Leadership styles and models in education are not one-size-fits-all. Different situations and contexts require different approaches and skills. As a leader in education, you need to be able to leverage data and evidence to inform your decisions and actions. How do you do that? Here are some tips and examples to help you.
Data-driven leadership is the practice of using data and evidence to guide your goals, strategies, and actions as a leader. Data can help you identify problems, monitor progress, evaluate outcomes, and improve practices. However, it is not enough to simply collect data; you must also interpret, communicate, and act on it in meaningful and ethical ways. For instance, data can be used to align your vision and mission with the needs and expectations of your stakeholders, set SMART goals and indicators, implement and monitor evidence-based interventions and programs, assess and improve your own and your team's performance and development, and share and celebrate successes while learning from challenges.
Leadership styles and models in education vary, but some of the most common ones are transformational, instructional, distributed, and servant leadership. Transformational leadership focuses on inspiring and motivating others to achieve a shared vision and create positive change. Instructional leadership emphasizes the improvement of teaching and learning, while distributed leadership recognizes that leadership is shared among multiple actors and levels. Servant leadership is based on the idea that leaders are first and foremost servants of others. All of these styles have their own unique characteristics, such as fostering a culture of trust, setting high standards and expectations, empowering and involving others in decision-making, and demonstrating humility, empathy, and integrity.
There are a wide-variety of “leadership styles” out there. The reality is that you must understand who you are as a leader - period. Don’t feel the need to attach a specific type to it. Trying to label yourself as a leader can lead you into a state of using that “type” as a crutch. Focus on developing who you are as a leader, while practicing vulnerability. Be open to knowing and getting curious about your blind spots as much as you do your strengths. Get to understand how your preferred decision-making models can positively AND negatively impact your ability to lead. This is critical to ensure that you strive to generate sustainable results, while empowering yourself to put safeguards in place to keep you from derailing too often.
As a leader in education, you have access to various sources of data and evidence that can inform your leadership decisions and actions. Student data, such as achievement, attendance, behavior, engagement, feedback, and well-being, can be used to monitor and improve student outcomes, identify and address gaps and disparities, and tailor support and interventions. Teacher data, such as performance, satisfaction, feedback, and development, can be used to evaluate and enhance teacher quality, provide recognition and reward, and foster professional growth and collaboration. School data, such as climate, culture, resources, processes, and results, can be used to assess and improve school effectiveness, efficiency, and equity, and to align practices and policies with your vision and mission. External data, such as research, benchmarks, standards, and best practices, can be used to compare and contrast your performance and practices with others, and to learn from and adopt proven and innovative strategies and solutions.
Using data and evidence to inform your leadership decisions and actions can be challenging. Data quality, data literacy, and data culture are all important factors to consider. Data quality refers to the accuracy, validity, reliability, and timeliness of the data collected and used. Poor data quality can lead to misleading or erroneous conclusions and actions, so it is important to use appropriate and consistent methods and tools, and to check and verify data sources and results. Data literacy is the ability to understand, analyze, and communicate data and evidence. Low data literacy can limit your capacity to use data and evidence effectively and ethically, so it is important to develop and enhance skills and knowledge, and to seek and provide support and training. Data culture is the attitudes, beliefs, and behaviors that shape how data and evidence are valued and used in an organization. A negative or weak data culture can hinder data-driven leadership efforts and outcomes, so it is important to foster a shared vision and commitment, and to promote a culture of trust, collaboration, and learning.
To maximize the benefits of using data and evidence to inform your leadership decisions and actions, it is important to start with a clear purpose and question. Additionally, you should use multiple and diverse data and evidence sources to get a comprehensive and balanced picture of your situation and context. Involving and engaging others in data and evidence processes is also essential to increase the relevance and impact of your data and evidence. Lastly, it is important to reflect and act on data and evidence, analyze and interpret them, and use them to inform your decisions and actions. Furthermore, you should monitor and evaluate the effects and outcomes of your decisions and actions to inform your next steps and improvements.
While I understand, appreciate and value QUANTIATIVE data, as a "recovering academic" and practicing social scientist, I also value QUALITATIVE data. Behind every NUMBER, there is a STORY. As a leader, I can learn so much from the stories. Stories give us rich data and insight into the lived experience of those around us. This is extremely valuable when those around us bring DIVERSE perspectives.
While I recognize the focus of this article is on data and evidence, we can’t overlook the importance of spending time in conversation with the target audience and those led by that target audience. Like many of the risks associated with AI, when we assume our data sources are giving us the complete narrative we often fail to truly understand what’s happening. While the data can serve as a powerful way to prioritize where to look and what questions to ask, we need to ensure we’re taking time to do the followup work, plumb the depths of complexity and context, and deeply understand what’s happening.