<img height="1" width="1" style="display:none" src="https://www.facebook.com/tr?id=1509222356040859&amp;ev=PageView&amp;noscript=1">

Complete this form to request your access to the platform.

Ensure a Positive Candidate Experience When Hiring Contingent Talent Remotely

As digitization, coupled with the global pandemic, propels contingent hiring online and with more individuals relying on employer reviewer sites to evaluate businesses, delivering a positive[...]

March 10, 2021

Read More
All Posts

A Cool Idea Staffing Tech Could Embrace from BlackRock’s Risk X-Ray System

If you run in financial or investment circles, you’ve probably heard of BlackRock Inc., a global asset management company based in New York. It currently holds the distinction of being the planet’s largest asset manager. What you might not know? BlackRock is also a technology developer whose 30-year-old risk detection system is now emerging as the next big thing for financial advisers. I’ve often discussed the application of external innovations to the staffing industry, like Blockchain and FinTech. BlackRock’s platform also fits neatly in that category.

Yet what really intrigues me is the story of its development, which speaks to a talent singularity where machine, human, and network intelligence converge. And as with Blockchain, there’s also an undeniable allusion to the crowd’s role in powering our digital ecosystems.

BlackRock’s Aladdin: Uncorking a Genie’s Bottle

Writing for Bloomberg, Annie Massa presented a fascinating look at BlackRock’s Aladdin, a “risk x-ray tool” that was launched internally about three decades ago: “BlackRock Inc. created software to obsessively monitor the then-fledgling firm’s financial risks. Now, after turning it into an essential tool on Wall Street, the firm is zeroing in another kind of client: financial advisers.”

BlackRock began in 1988 as a fixed income institutional asset manager that approached its business from a risk management perspective. Then it grew, went public, and gained a more diverse portfolio of assets by acquiring holding companies, mutual funds businesses, and investment firms.

But along the way, BlackRock continued to rely on its internal risk-detection platform to drive its solutions. BlackRock never stopped building on that technology. Now, in a slight return to its roots, the enterprise is again emphasizing risk management -- and reimagining itself as a genuine tech provider. Not only do BlackRock’s senior leaders see Aladdin as the “language of portfolio construction,” they believe the platform has taken its place as the company’s identity, announcing to shareholders that “Aladdin is BlackRock.”

BlackRock’s platform grew organically, but its ultimate realization came from a type of crowd-sourced exercise: “BlackRock’s more recent plan grew out of an internal hackathon about three years ago. Engineers paved the way for a new product, called Aladdin for Wealth, which flipped the business model.”

Risk X-Ray Tech in Staffing? Why Not?

Aladdin is a backronym for Asset, Liability, Debt, and Derivative Investment Network. The system, Massa explained in her article, “monitors all of BlackRock’s portfolios, weighing what-ifs and worst-case scenarios, and even handles tasks like tracking corporate headcount.” If you get creative, and take pure finance out of the mix, similar machine learning algorithms could throw open the doors to new possibilities for our industry. Risk mitigation is a predominant topic in contingent workforce outsourcing, but imagine how much more we could achieve through AI?

Improved Diversity

Diversity persists as a pressing business topic across industries. Obviously, tech companies find themselves under the microscope more often, but the problem has a wide berth. Traditional remedies don’t seem to be working, so a lot of organizations have turned to technology for the cure.

The staffing industry has tried to promote ATS and VMS tools as a form of diversity tracking, but they really just offer a snapshot of basic EEOC data in the workforce or the statuses of vendor firms. Although you can analyze that data and come up with some assumptions, these methods don’t truly speak to cultivating inclusion on a large scale or determining potential risks. Some newer platforms are experimenting with different approaches.

A specialty matching site called Jobwell concentrates on connecting companies with African American, Hispanic/Latino, and Native American talent. Jobwell encourages candidates to display their diversity data in their online profiles. While a great step in the right direction, the site seems to focus on a specific type of diversity. And by featuring racial, ethnic, or gender data upfront, prejudiced hiring managers can easily skip over these applicants without much fallout.

More effective solutions involve predictive analytics, machine learning, and even virtual reality (VR) to foster empathy and remove any candidate information that could inform existing biases. But I’d like to see where AI could take us -- where a risk x-ray system could detect and mitigate issues before they arise. Consider what such a system could do.

  • Measure risks based on the language used in job postings or inter-office communications.
  • Assess real-time inclusion across departments and managers to determine where successes and challenges that could be caused by individuals rather than corporate culture.
  • Detect trends in higher and lower diversity populations in company groups. Examine, for example, a manager’s attitude, emails, employee performance reviews, hiring decisions, job postings, etc.
  • Look at departments that are friendlier or more exclusionary to varied groups.
  • Evaluate homogeneity -- are people hiring similar people? Are males primarily hiring other males when better qualified candidates exist? Are women primarily hiring other women when better qualified candidates exist? And if so, is there genuine risk or balance across the enterprise?
  • Go beyond reporting on the state of diversity to develop trends that not only forecast shortfalls but begin to determine areas of risk -- and then course correct before problems arise.
  • Also detect for potential HR issue based on collected and analyzed behaviors in the company, preventing lawsuits.

Misclassification Risk

Employment misclassification risks remain huge undertakings for compliance managers. Unfortunately, issues are generally noticed after the problem has happened, so every resolution becomes a reactive crisis response. What if that could change through the type of x-ray platform we’re envisioning?

  • The system studies the actual work being performed by different classifications of employees to see if the roles match the duties. Are SOW workers actually performing the work of temps? Are exempt workers being classified as such to avoid OT and DT payments, based on intentional misclassifications in status?
  • What is the likelihood of misclassification based on a manager’s history of hiring, placements, assignment of duties, etc.?
  • Perhaps the x-ray system could compare possible misclassification to financial stressors from the board or executives, who could be applying pressure to curb costs that come from higher benefits, workers comp, statutory burdens, OT, and more.
  • Are unpaid internships being used properly?
  • Are freelancers actually falling under the control of the company? The risk here is no different to the IRS than when a corporation treats independent contractors as employees.

Co-employment Risk

In an outsourced workforce solution, or enterprise-wide contingent labor program, co-employment risks can lurk around every corner. For the most part, assessing and monitoring the situation requires manual observation.

At its core, co-employment defines the practice of sharing employer responsibilities between the client, the staffing agency and the managed services provider (where an MSP/VMS program is in place). Simple as it sounds, it’s a risky business. Where more than one company maintains control over particular aspects of an employee’s work, careful attention must be paid to legal responsibilities pertaining to the joint management of that talent. Typical examples include clients and staffing suppliers sharing the duties of supervising the day-to-day work of the employee, supplying equipment and materials, providing workspace, making disciplinary and promotional decisions, conducting performance evaluations, offering training, establishing wage rates, paying salaries and more. Companies that frequently rely on the use of indirect labor are among the most common to be exposed to co-employment scenarios and their inherent risks.

But as with employment misclassification risks, co-employment problems (more often than not) are found after the fact. Again, I believe our x-ray machine could warn of risk in advance by continually watching the interactions between organizations and their contingent workers -- then learning to identify potential obstacles. Some items the algorithms could use as triggers include the following.

  • Inclusion in employee training
  • Pay and rate negotiations by client managers
  • Performance coaching or counseling by client managers
  • Time off and vacation negotiations by client managers
  • Inclusion in functions reserved for client employees
  • Allowed use of client employee facilities
  • Issuance of business cards or name plates by the client
  • Handling of promotional or disciplinary actions by client managers
  • Career opportunities presented by client managers
  • Assignments terminated or ended by client managers directly
  • Inclusion in client benefit programs or related discussions

A 360-Degree View of Technology

The ideals inherent in BlackRock’s Aladdin are fascinating. Obviously, the staffing industry isn’t going to buy this financial platform and hope it will detect all the risks we’ve just discussed. But it’s important that we look at solutions taking root outside of our space, embrace their concepts, and find ways to apply them to our challenges -- many of which has lasted far too long. Throwing more modules on a VMS doesn’t seem sustainable. We need machines that can evolve and learn alongside us -- to help inform our decisions and build a proactive approach to problem solving. With a little creativity and vision, we can easily achieve those goals.

Sunil Bagai
Sunil Bagai
Sunil is a Silicon Valley thought leader, speaker, motivator, and the visionary behind the groundbreaking Crowdstaffing ecosystem. Blending vision, technology, and business skills, he is transforming the talent acquisition landscape and the very nature of work. Prior to launching Crowdstaffing, Sunil honed his skills and experience as a business leader for companies such as IBM, EMC, and Symantec. "We need to think exponentially to mindfully architect the future of humanity, civilization, and work. When we collaborate and work together, everyone prospers."
Post a comment

Related Posts

Ensure a Positive Candidate Experience When Hiring Contingent Talent Remotely

As digitization, coupled with the global pandemic, propels contingent hiring online and with more individ...
Crowdstaffing Mar 10, 2021 9:30:00 AM

How is COVID-19 Shifting the Hiring Trend from Local to Globally Distributed?

Due to the accelerating effects of COVID-19, Hiring Marketplaces are uniquely positioned to support new m...
Crowdstaffing Feb 17, 2021 2:13:34 PM

How Hiring Marketplaces Improve Cost Transparency

Benefit from a hiring marketplace’s optimal pricing strategy where you can adjust rates at each requisiti...
Crowdstaffing Jan 21, 2021 8:29:00 AM