| Course | HRM-7640 Technology, Data, and Analytics as Change Agents |
|---|---|
| Module | Module 2 |
| Paper type | Module 2 written assignment: developing an analytics culture |
| Length | About 720 words, 5 pages |
| Format | APA 7 student paper |
| School | Thomas Edison State University |
| Program | MBA in Human Resource Management |
| Updated | October 2026 |
Free sample paper for HRM 7640 Module 2
Data, Skills and Questions: Building an Analytics Culture at Shoreline Home Health
Student Name
MBA in Human Resource Management, Thomas Edison State University
HRM-7640: Technology, Data, and Analytics as Change Agents
Mentor Name
Month Day, Year
Data, Skills and Questions: Building an Analytics Culture at Shoreline Home Health
Introduction
Shoreline Home Health wants to predict which new aides will leave within ninety days, the question proposed in Module 1. When HR tried to assemble the data, it found that the payroll system, the scheduling system and the applicant tracking system recorded hire dates differently, that 15 percent of aides lacked a recorded recruiting source and that supervisors' reasons for departures were free text. Supervisors, asked about turnover, said they "can tell in the first week who will last." The agency's problem is not only data; it is a culture in which decisions are not expected to rest on evidence. This assignment examines what an analytics culture requires and how Shoreline can build one.
What an Analytics Culture Is
An analytics culture is one in which people ask questions that data can answer, expect decisions to be supported by evidence and trust the data enough to act on it. Fitz-enz and Mattox (2014) argue that analytics changes HR only when leaders ask for it and act on it, not when HR produces pieces of analysis on its own. Rasmussen and Ulrich (2015) add that analytics succeeds when it starts from business challenges and when HR builds credibility by delivering useful answers to real problems.
Capabilities Required
Minbaeva (2018) proposed that credible human capital analytics depends on three dimensions of organizational capability: data quality, meaning consistent, accurate and accessible data; analytical competencies, meaning the skills to analyze data and translate results; and strategic ability, meaning the capacity to connect analytics to strategy and to act on findings. Each is a weakness at Shoreline.
| Capability | Current state at Shoreline | Gap |
|---|---|---|
| Data quality | Three systems with conflicting records; missing fields | No common definitions or owner |
| Analytical competencies | One HR analyst with spreadsheet skills | Limited statistical and communication skills |
| Strategic ability | Leaders read reports but rarely ask questions | No link between analytics and decisions |
Barriers
Three barriers are specific to HR at Shoreline. First, ownership: no one is responsible for HR data definitions, so each system's administrator records data differently. Second, skepticism: supervisors see analytics as a challenge to their experience, and some fear that data will be used to judge them. Third, ethics and privacy: aides' data include home addresses and health information, and they may be uneasy if they learn the agency analyzes their records without explaining why.
A Twelve-Month Plan
| Months | Action | Capability built |
|---|---|---|
| 1 to 3 | Create a data governance group; define hire date, departure reason and recruiting source; assign data owners | Data quality |
| 1 to 3 | Replace free-text departure reasons with a coded list plus comments | Data quality |
| 3 to 6 | Train the HR analyst in regression and data visualization; partner with finance's analyst | Analytical competencies |
| 3 to 6 | Train supervisors to read simple dashboards and to record data consistently | Analytical competencies |
| 6 to 9 | Leadership team adopts three standing questions for monthly reviews: what changed, why, and what will we do | Strategic ability |
| 6 to 12 | Run the first predictive project on ninety-day turnover with the operations director as sponsor | Strategic ability |
| Throughout | Publish an HR data use statement for employees; restrict access to sensitive fields | Ethics and trust |
Engaging Supervisors
Supervisors' experience is an asset, not an obstacle. The plan will invite supervisors to suggest predictors from their experience, test them with data and see their ideas confirmed or refined. If a supervisor believes aides with long commutes leave early, the data can show how much. This turns analytics into a way of sharpening supervisors' judgment rather than replacing it, which reduces resistance.
Ethical Safeguards
An analytics culture must be trustworthy. Shoreline will use HR data only for purposes stated in the data use statement, limit access to identifiable records, avoid using predictions to make hiring decisions about individuals until the model is validated and checked for fairness across groups, and use predictions mainly to offer support, such as mentoring, to new aides at higher risk.
Conclusion
Shoreline's analytics problem is cultural as much as technical. Using Minbaeva's three dimensions, the agency can build data quality through governance, analytical competencies through training and partnership, and strategic ability by making leaders ask and act on questions. With ethical safeguards and supervisors as partners, the agency can move from monthly reports to decisions informed by evidence.
References
Fitz-enz, J., & Mattox, J. R., II. (2014). Predictive analytics for human resources. John Wiley & Sons.
Minbaeva, D. B. (2018). Building credible human capital analytics for organizational competitive advantage. Human Resource Management, 57(3), 701-713. https://doi.org/10.1002/hrm.21848
Rasmussen, T., & Ulrich, D. (2015). Learning from practice: How HR analytics avoids being a management fad. Organizational Dynamics, 44(3), 236-242. https://doi.org/10.1016/j.orgdyn.2015.05.008
HRM 7640 Module 2 instructions, in plain terms
The first of two HRM-7640 written assignments, which share 30 percent of the grade, is about building an analytics culture. Expect questions about what an analytics culture is, which capabilities it needs, what barriers exist in HR and how an organization can build one. Use the course text and analytics research on a workplace you know, preferably your final project organization, and propose a plan it could follow. Address the people side, such as leaders and supervisors, and the ethical side, such as privacy and fairness, not only data and tools. Use APA style. Expect to discuss both the technical side, such as data definitions, and the human side, such as leaders' willingness to act on evidence.
How the HRM 7640 Module 2 example is put together
The paper opens with a concrete failure to assemble data and a revealing comment from supervisors. It defines an analytics culture from the text and research. A table rates the organization on three dimensions of analytics capability, showing gaps in all three. A section identifies barriers specific to HR, including ownership, skepticism and privacy. A twelve-month plan table assigns actions to capabilities. Sections on engaging supervisors and ethical safeguards complete the plan. Each recommendation addresses a gap identified earlier. Engaging supervisors as contributors of hypotheses addresses resistance in a way that builds the culture the plan seeks. Ethical safeguards are presented as part of the culture, not an afterthought.
Reading the HRM 7640 Module 2 grading rubric
Mentors grade this assignment on understanding of analytics culture and capabilities, analysis of an organization's gaps and barriers, the feasibility of the plan and attention to ethics. Answers that use a research framework to diagnose the organization and build a phased plan show depth. Recognizing that culture and leadership matter as much as data demonstrates insight. Ethical safeguards for employee data show professional responsibility. Tables that show gaps and actions help the mentor follow the plan. Mentors also credit plans that assign ownership of data definitions and sequence the work so early wins build support. Using a research framework to organize the diagnosis shows scholarly grounding. Clear tables make the gaps and actions easy to follow.
Common HRM 7640 Module 2 mistakes, and how to avoid them
Students lose points by treating analytics culture as buying software, by ignoring leaders' role in asking for and using analysis or by overlooking privacy and fairness. Others propose plans with no sequence. Diagnose data, skills and leadership separately. Address resistance by involving people whose judgment analytics might seem to challenge. Phase the plan. State how employee data will be protected. A free first sample using your own HRM-7640 Module 2 organization is available on request. Start with a specific example of a data problem in your organization. Assign owners to data definitions. Explain how leaders will use analysis in regular meetings. Say how employees will learn how their data are used.
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HRM 7640 Module 2 questions, answered
Where can I find a free HRM 7640 Module 2 sample paper?
The complete Module 2 paper on building an analytics culture at Shoreline Home Health is above, with a capability diagnosis and a twelve-month plan.
What is an analytics culture?
A culture in which people ask questions data can answer, expect evidence for decisions and trust the data enough to act on it.
What capabilities does HR analytics need?
Research identifies data quality, analytical competencies and strategic ability to connect analysis to decisions.
How can supervisors be brought into analytics?
By inviting them to propose predictors from experience and testing their ideas with data, so analytics sharpens their judgment.
What ethical safeguards does HR analytics need?
Clear statements of data use, restricted access, fairness checks before using predictions about individuals and a focus on support.