PMP · Question #185
A project team is preparing a report for the stakeholders. The team gathers and collates a large amount of data to be included in the status report. What should the project manager do next?
The correct answer is D. Instruct the team to analyze and interpret the data before including it in the report.. After gathering and collating a large amount of data for a stakeholder report, the project manager must instruct the team to analyze and interpret the data to make it meaningful for the stakeholders.
Question
Options
- AEnsure the team follows standard operating procedures (SOP) for creating a stakeholder report.
- BInstruct the team to make only a graphical representation of all the data for the report.
- CInstruct the team to conduct a meeting with the stakeholders before finalizing the report.
- DInstruct the team to analyze and interpret the data before including it in the report.
How the community answered
(38 responses)- A5% (2)
- B3% (1)
- C11% (4)
- D82% (31)
Why each option
After gathering and collating a large amount of data for a stakeholder report, the project manager must instruct the team to analyze and interpret the data to make it meaningful for the stakeholders.
While following SOPs is important, this step focuses on *what* to do with the data, not just the process of preparing the report itself, and analysis is a crucial missing piece after collation.
Limiting the report to only graphical representations might obscure critical details or prevent a comprehensive understanding of the data, and it still requires prior analysis to determine what to represent.
Conducting a meeting before finalizing the report can be useful for feedback, but the data itself must first be processed and understood by the team to present something coherent and valuable.
Simply collating raw data is insufficient for a stakeholder report; the data needs to be analyzed and interpreted to provide insights, context, and actionable information. Stakeholders are interested in understanding the implications of the data on project progress, risks, and overall status, which requires the team to process and explain the information effectively. This step transforms raw data into valuable knowledge for decision-making.
Concept tested: Data analysis and reporting for stakeholders
Topics
Community Discussion
7D is the correct answer here. Data without interpretation is just noise, and the PM's job is to make sure stakeholders get actionable information, not a raw data dump. Options A and B are too dogmatic and miss the point, while C sounds collaborative but is unnecessary at this stage. The team needs to analyze and synthesize the data first so the report actually tells a meaningful story about project health.
Think of it like hauling a truckload of raw lumber to a client's front porch and calling it a finished house. The team has gathered the lumber, but the PM's job is to make sure they actually analyze and interpret that data before handing it over, which is the difference between raw data and useful information. Option B is a tempting trap because graphs are great, but slapping a pie chart on uninterpreted numbers just gives you a pretty picture of confusion. D is the only real answer here, confirmed on my exam last week.
D showed up on my exam last month, almost word for word. The trap is wanting to jump straight to graphics with B, but PMI wants you to remember that raw data has to be analyzed and interpreted first before it becomes useful information for stakeholders.
Good catch on the raw-versus-interpreted distinction, though I would add that the real trap in B is skipping the analysis step entirely, like serving flour and eggs to dinner guests and calling it a cake.
D is correct. A tempts people because SOPs sound governancy, but raw data without interpretation is noise, not information.
D wins, raw data is useless till you interpret it. Anyone know if PMP always pushes data over info here?
D is right but the exam framing is really about information being data with context and meaning applied, so watch for that pairing rather than a data over information bias.