Smart Reporting In Oracle HCM: Use Natural Language To Build OTBI Queries

In a traditional public sector HR setting, a request for a report on overtime hours, absence rates, or contract renewals follows a familiar pattern. The HR team drafts a request, submits it to IT or a reporting specialist, and waits while the request is translated into an OTBI query. The process can take days, sometimes weeks, especially if the first version of the report needs refining.

This delay not only slows decision-making but also discourages HR teams from exploring data proactively. The result is missed opportunities for workforce optimisation and, in some cases, delayed compliance reporting.

Natural Language Query removes the technical barriers to OTBI reporting. Instead of navigating menus, picking columns, and defining filters manually, users simply type a question or instruction in plain English. The AI engine interprets the request, identifies the right OTBI subject areas, applies joins, filters, and calculations, and produces the desired report in real time.

For example, instead of asking IT for a report showing absence days by department and reason over the last fiscal year, an HR manager can type:

"Show me absence days by department and reason for FY 2023–2024"

The system then generates the report instantly, without the need for technical intervention.

For public sector organisations where budget constraints and operational demands are constant, NLQ-enabled OTBI offers significant advantages. Faster access to data means HR teams can respond quickly to leadership queries, compliance requirements, and operational challenges. In local government, this could mean providing diversity metrics for a public accountability report within hours rather than days. In higher education, it could mean producing workforce allocation reports during term start without overwhelming IT. For healthcare providers, it ensures compliance and workforce planning can be adjusted on the fly.

Consider an HR manager in a university who needs a report on overtime hours by department for the last academic term. In the past, they would submit a request to IT, wait for a draft report, review it, and request changes — a process that might take a week. With NLQ, they simply type their request and have a usable report in minutes.

This shift transforms the relationship between HR teams and their data, making it an everyday tool rather than an occasional resource.

While every organisation has unique requirements, there are some common reporting needs across public sector HR teams that NLQ is particularly well-suited to address:

1. Headcount and workforce distribution reporting.

2. Absence and leave trend analysis.

3. Overtime and additional hours monitoring.

4. Contract renewal and probation tracking.

5. Diversity, equity, and inclusion metrics.

6. Training and certification compliance.

With NLQ, each of these reports can be generated by simply typing a question, without technical skills.

In public sector HR reporting, data security is non-negotiable. NLQ-enabled OTBI respects Oracle HCM’s existing security model, ensuring that users only see the data they are authorised to access. A local government payroll officer will not be able to retrieve sensitive executive HR data, and a healthcare HR assistant will only see information for staff they manage.

This approach ensures compliance with UK GDPR regulations, US HIPAA requirements for healthcare, and other relevant privacy laws. All AI-driven queries are logged for audit purposes, providing a clear trail of who accessed what data and when.

As a leading Oracle ERP and HCM services provider, Firstcron specialises in tailoring NLQ-enabled OTBI for the unique needs of public sector organisations in the UK and US. This includes ensuring that AI models are trained on the organisation’s specific data structures, aligning reporting templates with compliance requirements, and providing targeted training so HR teams can use the system confidently.

Firstcron’s approach ensures that NLQ is not just a technical feature but a practical, embedded part of the HR function.

Introducing NLQ requires more than just technical deployment. HR teams need to understand how to phrase queries, how to interpret AI-generated results, and how to refine reports as needed. Firstcron supports this transition with practical training, hands-on workshops, and support materials.

By focusing on change management as much as technology, adoption is smoother, and the benefits are realised faster.

While NLQ for OTBI is already transforming HR reporting, the potential for expansion is clear. In the future, similar AI-driven capabilities could be applied across Oracle ERP modules, allowing finance, procurement, and operations teams to query data in natural language and receive instant, accurate results

The ability to build OTBI reports in Oracle HCM using natural language is a major leap forward for public sector HR teams. It removes technical barriers, speeds up reporting, improves data accuracy, and empowers HR staff to engage with data directly. For local government, higher education, healthcare, and public agencies in the UK and US, this represents both an operational improvement and a cultural shift toward data-driven decision-making.

Firstcron is at the forefront of this change, ensuring that NLQ-enabled OTBI is secure, tailored, and embedded into public sector workflows. With conversational reporting now a reality, the future of HR analytics is not just smarter — it’s easier.

To learn more about how Firstcron can bring Natural Language Reporting to your Oracle HCM environment, visit Firstcron.