Write an Academic Report about using Advanced Analytics in HR

Write an academic report to address the following problem:

How can Human Resources use data-driven technologies like advanced analytics to drive employee engagement in order to create a work environment that fosters innovation?

Report specifications:

- Approximately 20.000 words

- APA style referencing

- Use relevant scientific references, a book is attached but feel free to use more sources


Human Resources executives face an overwhelming list of imperatives: predicting and fulfilling business requirements, meeting diversity targets, and decreasing recruiting and retention costs. Meeting these demands requires Human Resources personnel to make strategic decisions that can influence much more than obligation authority and public value—these decisions have the power to energize or disrupt the workforce, embolden or jeopardize policy.

Furthermore, many present-day Human Resources systems cannot meaningfully analyze the complex dimensions of employee behavior, workforce capabilities and Human Resouces processes that keep organizations on course toward their strategic goals.

As budgets shrink, increased scrutiny falls on workforce decision makers to promote lean organizations and trim overhead. To do so efficiently and effectively, Human Resources departments cannot afford to rely on historical data alone; they need advanced analytics to drive informed decisions that demonstrate an understanding not only of past behavior but more importantly of current and future trends.

Using advanced analytical techniques such as data mining, predictive modeling and factor analysis, Human Resources can help the organization answer important questions:

Which policies drive better workforce performance?

What organizational and talent levers can be pulled to improve employee satisfaction while maintaining performance?

Which top performers in the organization are at risk of leaving and how might they be enticed to stay?

Answers to these questions and others like them can have measurable results, such as lower Human Resources expenses, reduced workforce costs, increased employee productivity and improved customer service.

With that in mind, Human Resources needs to develop a data-driven framework for solving workforce problems using existing information to drive new insights. A four-phased approach that enables organizations to use advanced analytics to improve workforce planning, align organizational capabilities and derive better value from workforce talent across the entire Human Resources lifecycle.

Phase 1: Identify pressing concerns. Whether an agency’s pain points lie in recruitment, retention or any other aspect of the Human Resources lifecycle. A targeted and goal-oriented approach reduces redundancy and encourages meaningful transformation.

Phase 2: Establish key performance indicators (KPIs). Consider legacy and new data sources and establishes performance metrics for baseline comparison. This approach clearly defines what constitutes a positive outcome so that the analytical discovery fully aligns with a policy’s goals.

Phase 3: Collect and analyze historical data, workforce preferences and recruiting trends to produce a picture of an organization's Human Resources climate. Then employ proprietary models to produce key insights about the agency’s programs and strategies.

Phase 4: Tracking the results. Using established baseline metrics, quantify analytics, cost effectiveness and organizational improvements against desired results.

Taidot: Datatiede, haamukirjoittaminen, henkilöstöhallinto, Raportin kirjoittaminen, Tieteellinen tutkimus

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