TRUSAIC's Data Quality Management with WAM
The path to success starts with accurate data
In order to make decisions using workforce data that your organization can trust, your data needs to be accurate. The use of inaccurate data by U.S. businesses is having a massive impact.
Adverse Impact from Poor Data Quality
- Inaccurate data cost the U.S. economy $3.1 trillion in 2016.1
- One in three business leaders don’t trust the information they use to make decisions.2
- On average, U.S. organizations believe 32% of their data is inaccurate.3
- 91% of executives indicated their revenue is negatively affected by inaccurate data in terms of wasted resources, lost productivity, or wasted marketing and communications spend.3
- 92% of senior executives are concerned about the negative impact of data and analytics on corporate reputation.4
- Only 10% of senior executives felt their organization excels in managing the quality of D&A.5
What Causes the Problem
The challenge of obtaining accurate workforce data starts with collecting that data from a mix of separate and often disjointed data bases: Payroll, Time and Attendance, Leave of Absence, Benefits Administration and automated HR systems.
Trusaic’s Data Quality Management with WAM plays an important role in ensuring accurate data is used for critical business operations, such as ensuring compliance with complex regulations or performing analytics for business intelligence purposes.
Contact us to review your options today.
TRUSAIC's Data Quality Management With WAM
Triangle of TrustSM
Trusaic's proprietary Workforce Analytics Machine (WAM) software was developed based on the principle of the Triangle of TrustSM.
The Triangle of TrustSM is the foundation of our efforts to serve our clients. This principle calls for the optimal alignment of three key elements, data, regulatory expertise and software, to ensure that our clients' critical compliance and business intelligence objectives are met.
Trust in Data
Data, such as Payroll, Time and Attendance, Leave of Absence, Benefits Administration and general HR information that are structured and unstructured, are frequently scattered across various databases and platforms. The data from these disparate silos need to be aggregated, consolidated and validated into an accurate data set to support regulatory compliance and business intelligence.
Trust in Regulatory Expertise
Regulatory expertise is critical to ensure the proper analysis and application of the data to the regulatory framework. Such expertise is needed to use the software effectively to meet regulatory compliance and business intelligence objectives.
Trust in Software
Software development is a multidisciplinary effort in software programming, database management, data science, data analysis and regulatory expertise. These experts need to work together to properly develop and program software that will apply the clean data to effectively address regulatory compliance and business intelligence needs. This is critical to obtain correct outputs.
The challenge with using do-it-yourself software is that it won’t tell you if the underlying data contains discrepancies. It won’t tell you whether the inputs are proper or whether the outputs create compliance issues or flawed results. This can lead to poor business decisions with significant financial consequences.
At Trusaic, we apply the principle of the Triangle of TrustSM so that your data, regulatory compliance and business intelligence objectives are met. We get the job Done and Done right.
TRUSAIC's Focus is Workforce Data
Why care about workforce data? Because it is becoming an ever-increasing part of operating costs. According to the U.S. Department of Labor:
Employer costs for employee compensation now average more than $36 per hour worked.
Wages and salaries averaged more than $24 per hour worked and accounted for more than 68% of these costs.
Benefit costs accounted for almost 32% of these costs.
Total employer compensation costs for private industry workers averaged more than $34 per hour worked.
Total employer compensation costs for state and local government workers is more than $49 per hour worked.
At the same time, regulatory compliance is becoming a growing risk for employers. The impact of using inaccurate workforce data for complying with regulations can be significant.
U.S. companies spend $2 trillion annually on government regulations.
The average first-year cost for a new business to comply with regulations is $83,019. That does not factor in the significant penalties that can be assessed for failing to comply with federal, state and local regulations.
Many times, compliance failures are the result of organizations using inaccurate data. Sometimes, they can be the result of a flawed approach to data analysis. Other times, they can be caused by not having people with deep regulatory knowledge to help apply the data correctly in addressing regulatory requirements.
The largest institutional investors in the world understand the importance of workforce data and metrics, which is why they petitioned the U.S. Securities and Exchange Commission to require publicly traded businesses to provide dramatically increased transparency into their human capital management practices, viewing it as a significant part of a company’s performance and liability risk assessment.
Accurate Data is the Foundation
In order to make decisions using workforce data that your organization can trust, your data needs to be accurate. Using accurate data is the foundation for critical business decisions in today’s world. And the use of inaccurate data by U.S. businesses is having a massive impact.
On average, U.S. organizations believe 32% of their data is inaccurate, according to research by Experian Data Quality.
Only 38% of executives have a high-level of trust in their data.
91% of respondents believe revenue is affected by inaccurate data in terms of wasted resources, lost productivity, or wasted marketing and communications spend.
IBM has determined that inaccurate data cost the U.S. economy $3.1 trillion in 2016.
Our GIGO Score provides clients with an analysis of the accuracy of their payroll data.
The higher the GIGO Score, the more accurate the data. The lower the score, the dirtier the data.
The GIGO Score helps employers monitor data health and determine whether problem points are trending up or down from month to month. By alerting employers data anomalies and inconstancies, they can take steps to address these data accuracy issues in their databases to avoid inaccurate regulatory filings that can result in significant financial penalties.
If your data is dirty, Trusaic can undertake a program to provide immediate improvements to workforce data quality to ensure that organizations are using the most accurate information when using information to comply with federal and state regulations or to make important business decisions.
Trusaic determines your organization’s GIGO Score by reviewing payroll data fields, such as names, social security numbers, hire and termination, wages, and rates of pay.
The GIGO Score analysis identifies inconsistencies affecting data health, such as:
Inaccurate hire and termination dates for employees
Duplicate social security numbers and other IRS identifiers
Nonsensical data like improbable rates of pay
Unrealistic hours of service worked by individual employees
Data values that don’t fit data formats
Obtaining a monthly GIGO Score can identify the pain points that are causing data quality fluctuations so that they can be addressed.
As your GIGO Score improves each month, you will see how the quality of the workforce data your organization is using makes a difference in your regulatory compliance processes and helping you to avoid costly regulatory penalties.