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Monitor & Correctly Pay Salaries, Entitlements, Superannuation, Overtime & Allowances

Summary

 

Incorrectly paying employees can result in significant penalties and damaging adverse media attention. The intricate and complex nature of agreements and modern awards demands secure, scalable solutions, able to handle growing transaction volumes and regular, proactive monitoring and testing.

 

Employment Cost Analytics augments your organisation’s operations with super-human memory, processing power and insights to generate timely, consistent, deliberate and reliable analytics for a greater chance at success.

Data Collected

  1. Working hours and timesheet data (e.g. Kronos, ADP, Workday Peoplesoft, TMS, Replicon, Xero, etc.) including task type, start/finish date and time, leave, and more.
    Awards and Enterprise Agreement Data including base rates, overtime rates, allowance rates, leave liabilities etc.
    Superannuation data including superable task codes, expected super and paid super.
    Overtime by employee, day, task, location, department, overtime rate (1.5x, 2x, etc.), NES or EBA classifications etc.
    Other allowances by employee, day, task, location, department, NES or EBA classifications etc.

Key Technologies and Processes

Collect and Centralise the Data

 

  1. Accelerators to automatically ingest large data volumes directly from source systems ready for transformation.

 

Transform the Data into Useful Insights and Predictors

Outcomes

  1. Pay employees correctly with confidence and proactively remediate any issues discovered.
    Improve productivity and reduce overtime and additional costs through better planning and rostering.
    Analyse and optimise superannuation to identify remediation opportunities.
    Monitor excess leave balances or excess leave taken.
    Simplify your agreements to reduce complexity and cost.
    Identify areas for controls, training and process improvement.
    Automated, alerts and monitoring when solution is deployed.
    Handle large volumes of data with scalability and performance.
    Perform super-human levels of analysis and decision making.
    Feed the obtained data into predictive models and use machine learning to predict workforce demand and rostering.

 

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