Designing for role clarity: An essential leadership skill

By Gemma Jiang and Joan Lurie.

How can leaders design roles and role relations within their project teams? How can leaders recalibrate and re-align role relations as their project contexts shift? Why is designing for role clarity an essential leadership skill, beyond technical and interpersonal skills?

Just as we sign contracts outlining job descriptions and authority when starting a new position, a similar role contracting process should be initiated at the beginning of each project. This ensures that everyone understands their specific responsibilities and authority within the project context. This practice is particularly crucial when team members have overlapping roles outside the project. For instance, in one project, a faculty member might lead while their department chair takes on a supporting role. How should these two define their project roles to distinguish them from their ongoing department chair–faculty relationship?

Most teams start their role conversation with the RACI framework, which defines four essential roles: Responsible, Accountable, Consulted, and Informed (Miranda and Watts, 2024). In RACI, the accountable role holds ultimate responsibility for the project’s success or failure, responsible roles execute project tasks, consulted roles provide relevant input or expertise, and informed roles are kept updated but not directly involved. While RACI provides a strong foundation, more nuanced conversations around role dynamics are needed. One of us (Joan Lurie) has developed the Orgonomics methodology to address this need, which we describe here with its applications in cross-disciplinary teams.

1. Define Individual Roles at the Beginning
   The role contracting conversation should begin with the accountable person—the project leader—who is accountable for the project’s success. Without a clearly defined accountable person and role clarity, projects often default to positional leaders in the larger center, institute, or department, leading to decision-making gaps and disempowerment on both sides.
   For example, in a science institute using machine learning to interpret biological images, one project might focus on butterfly images, with a junior scientist leading the effort, even if they are not a principal investigator. As the person accountable for the success of this specific project, this junior scientist must have a conversation with the principal investigators to clarify role expectations before the project begins. Key questions to address include: What decision-making authority does the project lead have? How is the lead expected to report to the principal investigators to whom they are accountable? What are the agreed-upon deliverables, within what timeframe?
   The conversation should then extend to those responsible for various tasks: What are the specific roles? Who is fulfilling each role? What are the expectations? Once the team is established, with accountable and responsible members, they must collaboratively define how these roles interact and relate to one another, as discussed in the next point.
2. Contract for Role Relations
   Role clarity encompasses not only individual tasks and responsibilities but also the relationships between roles within the project team. Without it, significant roles may be overlooked, overlapping roles can lead to resource waste, or roles may be set up to work at cross purposes. Effective teamwork requires coherent and well-defined systems of role relations on the team.
   Take a climate resilience project for example. Each team member has a distinct role: ecologists collect biodiversity data, data scientists analyze climate models, and social scientists assess community adaptation. Without clear role definitions and understanding role relations among the three groups, however, the team risks inefficiencies or conflicts. For instance, if ecologists and data scientists both handle data integration, they may duplicate work or use inconsistent methods, wasting time and resources.
3. Agree Rules of Engagement for Relational In-Betweenness
   Role clarity has a dynamic interactive aspect, focusing on how work happens between roles. This can be accomplished through rules of engagement, which spotlight the actual interactive dynamics between roles.
   For example, what is the rule of engagement with those in “consulted” roles who will provide input as needed? We’ve observed many meetings intended for responsible roles where consulted roles are also required to attend. This not only leads to ineffective and bloated meetings for the responsible but can also cause frustration for the consulted because their time is not utilized effectively.
   Establishing clear rules of engagement is essential and could include time and inclusion expectations, the process for integrating feedback, decision-making authorities and sharing of information.
4. Maintain Agility through Role Re-Contracting
   As the project evolves, project teams need to regularly recalibrate and recontract roles and rules of engagement to adapt to shifting contexts. This ongoing role recalibration is crucial for maintaining agility within the team. Re-contracting is especially important at key inflection points in the project, during personnel changes, or whenever there is confusion emerging about roles.
5. Embed Rituals of Systemic Sense-Making
   In cross-disciplinary collaboration, tacit knowledge—like an engineer’s understanding of technical limitations or a biologist’s intuition about data—often remains unintentionally unspoken. These ‘uncommunicated insights’ can lead to assumptions about what needs to be shared, potentially causing conflicts.
   To prevent this, it’s crucial to make tacit knowledge explicit by embedding rituals that enhance systemic sense-making capacity. For example, teams can hold regular “balcony conversations” to check in on how the systems of role relations are working. For another example, teams can also hold periodic retrospective conversations to examine whether the rules of engagement are serving them as their work unfolds. These rituals and practices can be cultivated into good team science practices, helping leaders and organizations navigate key inflection points and maintain coherence as projects evolve.

Conclusion

Leadership in cross-disciplinary science teams requires the ability to design, clarify, contract, and recalibrate role relationships throughout a project. The goal is for every team member to have role clarity as the project evolves, ensuring the team functions as a cohesive whole, greater than the sum of its parts.

What have your experiences been with establishing role clarity in cross-disciplinary teams? Do you have additional suggestions or processes? Do you see designing for role clarity as an essential leadership skill?

Reference:

Miranda, D. and Watts, R. (2024). What is a RACI chart? How this project management tool can boost your productivity. Forbes Advisor, updated article. (Online): https://www.forbes.com/advisor/business/raci-chart/

Use of Generative Artificial Intelligence (AI) Statement: Generative artificial intelligence was not used in the development of this i2Insights contribution. (For i2Insights policy on generative artificial intelligence please see https://i2insights.org/contributing-to-i2insights/guidelines-for-authors/#artificial-intelligence.)

Biography: Gemma Jiang PhD is senior team scientist at the Institute for Research in the Social Sciences (IRISS) of Colorado State University in Fort Collins, Colorado, USA. She applies complexity leadership theory, social network analysis, and a suite of facilitation and coaching methods to enable cross-disciplinary science teams to converge upon solutions for challenges of societal importance.

Biography: Joan Lurie MA is the Chief Executive Officer and Founder of Orgonomics, which is both a business and a methodology, that she created with the purpose of developing leaders and organizations to be fit for and navigate complex landscapes. She works as a consultant and coach to enable leaders, teams and organizations to continuously adapt, perform, thrive and grow as interdependent ecosystems and learning networks.

Funding Acknowledgement:

This i2Insights contribution was supported, in part, by the National Center for Advancing Translational Sciences of the National Institutes of Health under Grant Number UM1TR004548. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.