06 Nov Unit 4_MT497_Discussion response
13762Respond or elaborate on the response below:
Intuition and evidence-based decision making can both work effectively within an organization because each method brings unique strengths. Intuition comes from experience and pattern recognition, allowing managers to make quick judgments in situations where information may be limited. Evidence-based decision making, on the other hand, relies on data, research, and structured analysis. According to Daft (2021), many leaders today use quasirationality, which is a balanced approach combining logical analysis with intuitive insight to make well-rounded decisions in complex situations.
This idea is supported by cognitive continuum theory, which explains that intuition and rational analysis are not opposites, but rather exist on a spectrum. Kenneth Hammond’s work shows that the most effective decision making often occurs in the middle of that spectrum, where managers use both structured reasoning and intuition together (Dhami & Mumpower, 2018).
This means managers might review data first and then use their intuition to interpret what the patterns mean in real-world terms. For example, in a construction project environment, data might show that labor productivity has decreased, but a project manager’s intuition may indicate that the root cause is not staffing levels but communication gaps or unclear expectations during daily briefings.
Artificial intelligence (AI) will likely play a growing role in evidence-based decision making. One advantage of using AI is that it can quickly analyze large amounts of information and detect patterns that may not be obvious to humans. This can help managers make faster, more accurate decisions and reduce errors caused by emotional bias or stress. AI can also support strategic planning by predicting risks or outcomes based on past trends. However, there are also disadvantages. AI cannot understand emotional context, workplace relationships, or the culture of a team. If the data provided to AI is incomplete or biased, the results may also be flawed. Relying too heavily on AI may also cause managers to overlook the importance of intuition, experience, and human judgment. Research shows that intuition works best when the environment allows professionals to learn from experience and receive feedback over time (Fleißner & Steimle, 2024). Because of this, AI should be used as a tool to support decision making, not replace human reasoning.
In construction project management specifically, both intuition and data-driven methods are used daily. For instance, scheduling decisions are typically based on data, such as production rates and material lead times. However, intuitively recognizing when a subcontractor is overwhelmed, when a safety concern is developing, or when a design detail will cause field issues often comes from experience and awareness, not just data. The best project managers combine analytical planning tools with intuitive judgment gained through real-world site experience.
Intuition and evidence-based decision making can coexist successfully when managers understand how to balance them. AI and data analysis can provide clarity and support accuracy, while intuition adds human understanding, experience, and awareness of context. The most effective leaders are those who intentionally use both.
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