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Transforming management oversight of payroll using ALICE

ALICE assisted management to gain oversight of their diverse payroll through data analytics and automated testing.  Read more on how ALICE did this.

The Scenario

Payroll is often the single biggest expense line item in a company. It is also seen as "high-risk" as it relates 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 being applied to different categories, locations and business units of employees. 

We were informed 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 the lack of a 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 this oversight of payroll costs to leadership through digital services. 

 

ALICE Procedures & Outcomes

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

Some examples of the insights included: 

      • Payroll expense trends;
      • Payroll components and drivers; 
      • Compliance with legislation; 
      • Compliance with company policy;
      • Identification of potential risk items for further investigation; and 
      • Validation and recalculation of accruals.

 

Data Assets Used

Using various ALICE connectors and application programming interfaces (“APIs”), the system was integrated with multiple data sources. This included the following categories of data assets:

      • Listing of all employees (across all categories);
      • Employee Self Services (“ESS”) audit logs;
      • General Ledger (“GL”) mappings; 
      • GL postings; and
      • Data sets highlighting leave policies.

 

Human Intelligence

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

      • To measure compliance with policies such as compulsory leave taken, sick leave management, etc;
      • To review the month-on-month payroll, categorized into different components and different drivers/ levers; and
      • 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:

      • Data modeling to analyze employee leave behavior helping the company to draw insights about its own employees;
      • Machine learning is applied to learn from data models and provide suggestions for the payroll strategy;
      • Standardized working papers of all procedures were performed, and a preview was configured to offer a dashboard view of all critical insights;
      • Single lens view of risks associated with the company's employee and payroll strategy; and
      • Recalculation of complex accruals and independently validated management's estimates.

All outcomes were recorded in a working paper with underlying data available for downloading for reperformance.

 

In a short period of time ALICE was able to accomplish many tasks that would have taken a human a much longer period to produce.  Instead, humans were tasked with more high-level analysis of the output of ALICE and actioning remediation for identified insights.  If your company is struggling to get a global or enterprise view of payroll, ALICE can supplement your current team and provide insights.

2020 | 8