Data Driven Human Resources

Data driven human resources is an adaptable system of managing labor needs, employment lifecycles and preserving corporate knowledge while easily complying to new and changing regulations.  Without consolidated data assets, optimized labor forecasts, recruitment data and compliance data, exposure to risk is increased, both legally and in succession planning.

Human Resource adaptability is driven by the demand for effectively hiring, developing and rewarding human capital while at the same time maintaining compliance in a shifting regulation environment.  By improving system integration, the costs and complexity of culture and talent management are lowered.

As demand to systemize talent management data increases and the regulatory environment shifts, a quality data system facilitates the ability to adapt, reduce costs, and improve reporting. Informed decisions create effective talent management and reduce risk.

Improve Employee Lifecycle Management

With a data management solution from Zendeux you’ll create opportunities in your human resources management, lifecycle management practices, and reporting that address your business objective. By mitigating data quality issues you’ll enable full utilization of your data assets.

The Zendeux solution for Data Driven Human Resources reduces your risk arising out of mismanaged data and leverages the Zendeux Data Management Framework, providing quality analytics for trusted data and trusted decisions. The framework implementation includes:

  • Improved data usability in Human Resources
  • Accelerated decision making
  • Consolidated reports and increase accuracy
  • Improved forecasting accuracy
  • Enabled real time HR analytics
  • Improved employee satisfaction
  • Utilization of internal and external technologies

The Zendeux Data Management Approach

Zendeux combines industry best practices with our collective experience solving numerous data management challenges. Our Zendeux Data Management Framework is specifically designed to quickly engage and gain consensus amongst key stakeholders, and rapidly advance the project from problem definition to solution implementation. The ZDMF has been successfully employed across a broad range of industries and business areas to implement effective data management solutions, including such Fortune 500 companies as Cisco, Ingram Micro, Yodlee, Huawei, Newmont Mining, and others.

Our Data Management consultants and specialists combine experience and the tools of the Zendeux Data Management Framework to quickly and accurately determine your current state, challenges to meet the business objectives, and a corrective course of action.  Our focus is quality alignment to contextual business intent.

Engagement Deliverables

Utilizing the Zendeux Data Management Framework, a Data Driven Human Resources engagement provides a step by step process to fully discover finance data objectives in a well-defined project that produces immediate and actionable benefit to the business.

  • Identify current state risks and opportunities using the Industry Data Management Audit.
  • Engage stakeholders in Human Resources and related areas to define business objectives that affect Human Resources, its upstream, and downstream processes.
  • Create business consensus across Human Resources, upstream, and downstream processes to define standard enterprise data definitions for master, transactional, and reporting data in Human Resources.
  • Align Human Resources data, systems, and processes to Human Resources objectives and provide seamless data flow to other business processes outside of Human Resources.
  • Reduce bottlenecks and operational costs in Human Resources processes through data, systems, and process optimization.
  • Establish sustainable data governance processes, policies, and organization to ensure ongoing excellence in data quality in Human Resources processes.
  • Empower business Stewardship and accountability in Human Resources at executive and user levels.
  • Baseline and measure business data quality requirements in Human Resources and establish data quality monitoring and mitigation as part of data governance duties in Human Resources.