NAKISA HANELLY INSIGHTS

Understand your HR data landscape to power the advancement of your organization.


HR Data Quality: Why it Matters

The power and significance of HR Data Quality has never been more relevant than it is today. On an ever-increasing basis, an organization’s data—be that Workforce data, People data, Talent data, etc.—is used to assess the health of the organization and make decisions affecting the future of the business.

The quality of the data being used to make those decisions needs to be sound. Data issues, which may arise completely unnoticed, can have a significant impact on the effectiveness of the decisions being made.

Poor data quality covers a multitude of issues such as:

  1. Missing employee contact information
  2. Active employees identified below the working age or over the expected age criteria
  3. Employees on payroll who should not be
  4. Positions that do not have a cost center or not associated with a business unit
  5. Location data missing

  6. Orphaned or duplicated employees

Identifying and correcting such issues is essential to effective business decision-making.

Data Quality Challenges

Multiple ERP or HRIS systems across the organization with no centralized source for quality checks

Loading “bad” data into other HR solutions without realizing there is an issue

Data inconsistencies due to general maintenance—human input errors can go unnoticed for years

Lack of visibility of what data is missing or incorrect

Nakisa Hanelly HR Data Quality

Providing a centralized visual interface to identify inconsistencies in data maintenance and other company-specific indicators, Nakisa Hanelly HR Data Quality enables organizations to address data integrity concerns and make corrections where needed. This is achieved in various ways:


  1. Automated detection of definable quality categories
  2. Dashboard summaries, tabulation of all data issues, data quality metrics, and trend graphics
  3. Company-specific prioritization levels and recommended actions to resolve inconsistencies and improve quality
  4. Control error resolution and processing times

Data Quality Insights:

Understand and identify an organization’s data integrity and consistency based on pre-defined business rules.

PA and OM Dashboards:

Display detailed analytics in Personnel Administration (PA) and Organizational Management (OM) groups to help users identify areas with data quality issues.

Search Results and Modify Error Status:

Utilize multiple view types to display object and error information and enable action.

By enabling organizations to identify gaps in their data, business leaders can then ensure complete HR data accuracy throughout the business. Nakisa Hanelly HR Data Quality acts as the cornerstone tool that provides organizations with the confidence that their business decisions are based on sound data.

Book an HR Data Quality Product Demonstration

Discover how Nakisa Hanelly HR Data Quality can ensure consistently clean, error-free data to fuel accurate decision-making for business success.

Nakisa Hanelly Insights: The Engine

Built on next generation engine analytics, Nakisa Hanelly Insights is the next leap forward in Nakisa technology. Using this technology as the base for our new suite of products, Nakisa Hanelly Insights capitalizes on machine learning technology, providing constant development. This includes progress into areas like predictive analysis and forecasting.

Nakisa Hanelly Insights enables the end user to:

regional support

View new sets of data and add customized charts and filters for targeted data analysis

proven go-to strategy

Base that data on their specific needs and preferences

comprhensive training program

Utilize preconfigured integration with existing Nakisa platforms and solutions for fast access and enablement

The engine behind Nakisa Hanelly Insights is built using native cloud architecture, and the data integration uses powerful a custom built ETL (Extract, Transform, and Load) tool in the cloud which, among other things, enforces data quality and consistency standards on the data, allowing the solution to make sense of the information and provide actionable insights.

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