WGU Data-Driven-Decision-Making Actual Questions

Performance indicators guide behavior, priorities, and decision-making. In data-driven decision making, selecting theright indicators ensures alignment with an organization’s definition of success. Metrics determine what is measured, monitored, and improved.

If indicators are poorly chosen, organizations may optimize the wrong outcomes, leading to unintended consequences. Well-aligned indicators translate strategic goals into measurable targets and ensure that analytics support meaningful results.

Rules, motivation, and compliance may be secondary effects, but the primary purpose of performance indicators is strategic alignment. Therefore, the correct answer isC.

Key performance indicators (KPIs) are designed to measure progress toward strategic objectives. In data-driven decision making, effective KPIs arestable, meaningful, and aligned with organizational goalsrather than frequently changing.

One important quality of KPIs is that theycan be used for internal benchmarking, allowing organizations to compare performance across departments, time periods, or projects. This helps identify best practices and performance gaps.

Another defining characteristic is that KPIs often followSMART criteria—Specific, Measurable, Achievable, Relevant, and Time-bound. These criteria ensure KPIs are clearly defined and actionable.

KPIs are not meant to be easily changed, as frequent changes undermine consistency and comparability. They also require ongoing monitoring and maintenance to remain relevant and accurate.

Therefore, the correct answers areB and D.

The fundamental difference between cost–benefit evaluation in the public and private sectors lies inhow benefits are defined and measured. In data-driven decision making, private-sector projects primarily focus onrevenue generation and profitability, making optionCthe correct distinction.

Private organizations evaluate benefits using measurable financial outcomes such as revenue, profit margins, and return on investment. These metrics provide clear, quantifiable indicators of success. In contrast, public-sector projects often aim to maximizegeneral public welfare, including social, environmental, and economic benefits that are more difficult to quantify monetarily.

Public-sector benefits may include improved public health, safety, education, or trust in government—outcomes that do not translate directly into revenue. Therefore, while costs are measurable in both sectors, benefits differ substantially in nature.

Options A and B are incorrect because public-sector costs are not minimal and public benefits are often difficult to quantify. Option D incorrectly assigns public welfare to private projects. Thus, the correct answer isC.

In data-driven decision making, themedianis the preferred measure of central tendency when data contain outliers or are skewed. Fundraising donation amounts often exhibit right-skewed distributions, where a small number of very large donations can significantly inflate the mean. Using the mean in such cases may misrepresent what a “typical” donor gives.

The median represents the middle value when donation amounts are ordered from smallest to largest. Because it depends only on position rather than magnitude, it isrobust to extreme values. This makes it especially useful for summarizing typical behavior in skewed financial data.

The mean is sensitive to outliers, the z-score measures standardized distance from the mean, and the mode identifies the most frequent value but may not reflect central tendency in continuous donation data. Therefore, the statistic that best represents a typical donation amount is themedian, making optionCcorrect.