Transforming Management Oversight of Payroll using ALICE !

Transforming Management Oversight of Payroll using ALICE !

The Scenario

Payroll is often the single biggest expense line item in a company. It is also seen as “high-risk” related to human resources, legislation, and disbursement of cash. 

We completed a use case with a leading logistics company with a distributed and diverse workforce. The workforce was split between salaried and wage-earning employees, with different policies, apply to different categories, locations, business units of employees. 

We learned that Payroll was audited on an annual basis by the Internal Audit function and actively monitored by management using custom-developed reports. The biggest problem was there was holistic view of payroll for leadership.  This was a major problem that needed to be resolved as soon as possible. 

ALICE was primarily tasked with providing digital services around ensuring management oversight of payroll costs. 

ALICE Procedures & Outcomes

ALICE produced a comprehensive set of insights supporting the managing and monitoring of payroll. 

Some examples of the insights included: 

  1. Payroll expense trends
  2. Payroll components and drivers 
  3. Compliance with legislation 
  4. Compliance with company policy 
  5. Identification of potential risk items for further investigation 
  6. Validation and recalculation of accruals

Data Assets Used

Using various ALICE connectors, including the API, the system was integrated with multiple data sources. This included the following categories of data assets.

  1. Listing of all employees (across all categories)
  2. ESS Audit Logs 
  3. General Ledger mappings 
  4. General Ledger postings 
  5. Data sets highlighting leave policies

Human Intelligence

Audit and assurance leaders provided vital inputs to help design algorithms for the following logic: 

  1. To measure compliance with policies such as compulsory leave taken, sick leave management, etc. 
  2. To review the month-on-month payroll, categorized into different components and different drivers/ levers 
  3. To assess the risk of “fictitious” employees given the nature and size of the workforce, value of payroll and distribution of oversight

This helped set up rule-based algorithms into the digital service to be offered by ALICE. 

The Outcome

Here are a few highlights post-deployment of the ALICE platform. 

  1. Data modeling to analyze employee leave behavior helping the company to draw insights about its own people.
  2. Machine learning is applied to learn from data models and provide suggestions for the payroll strategy.
  3. Standardized working papers of all procedures were performed, and a preview was configured to offer a dashboard view of all critical insights.
  4. Single-lens view of risks associated with the company’s people and payroll strategy. 
  5. Recalculation of complex accruals and independently validated management’s estimates. The outcome was recorded in a working paper with underlying data available for downloading for
  6. ALICE is able to complete the procedure within seconds what human would take hours. Now, humans are tasked with the high-level analysis of the output of ALICE. 

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