Data-Driven Decisions

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Data-Driven Decisions

Data-Driven Decisions

The institution aims to make decisions based on actual data rather than intuitions alone. In the absence of data, bias and false assumptions, among other issues, cloud judgment, leading to poor decision making. In higher education, governments and regulating agencies encourage institutions to support their decisions with factual data. Often, decisions are based on change initiatives that must b informed by data. Several assessment tools and approaches are used to collect qualitative and quantitative data to generate change ideas, support systems and strategies used to communicate and initiate change, and the change management process. Assessment tools provide data that supports decisions made in institutions of higher learning. This paper investigates the use of data in making decisions and the approach used to communicate change.

Data-Based Strategies to Communicate Change

Data-driven change management approaches to ensure an initiative delivers what it was intended to do. Ne of the most common strategies of driving change is by motivating employees to want change. Ultimately, this approach involves inspiring employees to propel change by themselves. To drive change using data, a quick survey can be done to establish to what extent employees are motivated and determine how engaged they are with the new initiative. In my case study, the College of St. Catherine, there was a change in leadership and management restructuring in various departments. An incentivized strategy would have been appropriate to communicate the rationale of these changes to all stakeholders. The new president could have sent an email to introduce herself and provide a brief description of how she intends to make the College a market leader in the region. Besides, an anonymous survey would have informed how the students and other key personnel perceived the departmental changes. The survey would have also provided a good opportunity for soliciting feedback, perhaps by asking respondents to give their opinions and feelings.

Regarding the re-design of the curriculum and revision of the college programs, stakeholders need to feel involved in the process. When people think they have a choice and their input is desired, then change becomes easy. The College’s management can provide access to curriculum training to relevant employees or even allow them to take up roles in the change process. Creating a culture of continuous improvement and professional development inspires employees to keep an open mind (Winkler & Fyffe, 2016), making the introduction of a suitable change initiative acceptable. In addition to surveys, behavioral observation can help evaluate the level of acceptance to change. For instance, tutors’ level of engagement can measure the acceptability levels of the new academic deans.

Gathering data can inform on what strategies work best for a particular type of change. Data is used to influence and accelerate institutional transformation in several ways. First, data is used as a baseline for defining the change roadmap. Baseline data eliminates the implementation of any change initiative that comes up. Instead, it helps select and prioritize change strategies that are likely to succeed with the existing resources. Secondly, the use of data creates a culture of learning and dependence. Information can be used to enhance the integrity and attract internal backing for change campaigns. Thirdly, data is used to measure progress and quickly make necessary changes to the transformation plan (“How can data accelerate change management? — Visual workforce,” 2019), making institutions swifter in the change management process. The fourth reason why data is considered crucial for change is that it helps establish and build on change skills. Finally, it is important to note that information is not only used to reduce resistance to change, but it is also used to deliberate on an approach that can proactively build resilience among employees.

Internal Challenges to Change

Colleges are increasingly using data to improve student success through effective leadership, decision making, and sufficient resources. In the case study, finding a balance between classroom work and clinical practice was expensive, and payers were unwilling to pay extra costs. The faculty-managed health clinics that were proposed to provide the deficit amount were not a success. Also, the health department in St. Catherine had twenty programs and relied on partnerships with community-based clinics and local area hospitals. However, after some time, the College faced difficulties securing placement positions for their students due to the reduced number of healthcare workers available to teach on-site. Lastly, the curriculum designers felt market-driven, but it was later put to the test by the kind of credentials graduates were expected to have in the marketplace. All these decisions were assumed to be informed by data to ensure students were trained to be problem-solving professionals, but they were ineffective.

Data can be an effective tool for colleges to improve student outcomes. Students’ persistence and success are a reflection of the overall institutional performance. The primary principle for an effective student retention program is an institutional commitment to ensuring student success. The College of St. Catherine needs to apply data-driven approaches to ensure that it produces competent healthcare graduates who can effectively compete with their peers and quickly respond to care trends.


How can data accelerate change management? — Visual workforce. (2019, December 31). Visual Workforce.

Winkler, M. K., & Fyffe, S. D. (2016). Strategies for cultivating an organizational learning culture. Washington, DC: Urban Institute9.

Last Updated on April 19, 2021

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