Can We Predict Layoffs by Understanding Business Risk?

How better data lowers unemployment

Given the high costs and adverse impacts of unemployment on society, state and local governments strive to prevent layoffs and, when they do occur, to get affected people re-employed as quickly as possible. But they struggle at this because they lack actionable data with which to develop proactive strategies and tactics that prevent layoffs and get unemployed people back to work.

You can take those workers at the distressed company, and, rather than saying, ‘Here's how you sign up for unemployment,’ you can transition them to another company that’s expanding.
Bill Greene, Senior Solutions Advisor, Dun & Bradstreet

To assess their business landscapes and labor markets, state and local governments often rely on Labor Market Information (LMI), which is summary data based on months-old business activity and, consequently, not actionable for government planners. LMI data cannot be sliced and diced at the individual company level, so government workforce and labor agencies cannot identify specific businesses within their jurisdictions that are in distress until it is too late. Conversely, governments cannot identify businesses that are growing to better understand what skills are needed so job training and job placement services can be calibrated more effectively. In fact, state and local governments today typically do not know what businesses are operating in their communities and what their circumstances are, except for the very largest employers.


Reacting to layoffs vs. preventing layoffs 

The result is that governments usually discover a company is in distress only after it issues a so-called WARN notice. WARN refers to the Worker Adjustment and Retraining Notification Act of 1988, which requires employers to provide a 60-calendar-day advance notice of a plant closing or mass layoff. By the time a company issues a WARN notice, it is usually too late to prevent the layoffs.

This means that state and local governments tend to be reactive, says Bill Greene, a strategic solutions advisor at Dun & Bradstreet. They spend most of their time responding to WARN notices, trying to place recently unemployed or soon-to-be-unemployed people into new jobs as fast as possible with little company-specific information to guide them. They lack actionable, “big picture” intelligence to proactively get ahead of layoffs so they can be prevented.

Shifting from reactive to proactive approaches to stem job losses

One U.S. state is taking a different approach. The state’s Workforce Development Board recently started using more refined and robust labor market and business data from Dun & Bradstreet that informs planners in great detail which specific businesses are growing, which are stable, and which are showing signs of distress — in real time. Because the data is current and specific, it is highly actionable and has completely changed how that state approaches the mission of workforce development.

With this data, the state’s workforce development planners can efficiently target companies where they can be most effective. For example, the data provides a Financial Stress Score for every business. The score is based on a myriad of performance data points that are continuously updated for each company, reflecting things such as the size of a company’s debt load; its on-time performance in paying suppliers, utilities, and bank loans. Dun & Bradstreet’s Financial Stress Score is stratified into three categories: Low Risk, signifying the company is financially strong and unlikely to fail; High Risk, meaning it falls in the bottom 1 percent of businesses and appears to face imminent failure; and Medium Risk, which constitutes roughly 30 percent of all U.S. businesses and makes up 65 percent of all business failures. It is this Medium Risk category of companies that, when targeted for intervention by state and local governments, presents the greatest potential for layoff aversion.  

With such information, the state — working in collaboration with local workforce development boards — has been far more proactive in stemming layoffs and placing people needing jobs. Many local government workforce boards target companies that have a financial stress score of Medium and then approach them to find out what is happening with their businesses and whether they may be in need of government assistance to help them stabilize or grow their businesses.

Getting better results from data-driven, proactive approaches

By finding and reaching out to struggling companies many months or years before they have to resort to layoffs or closure, state and local governments can provide assistance to stabilize and grow those companies. This assistance can include employee training, access to capital, access to consultants to help them adopt lean manufacturing processes or just-in-time inventory methods, and access to additional markets, among many other things.

The aforementioned state has developed a reporting process in which jobs that are saved through this approach are verified by the employer, tallied up, and then multiplied by the cost of an average unemployment insurance claim to calculate a return on investment. Last year, the state documented more than 6,000 jobs saved with most of those attributed to proactive engagement approaches. The state estimates that each job saved translates into $3,500 in annual savings to the state’s unemployment insurance fund, or a total savings of roughly $21 million.

In cases where layoffs are unavoidable, the state uses the Dun & Bradstreet data to find other companies in the same industry sector that have a Low Risk financial stress score that, for example, are growing and need more skilled workers. “Then you can take those workers at the distressed company, and, rather than saying, ‘Here's how you sign up for unemployment,’ you can transition them to another company that’s expanding,” Greene said.

In other words, with better data, state and local governments can finally put more focus on proactively preventing layoffs and expanding their labor markets instead of simply reacting to each layoff as it happens.