ or ‘Great Attraction’? The choice is yours ,” McKinsey Quarterly , September 8, 2021. Indeed, the importance of nonmonetary incentives represents a consistent theme in performance management research and inquiry.

Given the time and effort required to effectively implement nonfinancial rewards, it’s crucial for organizations to carefully consider how to deploy these rewards strategically with employee groups. The decision of where to place emphasis should align with the organization’s culture, values, and the specific workforce’s motivations.

It’s worth noting that companies focusing on team achievement over individual performance also tend to value praise of the team. Public recognition and praise for effective teamwork and joint accomplishments can foster a sense of unity, camaraderie, and motivation.

Things to get right

Of the global companies we observed, there was a shared set of enabling factors across those with effective performance management systems. These things are fairly intuitive, but they are hard to practice well. Done consistently, they can produce powerful results.

• Ensure that performance management systems are agile. Systems should allow for goals to be easily updated so the workforce—and therefore the organization—can respond to quickly changing conditions. The processes themselves should also be agile. For instance, relationships and interactions between managers and employees should allow for coaching that is close to real time so employees are consistently being pushed in the right direction—and learning to create that momentum themselves.
• Provide regular feedback. Annual reviews can create a bottleneck on managers and the C-suite. More regular performance conversations can be successful in a variety of formats; quarterly, weekly, and casual check-ins should supplement formal reviews. Conversations can be about both the what and the how of the work and be a source of ongoing coaching.

If reviews remain once a year rather than more frequent, top management may consider prioritizing their direct involvement in the evaluation process to keep a pulse on employee sentiment and progress. A leading financial institution in Europe chose this route and found it was able to build a strong capability-building program around a feedback culture that is unafraid of difficult conversations.

• Establish an effective fact base. According to our research, only two in five companies use both upward and downward evaluation in individual performance reviews. To establish a more comprehensive fact base, organizations can implement robust 360° review processes that solicit feedback from an employee’s manager, peers, direct reports, and even customers or stakeholders outside the company. Many leaders have found that 360° reviews offer a comprehensive understanding of an individual’s performance because such reviews consider perspectives from both those who are led and those who are in leadership roles.
• Maintain rating and differentiation. Many companies have reassessed their approach to employee ratings and the subsequent differentiation of consequences. While some companies have eliminated ratings altogether, most companies have been evolving their systems to drive motivation, recognize and incentivize performance, and create a “talent currency.” This means a high performer from one division is considered by the organization to be of the same caliber as one from another division. Overall, leaders are pushing for simplification, such as moving from a seven-tier approach to a four-tier or even three-tier system. There is also a stronger link between ratings and outcomes, as well as a shift from forced distribution to distribution guidance.
• Employ gen AI. Gen AI—the latest technology to change the business landscape—can be a tool to support select elements of performance management, such as setting goals and drafting performance reviews. A manager could use the technology to aggregate and synthesize input from different sources to draft communications to and about employees more efficiently, freeing them to focus on the core value driving parts of performance management and giving more time for personal interactions with their employees, such as coaching and feedback. 7 For more, see People and Organization Blog , “ Four ways to start using generative AI in HR ,” blog post by Julian Kirchherr, Dana Maor, Kira Rupietta, and Kirsten Weerda, McKinsey, March 4, 2024.

Getting started

Companies can get started by understanding where they are now. Specifically, they should assess their organizations’ current performance culture, including the level of adoption of the existing performance management system and its quality. Decision makers should then use the following three questions to check the health of their performance management efforts and outline their ambitions for performance management:

• Are we getting the expected returns from the time invested in the performance management process, and does it drive higher performance and capabilities?
• Does the current performance management system reflect the needs and context of this particular business or workforce segment?
• Do we have a performance culture? (Hint: How frequent are employees’ coaching interactions? How clear and differentiated is feedback?)

Many traditional approaches to people management are unlikely to suffice in today’s top-performing organizations. The research-backed benefits of prioritizing people’s performance, from enhanced revenue growth to lower attrition rates, underscore the strategic importance of these systems. By embracing a fit-for-purpose design anchored in the key elements of performance management, organizations can position themselves as dynamic and adaptive employers.

Simon Gallot Lavallée is an associate partner in McKinsey’s Milan office, where Andrea Pedroni  is a partner; Asmus Komm is a partner in the Hamburg office; and Amaia Noguera Lasa is a partner in the Madrid office.

The authors wish to thank Katharina Wagner, Brooke Weddle, and the many industry professionals who contributed to the development of this article.

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• v.42(4); 2019 Dec

Evidence-Based Performance Management: Applying Behavioral Science to Support Practitioners

Matthew d. novak.

4001 Dole Human Development Center, Department of Applied Behavioral Science, University of Kansas, 1000 Sunnyside Avenue, Lawrence, KS 66045 USA

Florence D. DiGennaro Reed

Tyler g. erath, abigail l. blackman, sandra a. ruby, azure j. pellegrino.

The science of behavior has effectively addressed many areas of social importance, including the performance management of staff working in human-service settings. Evidence-based performance management entails initial preservice training and ongoing staff support. Initial training reflects a critical first training component and is necessary for staff to work independently within an organization. However, investment in staff must not end once preservice training is complete. Ongoing staff support should follow preservice training and involves continued coaching and feedback. The purpose of this article is to bridge the research-to-practice gap by outlining research-supported initial training and ongoing staff support procedures within human-serving settings, presenting practice guidelines, and sharing information about easy-to-implement ways practitioners may stay abreast of current research.

Train people well enough so they can leave, treat them well enough so they don’t want to. —Richard Branson

The science of behavior has effectively addressed many areas of social importance including education (e.g., Sulzer-Azaroff & Gillat, 1990 ), traffic safety (e.g., van Houten, Nau, & Marini, 1980 ; Yeaton & Bailey, 1978 ), substance use (e.g., Higgins, Silverman, & Heil, 2007 ), parent training (e.g., Lindgren et al., 2016 ; Phaneuf & McIntyre, 2007 ), behavioral medicine (e.g., Piazza, Milnes, & Shalev, 2015 ), and others. Perhaps the most widely known application is the behavioral treatment of autism (Freedman, 2016 ). Due to the research supporting its effectiveness (e.g., National Autism Center, 2009 , 2015 ), autism treatment based on the principles of behavior analysis is endorsed by the U.S. Surgeon General (U.S. Department of Health & Human Services, 1999 ), National Institutes of Health (Strock, 2007 ), and the National Research Council (Lord & McGee, 2001 ). The model that has evolved for the provision of services to individuals with autism and other disabilities presents a challenge that is unique to those in health and human services. Whereas psychological therapy is delivered by licensed psychologists and medical procedures are performed by doctors, behavior analysts with the most amount of training and education (i.e., Board Certified Behavior Analysts®) often do not deliver services directly. Rather, they typically oversee the provision of services delivered by others. Thus, the challenge for those providing behavioral services to vulnerable populations is ensuring that individuals with relatively less training and education (i.e., Registered Behavior Technicians® or Board Certified Assistant Behavior Analysts®) provide direct services in an effective and responsible manner.

To be successful, this unique service model necessitates effective performance management—the careful training and supervision of staff who implement behavioral treatment. Unfortunately, recent research suggests the field could benefit from improvements in this area. DiGennaro Reed and Henley ( 2015 ) administered a survey to certified and aspiring behavior analysts to determine the extent to which evidence-based staff training practices were implemented by their employers. The results were worrisome and launched efforts by the authors to disseminate recommended practices to practitioners and organizational leaders (e.g., DiGennaro Reed, 2016 , 2017 , 2018 , 2019 ; Henley, 2018 , 2019 ). Only 55% of respondents indicated they received initial training after being hired; when training was provided, organizations relied on tactics with little empirical support, such as instruction alone. Fortunately, 71% of respondents reported they received ongoing training and support, but primarily in the forms of a lecture or monthly feedback, which are typically less effective than other forms of performance management. Respondents who worked as supervisors were also queried about the training they received to prepare them for the important responsibility of leading and managing staff. Only 33% indicated they received any formal training on how to effectively implement research-supported supervision practices. These results suggest training and performance management in settings that employ behavior analysts are not consistent with recommended practices. Many respondents began working without any formal training, received less-than-ideal ongoing support, and were expected to supervise staff without any guidance regarding best practices.

Many practicing behavior analysts lack sufficient training and ongoing support, which is worrisome because the lack of evidence-based staff training and performance management may lead to negative outcomes, including staff turnover, poor service quality, and charges of unethical conduct. Kazemi, Shapiro, and Kavner ( 2015 ) surveyed 100 behavior technicians from several companies and found that satisfaction with initial training, ongoing staff support, and supervisor behavior were key factors influencing respondents’ intent to quit their jobs. These results suggest that providing evidence-based staff training may help to mitigate staff turnover, which is reported to be as high as 75% within human-service organizations (Kazemi et al., 2015 ). Moreover, staff turnover places substantial financial strain on an organization, with average costs ranging from $5,000 for a single behavior technician to $10,000 for a certified behavior analyst (Sundberg, 2016 ).

In addition to affecting workforce stability, insufficient training and performance management may further disrupt the quality of behavioral services by influencing treatment integrity—the extent to which prescribed treatment procedures are implemented correctly (Peterson, Homer, & Wonderlich, 1982 ). In a review of 19 parametric analyses of treatment integrity, Brand, Henley, DiGennaro Reed, Gray, and Crabbs ( 2019 ) reported that treatment integrity errors produce unpredictable client outcomes. Although, in some instances, errors in behavioral treatment did not negatively influence client skill acquisition or problem behavior (e.g., Leon, Wilder, Majdalany, Myers, & Saini, 2014 ), in general researchers showed that integrity errors resulted in slower learner progress and less effective treatment. These findings underscore the importance of ensuring that staff implement treatment protocols as designed, which is fostered by the quality of training and performance management staff experience.

Insufficient performance management practices may have consequences that extend beyond affecting direct services; they may carry severe consequences for behavior analysts individually as well as for the profession more broadly. To ensure quality provision of services, the Behavior Analyst Certification Board® (BACB®) Professional and Ethical Compliance Code for Behavior Analysts (BACB, 2014 ) outlines a set of guidelines that all behavior analysts must follow. For example, section 5.03 of the Code states, “If the supervisee does not have the skills necessary to perform competently, ethically, and safely, behavior analysts provide conditions for the acquisition of those skills” (p. 14). Thus, supervisors are obligated to provide staff with effective training. On the topic of ongoing staff support, section 5.06 states, “Behavior analysts design feedback and reinforcement systems in a way that improves supervisee performance. Behavior analysts provide documented, timely feedback regarding the performance of a supervisee on an ongoing basis” (p. 14). Together these statements indicate that behavior analysts must rely on evidence-based staff training and performance management procedures to ensure compliance with this code. Failure to do so may result in ethical charges against the credentialed behavior analyst, which could lead to loss of certification or state licensure.

Evidence-based performance management involves a program that includes initial preservice training and ongoing staff support. Initial training, often referred to as orientation or onboarding , reflects a critical first training component and is necessary for staff to work independently within an organization. However, investment in staff must not end once preservice training is complete. Ongoing staff support should follow preservice training and it involves supervisors providing continued coaching and feedback regarding the staff’s performance in one or more areas. The purpose of this article is to bridge the research-to-practice gap by outlining research-supported initial training and ongoing staff support procedures within human-service settings, presenting practice guidelines based on our experience and current research, and sharing information about ways to stay up to date with research.

Preservice Training

The natural first step to ensuring high-quality staff training is the delivery of preservice training, which allows new employees to learn relevant job skills in a controlled, distraction-free environment. Although orientation and onboarding procedures are ubiquitous across all forms of employment, the presence of training alone does not guarantee proficiency with job skills. To be most effective, preservice training should use empirically supported training techniques. One empirically supported technique is behavioral skills training (BST), which is a procedure used to train new skills through a package including instruction, modeling, rehearsal, and feedback (Parsons, Rollyson, & Reid, 2012 ). Behavioral skills training can be implemented individually or in groups and has been used to train several tasks in the human service industry, including discrete trial instruction (Sarokoff & Sturmey, 2004 ) and mand training (Nigro-Bruzzi & Sturmey, 2010 ) among others. Each component of BST is outlined below.

Instruction

The first component of BST is instruction, which involves describing a target skill or behavior one expects the trainee to perform (Miltenberger, 2016 ). Trainers can deliver instruction by describing procedures vocally (e.g., lecture, discussion) or textually (e.g., written protocols). Written protocols can include text alone or text with supplemental components, such as diagrams and images (i.e., enhanced written instructions; Berkman, Roscoe, & Bourret, 2019 ; Graff & Karsten, 2012 ). All too often, preservice training ends after instruction alone (DiGennaro Reed & Henley, 2015 ). It is critical to know that instruction alone is insufficient in training new skills (Ducharme & Feldman, 1992 ). Instead, training should begin with instruction followed by the other components that comprise BST.

This is not to say that instruction does not influence performance. Indeed, there are several ways in which instruction can be delivered to influence trainees’ performance. For example, Henley, Hirst, DiGennaro Reed, Becirevic, and Reed ( 2017 ) compared the use of directive instructions (e.g., “you must”) to nondirective instructions (e.g., “you might consider”) on trainees’ responding under changing reinforcement schedules in a laboratory task. When presented with directive instructions, participants responded in accordance with the instructions, even when the instructions were inaccurate (i.e., instructions did not match the reinforcement schedules). Participants in the nondirective condition, however, responded in accordance with the reinforcement schedules, independent of the instructions. Studies on this topic suggest that, when creating instructions for staff, it is important to consider how instructions are delivered, as minor variations may affect performance.

There are isolated instances in the literature of participants correctly performing skills after detailed instruction alone. For example, Graff and Karsten ( 2012 ) taught staff to effectively conduct preference assessments using enhanced written instructions, which included a detailed data sheet, diagrams, and step-by-step instructions written without technical jargon. However, Shapiro, Kazemi, Pogosjana, Rios, and Mendoza ( 2016 ) only partially replicated Graff and Karsten’s findings and had to include additional training procedures to reach criterion performance. Instances of performing to criterion after instruction alone are rare and may depend on various factors, such as the skill being trained, the instruction format, and the trainee’s history. Because these several factors must align for instruction alone to be effective, it is prudent to implement all components of BST when conducting preservice training.

Practice Guidelines

We recommend that trainers present clear and succinct instructions about procedures, as Jarmolowicz et al. ( 2008 ) demonstrated that treatment adherence is better when instructions are written in a conversational form than in technical language. Moreover, it may be helpful to provide jargon-free, written protocols with diagrams (Graff & Karsten, 2012 ) that staff can use during training and refer to later, if needed. In our consultation experience, we have observed that trainees often appreciate the rationale for certain procedures, and providing that information may help guard against performance drift, though research is still needed in this area. Finally, we recommend trainers and supervisors be transparent about specific behaviors that will be observed and measured. It is presumed that the behaviors that will be observed and measured are of the utmost importance and, thus, should not be kept a secret from trainees. Also, new staff members generally want to perform well and may become nervous about their responsibilities and being observed. In our experience, transparency about what is expected and how performance will be measured generally reduces trainees’ nervousness.

The second component of BST is modeling, which involves an experienced staff person demonstrating perfect performance of a target skill or behavior one expects the trainee to imitate (Miltenberger, 2016 ). Modeling can take place in person or shown via video. Video modeling includes the advantages of conserving resources if used over time and being transportable, allowing trainees the opportunity to view the video model outside of the training session. Further, a live model may contain slight errors or inconsistencies across trainings that affect training outcomes; video modeling provides the added benefit of standardizing training procedures and ensuring that only desired models are shown 1 (DiGennaro Reed, Blackman, Erath, Brand, & Novak, 2018 ; Shapiro & Kazemi, 2017 ).

Recent research has shown video modeling, in particular video modeling with voiceover instruction, to be more effective than written instructions alone—though feedback was required for some participants—when training new staff to implement discrete trial instruction and behavior reduction interventions (e.g., DiGennaro Reed, Codding, Catania, & Maguire, 2010 ; Giannakakos, Vladescu, Kisamore, & Reeve, 2016 ). Furthermore, staff effectively learned how to conduct preference assessments after receiving training comprised of video modeling with voiceover instruction (e.g., Delli Bovi, Vladescu, DeBar, Carroll, & Sarokoff, 2017 ).

When incorporating modeling in training, it is important to model the entire procedure for the trainee. In addition, we recommend standardizing the models across training episodes to ensure the relevant skills are being modeled consistently. The latter recommendation may be accomplished by relying on video models or ensuring live models receive written protocols to follow during training. Finally, to aid in generalization, modeling should entail multiple exemplars of the target skill (Moore & Fisher, 2007 ). DiGennaro Reed, Erath, Brand, and Novak ( 2019 ) provide resources for creating video models, which readers may find beneficial.

The third component of BST, rehearsal—also referred to as practice or role play—involves having trainees practice a target skill (Miltenberger, 2016 ). Rehearsal can be arranged in multiple ways, such as using a trained researcher or confederate (e.g., Iwata et al., 2000 ; McGimsey, Greene, & Lutzker, 1995 ; Phillips & Mudford, 2008 ), another trainee who is acquiring the skill being rehearsed (e.g., Palmen, Didden, & Korzilius, 2010 ; Wallace, Doney, Mintz-Resudek, & Tarbox, 2004 ), a service recipient (e.g., Erbas, Tekin-Iftar, & Yucesoy, 2006 ), or by varying the number of rehearsal opportunities (e.g., Jenkins & DiGennaro Reed, 2016 ). An important distinction is that rehearsal alone does not guarantee high levels of performance; in fact, it may allow trainees to practice errors, which may impede acquisition (Ward-Horner & Sturmey, 2012 ). Thus, rehearsal is typically accompanied by performance feedback and continues until trainees achieve mastery (Reid, Parsons, & Green, 2011 ).

In suggesting guidelines for trainers, we offer that practice does not make perfect; rather, practice with feedback makes perfect. That is, feedback should be delivered immediately following each rehearsal opportunity; thus, rehearsal and feedback should occur in tandem. Feedback is described in more detail in the next section. To help trainees acquire all relevant skills, the trainer must engineer opportunities for the trainee to practice the entire procedure, respond to a range of client responses, receive feedback, and meet a mastery criterion. These opportunities include using confederates in-vivo or in an analog setting, and having the confederate behave in scripted or predetermined ways to ensure the trainee practices all the components of a procedure and responds to a range of behaviors. Allowing trainees to respond to many situations is important, especially when dealing with vulnerable populations and procedures that need to be implemented with high integrity.

The fourth component of BST is feedback, which refers to information about past performance that specifies how the trainee can improve performance in the future (Miltenberger, 2016 ). At this stage of training, feedback should be delivered immediately after each rehearsal opportunity and specify steps performed correctly and steps requiring correction (DiGennaro Reed et al., 2018 ). Several reviews of the literature reveal there are various dimensions of feedback, such as its source (supervisor, peer), medium or mode (written, verbal), frequency (daily, weekly), recipients (individuals, groups), privacy (private, public), and content (type of information provided; Alvero, Bucklin, & Austin, 2001 ; Balcazar, Hopkins, & Suarez, 1985 ; Prue & Fairbank, 1981 ). In addition, the way in which corrective and positive feedback are sequenced can influence its efficacy (Henley & DiGennaro Reed, 2015 ; Slowiak & Lakowske, 2017 ). Although supervisors and trainers have flexibility regarding how to implement the various dimensions of feedback, it is likely most efficient and effective to deliver both corrective and positive verbal feedback immediately upon completion of rehearsal.

The numerous variations and dimensions of feedback present a challenge to researchers seeking to examine the most effective combinations. Thus, no practice recommendations with an exact combination of methods can be made, which may be impractical as most supervisors are subject to various organizational and logistical constraints that limit their control over certain factors. However, research on the dimensions of feedback and its delivery has produced results with enough consistency to support general practice guidelines.

We recommend trainers base their feedback on direct observations rather than verbal reports or indirect measures. The use of observational data provides important information for the trainer and may also be used as a data source for delivering feedback. Next, trainee performance may improve faster if corrective feedback is presented before positive feedback (Henley & DiGennaro Reed, 2015 ); however, we often ask trainees to specify their preference for the order in which feedback is delivered. Third, supervisors should deliver feedback immediately after performance, as research suggests immediate feedback is more effective than delayed feedback (Goodman, Brady, Duffy, Scott, & Pollard, 2008 ) and staff prefer immediate feedback compared to delayed feedback (Reid & Parsons, 1996 ). We also recommend that feedback is used in conjunction with the components of BST described previously. Finally, it is important that feedback is delivered in a respectful and professional manner to maintain a positive working relationship, in particular when corrective feedback must be shared.

Ongoing Staff Support

It would be a mistake to assume that, once preservice training is complete, staff will perform all skills with high integrity while on the job and in a complex real-world environment. Thus, high-quality preservice training should be viewed as the initial investment in the professional development of staff. Based on decades of research, it is reasonable to assume that staff may not generalize skills learned in a contrived training environment to the actual work setting or maintain high levels of performance over extended periods of time. To address these challenges and support the maintenance and growth of staff skills, ongoing coaching is necessary. In the following sections, we outline how supervisors can provide ongoing support to staff following preservice training.

Observations and Feedback

The next step in the training process is the provision of ongoing supervision and support. This usually involves supervisory observations of the staff implementing varied procedures. The purpose of direct observations is twofold: to provide the supervisor with opportunities to monitor treatment integrity in the natural environment and to use data to provide performance feedback to staff. Depending on contextual variables operating in the organization (e.g., staff schedules, supervisor schedules, the setting), these observations can vary widely in when, how, and how often they are employed. For example, observations can be scheduled in advance or unscheduled drop-ins ( when ); viewed live (i.e., in-vivo) or via video recordings ( how ); and conducted as often or as little as needed, depending on staff performance, feasibility, and other related variables ( how often ).

Although variability exists regarding how supervisory observations are implemented, one commonality across all variations is to ensure recommended practices are being used. Table ​ Table1 1 depicts an on-the-job training protocol (adapted from Ricciardi, 2005 ) for using recommended practices to conduct ongoing observations. This protocol uses a competency-based approach to training (e.g., Reid & Parsons, 2002 ), and shares many of the same components used in initial training procedures (e.g., instruction, rehearsal, performance feedback). Thus, divergence from initial training procedures is more in relation to the training process , not training content , wherein the goal of ongoing supervision observations is to provide practice opportunities for staff to demonstrate high levels of treatment integrity in their actual workplace setting. The provision of supervision and support in this capacity also affords other benefits, such as the opportunity for supervisors and staff to troubleshoot issues regarding implementation in practice—an issue which may not have been present in the controlled training settings where initial training typically occurs. Related to this, supervisors can also embed coaching procedures (e.g., prompting, prompt fading, reinforcement) into their observations to facilitate staff implementation at mastery levels.

On-the-job training protocol (adapted from Ricciardi, 2005 )

Pay for Performance

An important consideration for maintaining desirable performance is the method by which staff are compensated for their work. Most compensation systems in the United States involve pay-for-time systems, in which compensation is primarily based on the amount of time spent at work, not performance of job duties. The prevalence of pay-for-time systems presents an interesting challenge for behavior-analyst supervisors, as the primary contingency (i.e., pay) is delivered largely independent of performance of job duties. Although pay-for-performance systems likely maintain higher quality and quantity work than pay-for-time, several factors impede implementation of the pay-for-performance systems.

The first barrier to performance-contingent pay is that many supervisors may not be in a position in their organization where they are able to dramatically change existing pay structures. Those supervisors who have control over organizational pay structures would also be likely to experience resistance from staff due to the ubiquity of traditional pay structures. A second barrier to pay-for-performance systems is a concern that these systems may place undue stress on employees—because their income is tied directly to their performance (Ganster, Kiersch, Marsh, & Bowen, 2011 ). This issue is made worse when incentive systems are dependent on factors beyond staff control.

Notwithstanding these barriers, supervisors must identify methods for reinforcing desirable performance within a traditional pay-for-performance system. A large body of research on the use of incentives in organizational settings suggests that desirable staff performance can be maintained by monetary incentives that account for a relatively small proportion of total compensation for staff (e.g., Dickinson & Gillette, 1994 ). That is, desired performance is maintained by the presence of an incentive contingency, not the percentage of incentive pay (Poling, Dickinson, Austin, & Normand, 2000 ). Thus, one solution may be for supervisors to use monetary incentives in conjunction with traditional pay systems—readers in organizations capable of and interested in providing performance-based pay are directed to Abernathy ( 1996 , 2014 ) for additional resources. Note that this type of system is not without limitations. First, monetary incentives must be arranged so they are sustainable over an extended duration, and many human-service settings simply do not have the funds to maintain these efforts. Second, monetary incentives may be subject to certain federal and state labor regulations (e.g., Fair Labor Standards Act of 1938 ), which may create unwanted logistical difficulties for an organization. Thus, despite the advantages of using a generalized conditioned reinforcer in the form of monetary incentives, supervisors may seek alternative forms of incentive delivery to maintain desirable staff performance.

Identifying Potential Incentives

Although supervisors may feel confident in their ability to select effective nonmonetary incentives for their staff, we urge caution in doing so. Wilder, Rost, and McMahon ( 2007 ) asked supervisors to rank-order potential incentives based on how effective they thought the incentive would be for each of their employees. When comparing supervisor predictions with employee rankings, Wilder et al. observed high agreement between supervisors’ indication of their employees’ most preferred items or activities; however, few supervisors accurately predicted moderate- and lower-preferred items or activities. These findings were replicated by Wilder, Harris, Casella, Wine, and Postma ( 2011 ) and suggest that supervisors generally do a poor job at predicting effective incentives.

Daniels and Bailey ( 2014 ) offer a systematic procedure to assist with selecting incentives. First, supervisors should consider what types of incentives they can reasonably provide. At this stage it is important to consider that incentives may be a mix of items, activities, or privileges. Whereas monetary and most tangible incentives have an inherent cost to an organization, many activities or privileges may come at little or no cost. For example, Iwata, Bailey, Brown, Foshee, and Alpern ( 1976 ) maintained high levels of daily care and training activities from staff working in a residential facility using an incentive where staff could rearrange their days off for the following week. Another important consideration at this stage is that supervisors should select items or activities that are sustainable for use for the indefinite future. Although reinforcement schedules may be thinned over time, the incentive program is only effective for as long as it is being implemented. Supervisors may need to have conversations with their organization’s management to identify incentives that the organization allows and can support—so the supervisor does not have to pay for it out-of-pocket.

Second, supervisors may wish to discuss these options for potential incentives with staff to identify a small number of items, activities, or privileges. This step should be conducted after first identifying potential items and activities because, otherwise, employees do not know what is available or may ask for things that cannot be delivered (see Daniels & Bailey, 2014 ).

Finally, after potential incentives have been identified, supervisors should conduct a systematic preference assessment with staff. Although there is a rich literature evaluating methods for assessing preference in clinical populations with limited verbal repertoires (e.g., Fisher et al., 1992 ), these methods are likely not appropriate for staff with strong verbal repertoires (see Waldvogel & Dixon, 2008 ). Two commonly used methods for assessing employee preference for incentives are a reinforcer survey (Daniels & Bailey, 2014 ) and a ranking procedure (Waldvogel & Dixon, 2008 ; Wine, Reis, & Hantula, 2014 ). The reinforcer survey asks employees to rate how much work they would be willing to do for each item or activity on a Likert-type scale from 0 ( none at all ) to 4 ( very much ). The ranking procedure is similar but provides a relative value for each potential incentive by asking employees to rank the items or activities from least to most preferred. Both the survey and ranking procedure provide relatively accurate indications of effective incentives—although the survey method may be better at identifying a greater range of effective incentives (see Wine et al., 2014 for a comparison).

Incentive Delivery

A final consideration for ensuring effective use of incentives is the way they are delivered. Some variables that warrant additional consideration for use with staff include incentive quality, probability of delivery, and delay to delivery. Incentive quality is largely determined by preference, although incentive magnitude and schedule also affect quality. Incentives may be delivered on a dense schedule initially and thinned once the employee has consistently demonstrated desired performance. Two considerations with respect to quality are that staff preferences may shift over time (Wine, Gilroy, & Hantula, 2012 ) and the use of incentives of varied preference may maintain high levels of performance (Wine & Wilder, 2009 ). Thus, supervisors should consider assessing preference on a regular basis and using a variety of moderate- to high-preferred incentives.

Although rules can help bridge the gap of delays to reinforcement, supervisors should seek to minimize delays as much as possible. In addition, with respect to the probability of incentive delivery, reinforcers may not need to be delivered each time. Though there is little research assessing probability of incentive delivery in OBM settings, several studies have demonstrated the effectiveness of lottery systems at maintaining performance (e.g., Cook & Dixon, 2006 ; Iwata et al., 1976 ). Taken together, there has been little OBM research assessing the relative impact of reinforcer dimensions. However, recent research incorporating the area of behavioral economics has provided a promising methodology through which a thorough understanding may be developed (e.g., Henley, DiGennaro Reed, Reed, & Kaplan, 2016 ; Wine et al., 2012 ).

Assessing Performance Problems

Despite best efforts to train and provide follow-up support to staff, supervisors will likely encounter instances of less-than-desirable performance. As is true with service delivery in clinical populations, performance management interventions typically provide benefit when they are informed by preintervention functional assessment. Though several informant assessments exist and have been implemented with success (e.g., Daniels & Lattal, 2017 ; Mager & Pipe, 1984 ), the Performance Diagnostic Checklist–Human Services (PDC–HS; Carr, Wilder, Majdalany, Mathisen, & Strain, 2013 ) has emerging support for use in human-service settings. The PDC–HS may be especially advantageous for BCBAs in supervisory positions who may have limited OBM experience as it is less time consuming and does not require the same level of expertise as behavioral systems analysis (for more information about behavioral systems analysis, see Johnson, Casella, McGee, & Lee, 2014 ; McGee & Diener, 2010 ; Sigurdsson & McGee, 2015 ). The PDC–HS is an informant assessment that may be used to identify variables causing or maintaining substandard performance. The assessment consists of 20 questions across four domains: (a) training; (b) task clarification and prompting; (c) resources, materials, and processes; and (d) performance consequences, effort, and competition. As its name suggests, the PDC–HS was developed specifically for use in human service settings, and the questions and domains were developed to target environmental variables that commonly affect performance in this particular setting.

The first section, training , contains questions about the type of training received and whether the employee has demonstrated desired levels of performance in the past. The second section, task clarification and prompting , includes questions about the employee’s knowledge of job requirements and the environment where the behavior is expected to occur. Third, the resources, materials, and processes section contains questions about the organization’s systems and resources that may be beyond the employee’s control. Finally, the performance consequences, effort, and competition section includes questions about overall supervisor support and supervision, feedback, and potential competing activities.

Carr et al. ( 2013 ) indicated that seven of the items on the PDC–HS can be answered through direct observation and recommended administering the remaining 13 items through discussion with the employee’s supervisor. Practitioners administering the PDC–HS might consider also administering it with multiple supervisors or across different levels of the organization (e.g., management, supervisors, employees) as there may not be 100% agreement across all relevant parties (e.g., Merritt, DiGennaro Reed, & Martinez, 2019 ).

When complete, results of the PDC–HS are scored by counting the number of items for which an area of concern was flagged in each domain (see Carr & Wilder, 2016 ; Carr et al., 2013 ); the domain with the most flagged items typically indicates the “function” of the performance problem, or the area to be targeted for intervention. Where the PDC–HS may be particularly useful is the accompanying intervention planning guide, which provides a list of recommended interventions (with supporting literature) for each domain. For example, Bowe and Sellers ( 2018 ) conducted a PDC–HS to assess inaccurate implementation of error correction procedures during teaching sessions, and results indicated that insufficient training was likely the greatest contributing factor for performance problems. The experimenters then compared an indicated intervention of BST with an intervention recommended in the task clarification and prompting domain (posting reminders; i.e., a nonindicated intervention) and found that performance improved only following the indicated intervention. In sum, the PDC–HS is particularly beneficial for supervisors in human service settings as it provides a systematic assessment of performance problems, is tailored specifically for use in human service settings, and helps supervisors select a function-indicated intervention.

Continuing Education for Staff

As employees continue their professional growth at an organization, their interests may begin to extend beyond the scope of what a supervisor is able to provide. These interests may be viewed as an opportunity to develop skills by facilitating additional learning opportunities. Many of the approaches described in the section below on staying up to date with research can also be adapted for staff development. For example, a supervisor may encourage staff to attend regional conferences or workshops by providing time off work or assisting with registration costs. Those who oversee a large number of staff may consider inviting speakers to deliver workshops on topics related to the services the organization provides. By facilitating continuing education opportunities, supervisors create varied learning opportunities for staff while also creating natural rewards for staff who stay with an organization.

Staying Up to Date in Performance Management Research

Staying current with the research literature is an important skill for practitioners as it may foster the provision of high-quality supervision, training, and services across all levels of the organization. Section 1.01 of the Professional and Ethical Compliance Code includes a provision that states “behavior analysts rely on professionally derived knowledge based on science and behavior analysis when making scientific or professional judgements in human service provision, or when engaging in scholarly or professional endeavors” (BACB, 2014 , p. 4). To meet this standard, credentialed behavior analysts must remain abreast of current scientific findings. At the broadest level, this often involves various classes of behavior that can be categorized into two areas: (a) attending professional development opportunities and (b) reading peer-reviewed publications in staff training and performance management.

Attending professional development opportunities often means attending local, regional, and/or international behavior-analytic conferences and workshops to learn about recent developments in a given area. With current technology, webinars, online-based trainings, and podcasts may be options. For example, the OBM Network ( http://obmnetwork.com ) provides numerous webinars from excellent researchers in the field of OBM on topics such as feedback, remote supervision, pay-for performance, leadership, and staff turnover, among others.

Carr and Briggs ( 2010 ) offer helpful recommendations for overcoming barriers to staying abreast of the scholarly literature. In addition, a means of remaining up to date on latest publications is to use software- and internet-based tools for alerts on recently published literature in a journal or content area. For example, many journal providers offer table-of-content alerts, which present the user with a brief snapshot of the articles published in the newest issue of a journal. Pubcrawler ( http://pubcrawler.gen.tcd.ie/ ) is an internet-based alert service that allows users to create personal queries for recently published articles, which are then compiled into a list and sent via email. A notable feature is that users can set their search criteria for the query using an extensive list of settings, including but not limited to commonly used components such as keywords and articles from particular journals. For example, if a user were interested in receiving updates for recent publications on staff training, the user could set up a search query by setting the search criteria for “staff training” as the keyword and a list of behavior-analytic journals as the places in which the query should search.

Given the expansive and ever-growing body of literature, it can be difficult to discern which literature is most relevant, in particular when many articles are accessible only through fees or university subscriptions. However, there are numerous methods to find articles that contain staff training or performance management content. One simple and straightforward way is to purchase access to behavior-analytic journals through the Association for Behavior Analysis International©, which can often be done at a discounted rate for members. Credentialed behavior analysts also have access to select journals through the online portal of the BACB. Another method is to use Google Scholar ( https://scholar.google.com ), where articles may be freely available. An additional benefit to using Google Scholar is that searches expand beyond the scope of just peer-reviewed articles, as their database also indexes books, conferences, and other nonpeer-reviewed materials. ResearchGate© ( https://www.researchgate.net ) is another tool for individuals to use to either download an article or reach out to the researcher directly. Finally, although many articles can be accessed using the methods described above, authors will typically be happy to send articles to those who reach out to them directly via email (often found on their university web page) or ResearchGate.

Recent research suggests that recommended staff training and performance management practices are not being regularly implemented in organizations that hire behavior analysts, which could affect the quality of services being provided. This article attempted to bridge the research-to-practice gap by outlining research-supported initial training and ongoing staff support procedures within human service settings, presenting practice guidelines, and sharing information about easy-to-implement ways practitioners may stay abreast of current research. Assessment and intervention procedures based on the science of behavior analysis have empirical support, but we must ensure they are being implemented with high integrity by a well-trained and supported workforce.

1 To our knowledge, the extant research has focused on effects of models of exemplar performance only; more research is needed on the effects of including models of nonexemplar performance on training outcomes.

Portions of this manuscript were presented as an invited talk by Florence D. DiGennaro Reed at the OBM in Health and Human Services Conference, Denver, CO.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Jaclyn K. Schwartz , Katherine Aylmer , Samara Green , Sami Tayeb , Timothy J. Wolf , Elizabeth Unni , Emily Somerville; Performance of Medication Tasks: Relationship Among Patient-Reported Outcomes, Performance-Based Assessments, and Objective Assessments. Am J Occup Ther May/June 2024, Vol. 78(3), 7803205060. doi: https://doi.org/10.5014/ajot.2024.050500

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Importance: Occupational therapy practitioners use standardized assessments to guide their clinical decision-making, but it is unclear how well performance on standardized assessments translates to performance at home.

Objective: To understand the concurrent and predictive validity of patient-reported outcomes and performance-based assessments for monitoring performance at home within the context of medication management and adherence.

Design: Exploratory study.

Setting: Participants completed standardized assessments in a lab or at home, which were followed by home-based electronic monitoring of medication adherence.

Participants: Sixty community-dwelling adults with hypertension or stroke who independently took antihypertensive medications.

Outcomes and Measures: Participants completed the Hill-Bone Medication Adherence Scale, the Hill-Bone Medication Adherence Reasons Scale, the Performance Assessment of Self-Care Skills Medication Management subtask, and the Executive Function Performance Test–Enhanced Medication Management subtest. Then, they used an electronic pill cap to monitor medication adherence at home for 1 month.

Results: Patient-reported outcomes and performance-based assessments in the context of medication management and adherence demonstrated poor concurrent and predictive validity to medication adherence at home.

Conclusions and Relevance: There is a gap between what people think they will do, what they can do on a standardized assessment, and what they actually do at home. Future research is needed to strengthen concurrent and predictive validity to clinically meaningful outcomes.

Plain-Language Summary: Occupational therapy practitioners should use caution when using standardized assessments to try to predict client performance at home. They should also continue to use a battery of assessments, clinical reasoning, and client preferences to guide their decision-making for monitoring performance at home within the context of medication management and adherence.

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Optimization of topology and energy management in fuel cell cruise ship hybrid power systems

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• Published: 17 May 2024
• Volume 2 , article number  12 , ( 2024 )

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• Lei Niu 1 , 2 &
• Li Xiao 3  

Current research on energy management strategies (EMSs) often neglects the impact of system topology and local control. This study tackles this issue by optimizing the topology of the hybrid power system on the ’FCS Alsterwasser’ cruise ship and enhancing EMS performance using various local controllers. First, the paper outlines the objectives of the research and provides an analysis of the current domestic and international research status. Second, the methods used in this study are introduced, including the topology optimization method and EMS. Subsequently, a model of the hybrid power system is constructed and verified through simulations. Finally, the effectiveness of different strategies is evaluated according to simulation results. Compared with an EMS based solely on a proportional-integral controller, the combination of a state machine and droop controller achieves better results, reducing battery power fluctuations by 86.5% and fuel cell power fluctuations by 16.2%.

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1 Introduction

1.1 motivation.

In the shipbuilding industry, fuel cells are considered promising clean alternative energy sources (van Biert et al. 2016 ). Proton exchange membrane fuel cells (PEMFCs) are preferred in the maritime industry because of their benefits, such as zero emissions, quick startup, high efficiency, high power density, and low noise (Ma et al. 2013 ). However, ship navigation conditions are complex, and load fluctuations are considerable (de-Troya et al. 2016 ). The application of fuel cells to various types of ships is much more intricate than to land equipment, mainly because fuel cells cannot rapidly suppress power fluctuations in a ship’s microgrid (Wu and Bucknall 2020 ). Therefore, energy storage systems (ESSs) are often used to complement fuel cell systems to address the synergy and complementarity among energy sources, ultimately enhancing the overall energy efficiency of vessels. ESSs can effectively smooth out power fluctuations in a ship’s load (Yang et al. 2020 ). Battery systems are typically used for energy storage in fuel cell power systems to enhance efficiency and power. These storage systems combine the high energy densities of batteries and high power densities of supercapacitors and can thus handle frequent charge-discharge cycles (Banaei et al. 2021 ). This capability enables them to mitigate low- and high-frequency power fluctuations, resulting in peak shaving and valley-filling effects and effectively reducing the impact of load fluctuations on a grid (Xing et al. 2021 ). A hybrid power system composed of fuel cells and ESSs can optimize the operation of fuel cells, improve their efficiency, extend their lifespan, enhance the dynamic response of a power system, and enable multisource complementary power generation (Dall’Armi et al. 2023 ).

Designing an efficient energy management strategy (EMS) that appropriately allocates the required power between a fuel cell system and ESS is challenging. An EMS controls the dynamic behavior of components in a hybrid power system, thereby affecting system efficiency, fuel consumption, and lifespan (Sun et al. 2013 ). Therefore, developing a suitable EMS for hybrid fuel cell power systems has always been an essential research topic (Sulaiman et al. 2018 ). However, existing research on EMSs for hybrid fuel cell power systems has mostly focused on EMS performance, overlooking the impact of local control on energy management performance (Liu et al. 2024 ). Nevertheless, some researchers have achieved favorable research results by using topology optimization or capacity optimization design. Given the shortcomings of existing research, this study aims to explore topology optimization and energy management in the hybrid power system of the ’FCS Alsterwasser’ cruise ship. It will investigate the impact of topology and local control on EMSs and further enhance the performance of EMSs.

1.2 Literature review

Various advanced ship EMSs have been proposed and examined owing to challenges in enhancing hybrid power systems’ performance, including dynamic programming (DP; Zhang 2019 ), Pontryagin’s minimum principle (PMP; Schmid et al. 2021 ), equivalent consumption minimization strategy (ECMS; Ge et al. 2023 ), machine learning algorithms, and model predictive control (Ghorashi Khalil Abadi et al. 2022 ). The DP algorithm, as a classic multistage decision optimization method, optimizes the operation cost of ship power systems. However, this strategy is difficult to apply to practical energy management because of uncertainties about ship navigation conditions. DP requires accurate global operational conditions. PMP is partially applicable to hybrid electric vehicles, but research into hybrid power ships is limited. The principle of this strategy is to find an optimal solution by calculating the Hamiltonian function at each moment. DP and PMP are usually conducted offline and often used as benchmarks. Meanwhile, the ECMS optimizes all energy sources in real time by adjusting factors representing equivalent fuel consumption costs and is widely used for real-time power distribution optimization in hybrid power systems. However, this strategy heavily relies on equivalent factors. Thus, determining optimal values is difficult, and the method has limited performance. Energy management strategies based on machine learning algorithms have potential but are hampered by the ’black box’ issue (Fan et al. 2023 ), which renders their direct application to actual ships difficult. To further enhance the performance of hybrid power systems, innovative and effective approaches that address current strategy dependencies and uncertainties are needed.

A hybrid fuel cell propulsion system, as a typical form of ship hybrid power system, has many potential applications, thus garnering considerable interest from the shipbuilding sector. The system has already been applied and researched, but studies on hybrid fuel cell propulsion systems have mainly focused on the hybrid power system of the ’FCS Alsterwasser’ ship to develop new EMSs for conserving energy and reducing emissions. Han et al. ( 2014 ) proposed a state machine-based energy management system for the hybrid power system of the ’FCS Alsterwasser’ ship; the proposed strategy was designed on the basis of the optimal efficiency of the fuel cell (FC) and batteries to ensure that both energy sources operate in the high-efficiency range. Bassam et al. ( 2016 ) proposed a novel energy management strategy that uses fuel cell efficiency as input to maintain high fuel cell efficiency and reduce pressure and thereby reduce fuel consumption; compared with a state-based ECMS strategy and the original proportional-integral (PI) strategy, the proposed PI strategy achieved daily hydrogen savings of 3.5%, 1.7%, and 1.4% while reducing fuel cell stress. Sun et al. ( 2020 ) considered the aging cost of fuel cells and developed a unified optimization model to minimize the total cost of fuel consumption and power source aging over the entire voyage and to optimize the output power of multiple fuel cells and batteries, as well as propulsion power. Tang and Wang ( 2021 ) proposed an EMS based on wavelet transformation and fuzzy logic for a fuel cell/battery/supercapacitor hybrid power cruiser, considering the dynamic characteristics of each power source; the simulation results showed that the proposed EMS enabled the fuel cell to provide approximately 50% of high-frequency power and reduced peak power from the fuel cell by 80% when the initial charge level of the supercapacitor was low. Rafiei et al. ( 2021 ) presented and analyzed a zero-emission all-electric hybrid energy system based on fuel cells, batteries, and shore power, using an improved sin-cosine algorithm to optimize power scheduling; the proposed hybrid power system and energy management method demonstrated high performance as an applicable approach for ships. Wu et al. ( 2020 ) introduced an EMS based on dual Q reinforcement learning; their results indicated that the strategy achieved nearly optimal cost-effectiveness compared with DP and comparable state space resolution without prior knowledge of future power demand. However, although these studies have conducted advanced research on energy management strategies, they have overlooked the impact of local control on hybrid power systems (Zeng et al. 2023 ). Owing to the multiple aspects of energy management in hybrid power systems, it can include an energy management layer and a local control layer according to the hierarchical control architecture. The energy management layer is primarily responsible for optimizing power distribution and decision-making in hybrid power systems (Haseltalab et al. 2016 ), whereas the local control layer is responsible for executing the structure determined by the energy management layer. The two layers are interdependent and cannot be discussed separately. Therefore, the local control layer should be investigated in order that the impact of different local control layers on hybrid power systems and energy management strategies can be explored.

Existing research primarily utilizes a classic proportional-integral (PI) controller for fuel cells because of the direct parallel connection of a ship’s batteries to a DC bus. The control principle relies on open-loop control based on the reference power of a fuel cell and the state of charge (SOC) of batteries, which provide passive energy. This feature leads to challenges in the optimization of fuel cells and battery power. Some studies have explored strategies for optimizing the architecture and capacity configurations of hybrid power systems. Zhang et al. ( 2020 ) proposed a selection method for the hybrid ESS of a fuel cell hybrid propulsion cruise ferry to extend the lifespan of fuel cells; based on the configuration of the power system, a real-time optimization control strategy that balances efficiency and durability was proposed; the simulation results showed that the strategy outperformed rule-based strategies in terms of fuel economy, system durability, and dynamic performance. Zhu et al. ( 2020 ) proposed a multi-objective dual-layer optimization approach, where component sizing adjustments and energy management were simultaneously conducted in the upper and lower layers, respectively; the results of the proposed dual-layer optimization were compared with the results of two independent single-layer optimization strategies; the optimal solution of the proposed method outperformed single-layer optimization, and the results of single lower-layer optimization were closer to the dual-layer optimization results than single upper-layer optimization results (Zhu et al. 2020 ).

However, not only the selection of energy equipment but also the topology structures of different energy sources affect the selection of energy equipment and the performance of hybrid power systems. Chen et al. ( 2020 ) introduced a multi-objective optimization method for HESS and EMS based on a support vector machine and frequency control; the simulation results indicated that compared with different hybrid power system structures, the optimal HESS can meet power demands and reduce the cost of energy storage devices. Compared with rule-based energy management strategies, the optimal hybrid power system showed a 5.4% decrease in energy consumption, improving the quality of electrical energy and extending equipment lifespan (Chen et al. 2020 ). Ge et al. ( 2023 ) optimized the topology structure of a ship’s hybrid fuel cell power system; in addition, they proposed a hybrid power system combining fuel cells, batteries, and supercapacitors and utilized a fuzzy logic-based EMS to improve the performance of the hybrid power system; they suggested the potential of the capacity and topology structure of the ship’s hybrid power system for further optimization. Overall, these studies have optimized and compared the topology structures of hybrid power systems, studying the performance of hybrid power systems under different topology structures and demonstrating the impact of topology structure optimization on the performance of hybrid power systems. Therefore, studying the influence of topology structure on hybrid power systems is necessary.

The purpose of this research is to enhance the existing topology structure of a fuel cell/battery hybrid power ship, investigate the combined effects of different energy management strategies and local controllers, and improve the performance of the EMS. This study will compare the performance of energy management strategies on the basis of PI-based local controllers and droop controllers. It will compare these strategies with an EMS based on the original PI controller, state machine-based EMS, and fuzzy logic-based EMS according to the energy quality of batteries and fuel cells and SOC of batteries.

1.3 Outline

The remaining sections of this study are organized as follows. Section  2 introduces topology structure optimization, EMS, and local controllers. Section  3 focuses on the information on the hybrid power system of the ’FCS Alsterwasser’ ship, including the modeling, simulation process, setup, and construction of the hybrid power system, EMS, and local controller models. Section  4 presents and discusses the simulation results. Section  5 concludes the paper and provides future research directions.

2 Methodology

2.1 topology optimization.

The ship’s original hybrid power system directly connected the battery to the 560 V DC bus as an ESS (Fig.  1 ). However, owing to frequent fluctuations in the ship’s load, the traditional PI-based EMS ensured stability by only controlling the fuel cell system’s power, and the battery had to bear not only partial low-frequency loads but also the main high-frequency load output. Thus, optimizing the hybrid power system and stabilizing the bus voltage were difficult.

Original hybrid power system topology of the ’FCS Alsterwasser’ ship

Given the fluctuations in shipload, the economy and equipment lifespan of the hybrid power system can be enhanced by improving the controllability of the hybrid power system. This paper proposes a scheme for improving topology, local control, and EMS to achieve the efficient operation of the hybrid power system. The modification process primarily involves connecting the battery to the DC bus through bidirectional DC/DC converters to enhance the controllability of the batteries. The improved topology of the hybrid fuel cell power system is illustrated in Fig.  2 .

Modified hybrid power system topology of the ’FCS Alsterwasser’ ship

With the aforementioned modifications, the batteries can be controlled through external control signals for voltage or current closed-loop control, which can enhance the controllability of the batteries. Therefore, voltage or current closed-loop controllers can be employed for the batteries and fuel cells, enabling reference power tracking and assisting the EMS in distributing power to the hybrid power system.

2.2 Energy management strategies

2.2.1 classic pi ems.

Early EMS based on classic PI and PID controllers have been proposed, featuring a simple and easy-to-implement control structure. The control principles are illustrated in Fig.  3 . In this study, the P gain was set to 200, and the I gain was set to 1.

Control principles of classic PI EMS

The current SOC of the battery and its reference SOC are compared, and a PI controller is employed to derive the battery’s reference power, which is then subtracted from the load power, yielding the computed reference power for the fuel cell. Subsequently, by dividing the reference power of the battery and fuel cell by the bus voltage, the theoretical current output for the fuel cell and battery is determined. This output, in turn, facilitates closed-loop control through current feedback. The primary objective of the PI-based EMS is to maintain the battery’s SOC at its designated level to alleviate stress on the battery and extend its operational lifespan. However, this control methodology has limitations. When the battery’s SOC falls below the reference value, the fuel cell operates according to the required load power or at maximum power. This feature can adversely affect the efficiency, hydrogen consumption rate, and longevity of the fuel cell.

2.2.2 State machine-based strategy

The state machine-based EMS is based on deterministic rules and adjusts the operation of the hybrid power system under varying loads through predefined control rules. The principles of the state machine-based energy management control strategy can be found in Fig.  4 , and the configuration of its principles is shown in Table  1 .

Principles of state machine-based EMS control

For hybrid fuel cell power systems, a state machine-based control strategy is typically devised on the basis of the desired power and battery SOC, and the operational constraints of the hybrid power system are considered. In this study, the maximum value for battery SOC (SOC max ) is set at 85%, while the minimum value (SOC min ) is 10%. Refining control rules is an effective approach for enhancing the performance of a state machine-based control strategy. However, an excessive number of rules can lead to frequent control changes, resulting in the unstable operation of the hybrid power system and increasing susceptibility to the influence of sudden load variations.

2.2.3 Fuzzy logic control strategy

In this study, the fuzzy logic controller has two input variables, namely, the battery’s SOC bat and power demand P demand , and one output variable, which is the required power for the fuel cell ( P FC ). The fuzzy controller employs IF-Then rules to establish a map between inputs and outputs. The control principles are illustrated in Fig.  5 .

Principles of fuzzy logic-based EMS control

This study utilized a fuzzy controller with 12 rules (Motapon et al. 2014 ). The details are provided in Table  2 .

The fuzzy controller uses trapezoidal membership functions for input and output selections (Fig.  6 ).

Fuzzy logic control membership functions

2.3 Local controller

2.3.1 pi controller.

The classic PI controller as a local controller has been integrated into energy management strategies. However, the classic PI control method is mainly based on obtaining reference current from the ratio of reference power to the bus voltage and achieves power distribution and control through current closed-loop control. The classic PI control method primarily collects current signals for closed-loop control without introducing reference voltage, leading to large bus voltage fluctuations. It is suitable for use in a semiactive topology, where energy storage devices are directly connected in parallel to the bus in a microgrid structure.

The microgrid structure of FCS Alsterwasser adopts a semiactive structure, where the fuel cell needs to be controlled through DC/DC boost and control without the need to control the battery, which is a type of PI controller. The PI controller cannot achieve simultaneous control of the fuel cell and battery.

2.3.2 Droop controller

Droop control mainly consists of two types: voltage-power droop control, which describes the voltage-power relationship, and voltage-current (V-I) droop control, which describes the voltage-current relationship. In this study, the V-I droop control is employed to achieve power control based on droop characteristics among parallel distributed power sources. In DC microgrids, the droop characteristic curve reflects the relationship between the DC voltage and DC current of the power sources. In fuel cells, which can only discharge, the droop curve exists only in the first quadrant. In batteries that can charge and discharge, the droop curve typically exhibits characteristics in two quadrants, as illustrated in Fig.  7 .

Droop control principle

However, traditional droop controllers mainly use fixed droop coefficients, which renders tracking nonlinear reference power obtained from the EMS difficult. Therefore, these controllers cannot be directly applied to this study. This study intends to propose a droop controller based on dynamic virtual impedance as a local controller and compare its performance with a local controller based on the classic PI controller. According to the principle of traditional droop control, the power of an energy source is inversely proportional to the droop coefficient; that is, the droop coefficient decreases with increasing rated power. Depending on the operating state of different energy sources, the droop coefficient can be obtained according to the load power and the power of each energy source. The formula for calculating the droop coefficient is summarized in Eq. ( 1 ).

where \(k_{d}\) is the n- th distributed power source, \(p_{n}\) is the expected power of the n- th distributed power source, \(k_{adj}\) is the correction factor, and in the study, and \(k_{adj}\)  = 0.1. On the right-hand side of Eq. ( 1 ), the denominator is the load power, and the numerator is the load power minus the reference power of the energy source. p total refers to the total demand power, p bat represents the battery power.

3 Modeling and simulation implementation

3.1 ’fcs alsterwasser’ overview.

This article focuses on the world’s first fuel-cell cruise ship, the ’FCS Alsterwasser’. Owing to the widespread availability of its key technical parameters and navigation data, it has been widely used as a subject of study in maritime energy management research. Comprehensive information about this ship can be found in previous studies (Zhu et al. 2014 ; Choi et al. 2016 ). The primary parameters of the ship can be found in Table  3 .

The ship’s hybrid power system consists of a PEMFC and a set of lead-acid batteries, primarily relying on the fuel cell during cruising. During high-load operations, it uses a battery to reduce the output power of the fuel cell and extend its lifespan. The battery mainly serves a ’peak shaving’ function to stabilize the bus voltage. The primary parameters of the ’FCS Alsterwasser’ ship’s hybrid power system can be found in Table  4 .

3.2 Hybrid power system model

3.2.1 fuel cell.

The ’FCS Alsterwasser’ employs a PEMFC, which is a type of fuel cell with a well-established model that is widely studied and applied. As shown in Fig.  8 a, this study utilizes the fuel cell module provided by Matlab/Simulink for modeling purposes, configuring it as a detailed fuel cell model and defining the fuel cell parameters to simulate the fuel cell system. This model is then integrated into the hybrid power system. Detailed information about this module is provided in the documentation of Simulink and the associated reference literature.

FC model. a FC module; b FC equivalent circuit

The stack consists of several series-connected fuel cells. The equivalent circuit for a single fuel cell used in this module is provided in Fig.  8 b. The primary parameters for this model can be obtained from the fuel cell’s parameter table (Table  4 ). Considering the response time of the fuel cell, this model can represent the steady-state performance and dynamic behavior of the PEMFC. Additionally, the model considers the characteristics of the electrical and chemical aspects of the FC.

3.2.2 Battery

In this study, the primary focus is researching EMS performance, and the intricate characteristics of the battery are not considered. Constructing a battery model with dynamic properties is sufficient. Therefore, the battery model in Matlab/Simulink is utilized (Fig.  9 ). The model is configured according to the battery’s parameter information (Table  4 ).

Battery model

The voltage source of this battery model is defined as follows:

where V nom is the rated voltage and beta is a coefficient that can be adjusted to simulate battery characteristics.

3.2.3 DC/DC converter

The voltage of the DC/DC converter component in the hybrid power system varies according to the current requirements of each power source. Therefore, an electronic circuit is needed to stabilize the power supply voltage while providing the required power. Given that this study does examine the dynamic behavior inside the DC/DC converter, an ideal bidirectional DC/DC converter module from Matlab/Simulink is used to regulate the output voltage of the PEMFC or battery, as shown in Fig.  10 .

DC/DC converter model

The ideal DC/DC model can simulate the dynamic behavior of the DC/DC converter and can implement current or voltage closed-loop control through external signals. In this study, the focus is on investigating the impact of different local control strategies on the EMS. Therefore, the DC/DC model facilitates the design of local controllers and EMS simulation studies.

3.2.4 Ship load

To simulate the typical ship conditions, this study utilizes the dynamic load module available in Matlab/Simulink (Fig.  11 ).

Dynamic load model

In this study, this module is configured as a DC load. The power consumption of this module will be equal to the input demand power signal if the power consumption of the module is greater than the minimum power consumption parameter value and the DC power source voltage exceeds the specified value of the minimum power source voltage parameter.

3.3 Navigational conditions

The data from a single navigational condition of the ’FCS Alsterwasser’ has been established as a typical condition in ship energy management research and has been widely used in testing various types of EMSs (Peng et al. 2023 ). This segment of navigational condition data can be found in Fig.  12 .

Navigational condition of the ’FCS Alsterwasser’ ship

The primary characteristics of this navigational condition data are as follows: (a) peak propulsion power is approximately 112 kW; (b) acceleration time is approximately 32 s (163–195 s); (c) cruise power is approximately 40 kW; (d) excluding auxiliary power during the cycle, the average power demand is approximately 41 kW. This power demand includes propulsion and auxiliary power and covers power requirements during various phases of ship operation, including sailing, docking, stopping, and acceleration, serving as a typical navigational condition for ships. The relatively short duration of this data segment hampers the comprehensive evaluation of the strategy’s performance. Thus, this study plans to test and evaluate the proposed method by continuously cycling this condition 10 times.

3.4 Simulation implementation

Based on the modeling described above, the hybrid power system model for the ’FCS Alsterwasser’ ship and the EMS model are obtained, as shown in Fig.  13 . The voltage, current, and power data for the battery, fuel cell, and load can be obtained through the sensor module. Through their interaction, the performance of the EMS can be evaluated.

Hybrid power system and EMS model

4 Results and discussion

4.1 simulation result.

This study has validated the proposed topological optimization and the effectiveness of the EMS through software simulations. Figures  14 and 15 , respectively, depict the current profiles of the battery and fuel cell, while Fig.  16 shows the SOC of the battery. The simulation results in the figures for the PI controller are based on the original topology, whereas the results for the droop controller are based on the improved topology.

Battery power

SOC of the battery

Based on Figs. 14 , 15 and 16 , the following observations can be analyzed:

Under the same EMS, different results are obtained when the PI controller or droop controller as the local controller is used. For example, when the PI controller is used, the direct control of the FC’s output power causes large fluctuations in the FC power because of repeated changes in the reference power output based on the fuzzy-based EMS. By contrast, the droop controller simultaneously controls the battery and the fuel cell, resulting in the suppression of fuel cell power fluctuations.

According to Fig.  14 , in the PI-based EMS, the battery is in a state of discharging before the 2000 s, during which the battery bears the entire load, and the fuel cell does not work. After the 2000 s, the battery SOC is maintained at approximately 60%, at which the fuel cell bears most of the power, and the battery frequently switches between charging and discharging as the load changes. The strategy based on the PI-based EMS evidently does not rationally allocate power between the battery and fuel cell, leading to large fluctuations in the battery and affecting its lifespan.

The principle of the state machine-based EMS is to determine the reference power for the battery and the fuel cell according to the magnitude of power. The designed scenarios include a relatively stable 41 kW load, repeated pulse loads, FC bearing all the power under steady loads, and batteries only serving as supplements under pulse loads. The reason is that the state machine-based EMS outputs reference power on the basis of predetermined rules, and the wide range of designed scenarios in this study makes balancing the output of the battery and fuel cell with this strategy difficult. Thus, the battery is not working during the steady demand phase.

4.2 Power quality analysis

Based on simulation data, the analysis of the power results for the battery and fuel cell under different strategies, including their mean and standard deviation, is presented in Tables 5 and 6 .

According to Tables 5 and 6 , the following results can be analyzed:

Topological optimization improves the controllability of the battery and enhances the stability of the hybrid power system. When relying solely on the PI controller, the battery power experiences large fluctuations because the battery is directly connected to the bus. This connection results in passive energy supply and large power fluctuations. Nevertheless, adding a DC/DC converter considerably reduces these power fluctuations. In particular, the EMS based on the state machine and PI reduces battery power fluctuations by 94.6%.

As observed in Fig.  16 , the traditional PI controller stabilizes the SOC once it reaches the desired SOC value, at which the battery output power remains nearly zero, and the battery handles most of the load power. The state machine-based EMS primarily maintains the SOC at approximately 65%, while the fuzzy logic control allows the battery to fully discharge.

Performance varies when different local control strategies are integrated into the EMS. Energy management based on the state machine and PI effectively suppresses battery power fluctuations but is limited by the technical challenge posed by the fuel cell that handles most high-frequency fluctuations. This limitation is detrimental to the fuel cell’s lifespan and efficiency.

The results indicate that the EMS based on the combination of the state machine and droop control achieves balanced outcomes. This strategy maintains a high average output power for the fuel cell and minimizes power fluctuations, allowing the battery to handle the majority of high-frequency loads. This aligns with the predefined optimization goals. Notably, the battery power fluctuations decrease by 86.5%, and the fuel cell power fluctuations decrease by 16.2%.

The combination of fuzzy logic control and PI represents a relatively balanced control strategy. Compared with the combination of fuzzy logic control and droop control, the power fluctuations of the battery and fuel cell are enhanced because the fuzzy logic control continuously adjusts the reference power output, leading to frequent adjustments in the droop coefficients in the droop controller and intensifying the fluctuations.

5 Conclusions

Topological optimization improves the stability of the hybrid power system and enhances the controllability of the battery. When the PI controller alone is used, large power fluctuations occur because of the direct connection to the bus, leading to passive energy supply. However, integrating a DC/DC converter into the battery can greatly reduce power fluctuations, and the combination of the state machine-based EMS and PI reduces battery power fluctuations by 94.6%. Different local control strategies coupled with EMS lead to varying performance, and the combination of the state machine and droop control achieves balanced outcomes by minimizing power fluctuations in the battery and fuel cell. The combination of fuzzy logic control and PI represents a relatively balanced control strategy, while the combination of fuzzy logic control and droop control intensifies power fluctuations because of frequent adjustments.

This study primarily focuses on optimizing the topology and EMS of a fuel cell hybrid power system. By improving the topology and devising suitable energy management and local control strategies, the EMS based on the state machine and droop control achieves the most balanced results, demonstrating its suitability for hybrid fuel cell power systems. However, this research has some limitations.

The DC/DC converter used in this study employs an average value model, which cannot capture the current or voltage closed-loop control implemented based on PI or droop controllers. Thus, results are directly based on reference current or voltage, and the dynamic characteristics of the DC/DC converter are not considered.

This study solely focuses on the modification of the DC/DC converter while neglecting the optimization and modification of the capacities of the battery and fuel cell. It overlooks additional economic costs associated with these modifications, and thus, the simulation results are limited. A comprehensive evaluation of strategies should consider various factors to provide a holistic perspective.

This study conducts testing and analysis solely through software simulations without incorporating real-world testing and validation. Hardware-in-the-loop simulations are needed to validate the proposed topological optimization strategy and EMS in a real-world context.

Availability of data and materials

All data, models, and code generated or used during the study appear in the submitted article.

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Acknowledgements

This paper is supported by the 2020 Hubei Provincial Department of Education Science Research Program Guidance Project (Grant No. B2020252).

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Edited by: Wenwen Chen.

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Guanghua School of Management, Peking University, Beijing, 100871, China

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Lei Niu: Conceptualization, Manuscript writing, Implementation of the computer code; Li Xiao: Methodology, Writing-Review & Editing, and Language polishing.

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Niu, L., Xiao, L. Optimization of topology and energy management in fuel cell cruise ship hybrid power systems. Intell. Mar. Technol. Syst. 2 , 12 (2024). https://doi.org/10.1007/s44295-024-00026-3

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Received : 22 January 2024

Revised : 12 March 2024

Accepted : 12 April 2024

Published : 17 May 2024

DOI : https://doi.org/10.1007/s44295-024-00026-3

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