Leveraging The Massive Volume Of HR Data To Ensure Legal Compliance

Data is the currency of exchange in the digital economy

Thomas Friedman in his book, “Thank You for Being Late,” suggests that technological innovation in the digital age is accelerating at a pace which makes it challenging for businesses to adapt. The volume, variety and the velocity data create formidable challenges for organizations to mitigate compliance risks.

 

Robert Sheridan, a partner in the labor and employment department of Nelson Mullins, and co-author of the ground-breaking New York Law Journal article, “Big Data Analytics May Haunt Employers” cautions that “technology is moving so fast that this is an area where its capabilities have outpaced our ability to carefully consider the legal concerns.”
 
The confluence of the proliferation of data and the disruptive impact of the digital economy on the nature of work creates unique challenges for employers to mitigate risks, safeguard employee records while at the same time harness data to create sustainable competitive advantages in the digital economy.

Digital transformation is creating a number of challenges for employers, in particular, adherence to a more rigorous compliance framework that safeguards employee data. At the core of it is the need for a cohesive information governance framework that enables organizations to discover, classify and manage their information holdings that span across multiple information repositories.
 
More specifically, contracts contain the critical business intelligence you need to run your enterprise. According to the Institute for Supply Management, a typical Fortune 1000 company manages anywhere between 20,000 to 40,000 active contracts at any given time, 10% of which are misplaced, difficult to find, or buried in an email attachment, not managed. Many companies will have thousands of such contracts and documents, all of which need to be managed and the content therein properly utilized to understand obligations and to mitigate risks.
 
Many of those contracts will deal with critical employment information, such as employment agreements, subcontractor agreements and NDAs. Dealing with such a vast volume of data is a daunting task, and the difficulty of it is only increased by the pressures of litigation and regulatory investigations. Fortunately, there are now solutions available that can give you what you need to take back control.

Contract analytics uses the power of machine learning and Natural Language Processing (NLP) to extract the meaning from documents, converting the human-readable text into machine-readable content. Instead of having to hand-review thousands or even tens of thousands of contracts, you can use contract analytics to extract, manage and analyze the content – and present it in a form that you can easily and quickly put to use:

An example of this focused power would be a situation where a company needs to identify specific employees who are potentially subject to specific clauses in an employment agreement.  We spoke with Ralph Losey, a partner at Jackson, Lewis and an internationally-known expert who has used search tools to save his clients millions of dollars in eDiscovery costs in litigation.  He identified for us a recent client litigation matter where, even though he was able to use his unique skills to save his client substantial eDiscovery costs, a contract analytics solution would have let him go one step further. 
 
Losey’s client needed to search through over 30,000 employment agreements in various formats to identify only those workers subject to a particular clause that applied to just one state.  Normally, this would have been an easy task for search software, except that the specific state was also contained in the clauses for governing law and venue. Thus, the search for the state in question brought back the entire, 30,000 document set, requiring Losey to make a manual search instead.  A solution that understood and differentiated between the clauses of the agreement would have not only saved the client substantial additional attorney fees.
 
Nelson Mullin partner Robert Sheridan concurs that the use of this kind of analysis only going to expand: “The biggest push for the regulators now, the EEOC and state attorneys general, their low-hanging fruit so to speak, is examining the process of recruiting and screening. A lot of cases and enforcement actions have arisen in this area. . . Big Data is here to stay and the technology is becoming more and more sophisticated – and cheaper – for analyzing that data.”

However, not every event presents an emergency response situation. Most HR or labor and employment needs arise as part of an all-too-routine process that can create a form of “death by a thousand cuts.”  To reduce those costs and the attendant risks of such non-emergent “emergencies” you need to take contract analytics to the next level by combining it with robots, in the form of something called Robotic Process Analysis.

Robotic Process Automation (RPA) is a new buzzword and a potentially transformative technology that is proven to drive costs out of labor-intensive and error-prone business processes such as employee on-boarding and compliance. RPA is designed to remove highly repetitive, error-prone and labor-intensive data-driven business processes such as employee on-boarding:

“Instead of having to manually update the applicant tracking system after a new hire, make a new employee record for your employee database, gather employee documentation and create a new employee in your payroll system, . . . It makes it possible for your software systems to communicate with each other. And in a world of frequent regulatory change, RPA can double-check HR compliance, saving the company from big fines.”
 
A particularly labor intensive and error process is compliance with regulatory requirements, such as Privacy. The Digital Economy ushered in a heightened sense of strengthening data subject rights. The EU General Data Protection Regulation is perhaps the most consequential privacy regulation in the past 20 years in that it brings privacy law into the digital age. 
 
The Regulation implements some of the most stringent privacy rules, empowers data subjects with more control over what’s collected and shared about them, and incorporate some of the toughest enforcement mechanisms. The GDPR sets out strict mandates around reporting the theft or loss of personal data. Employee-related data is not just highly personal in nature, because of the sensitive data that is often collected about employee’s finances, health and their child-dependents for benefits, such data is quite often far more sensitive in nature and in need of even stricter protection than usual, such that companies must now:
 

 
Conclusion: It’s time to put innovation to work for you if only to solve all of the problems that innovation creates
 
Even though we started with the wise words of Thomas Friedman, you probably didn’t need him – or us – to tell you how the pace of innovation seems, if anything, almost out of control.  That’s because, to put it bluntly, you’re living it, every hour of every day. The challenges are real.

When those challenges take the form of acute surprises like litigation or regulatory investigation, contract analytics can give you the power to handle them with the same speed and certainty you had in the “good old days” when you just had to read through a few agreements and be done with it. 
 
When those challenges are more grindingly, almost perniciously systemic, adding the power of Robotic Process Automation to the mix lets you take back control and drive efficiencies.  In any event, with the power of text analytics at hand, you are ready to meet – and beat - any new challenges that come your way.