Moneyball: How predictive analytics accelerates business engagement for Workforce Development Boards
– by Danny Patterson
As the baseball season kicks off, I realize that WDBs can learn a lot from baseball and their Moneyball approach. Let me explain.
In the old days of baseball, scouts focused on the usual statistics—batting average, RBIs, stolen bases, and their utility in the field. That all changed with the Moneyball approach made famous by the Oakland A’s and their general manager Billy Beane in 2002.
The premise behind the Moneyball theory is still player analytics. But it only considers two key data points – a player’s batting average and their on-base percentage – as predictors of their true potential for winning baseball games. Essentially, Can a player hit to get on base and create runs? After losing some star players, Beane’s team-building approach changed the whole game, led to a 20-game winning streak (2nd longest in the modern era), and clinched the American League West playoffs. Today, most teams leverage predictive analytics in the same way to fuel their winning strategies.
So, what can WDBs learn from this? We know analyzing data is nothing new to WDBs. They still look to answer these fundamental questions – Who is looking for a job? Who is hiring? Is there a skills match? However, it is a game-changer for those who leverage the power of predictive analytics for accelerating business engagement. Surprisingly, however, WDBs often do not understand the importance of or do not have the data to identify healthy and growing businesses in the hiring equation. Business health is as vital to job quality as an on-base percentage is to scoring runs. Both are winning formulas.
Adopting predictive analytics requires a mind shift that leads to improved performance. By using three simple strategies, WDBs/OneStop Operators can:
As in baseball, a team needs the ability to predict a player’s batting average. Target the ball with greater precision and speed for a higher on-base percentage. And succeed by making the most runs to win the game.
In the movie, Beane calculated correctly that a catcher with good predictive scores could be a great first baseman long before the player realized his potential. Also, in that position, the player would help the team add to the win column. I recognize the same hesitancy for WDBs, who have been doing great work for years, but often do not realize the potential for even greater success can be achieved through actionable, predictive business insights. All sports enthusiasts know an excellent regular season is not the final goal but a first step into the pennant races and towards a place in the World Series. That’s the goal! The only way to get there is to play championship-level baseball all year. Similarly, the negotiated performance goals are not the ceiling but the floor for WDBs. This shift requires the use of Moneyball strategies.
Today, WDBs rely on BLS Data for strategic planning. The Quarterly Census of Employment and Wages (or QCEW) is insightful for sector breakdown by NAICS codes and salaries. Still, it is aggregated Employer Data and is not available at the business address level for targeted outreach.
WARN Notices are also available through the states’ Employment Security Agency and are address-based. But WARNs are only filed by companies with over 50 employees. Did you know that it accounts for only 2% of all businesses and predominantly spans just three sectors: manufacturing, healthcare, and the public sector? Moreover, only a tiny fraction of these businesses ever submits WARN notices. As a result, poor company health is only evident because of the layoffs or closures.
Online job sites, another employer-based data source used by WDBs or OneStop Operators, represent a fraction of companies hiring in the community as it is a voluntary and self-selected source. The number of jobs they post is no way of calculating a company’s financial well-being.
First and foremost is the ability to drill down from the sector level to the business address level. Secondly, understanding a company’s financial health and where they are in the business cycle is integral to accelerating successful business engagement strategies.
The Moneyball approach is in full effect once a WDB understands the current and future state of an employer’s financial health. For example, there is immense value in understanding who is expanding, stable, contracting, or at risk of failure – before targeted business outreach.
Business expansion, contraction, and failure risk are three health measures derived from performance and data signals to predict a business’ change in financial position.
WDBs across the U.S. deploy various outreach strategies – and require predictive insights to pinpoint your targeted list. Some comprehensive address-based databases capture all the 17.5 million businesses in the U.S., but not all come with any means of filtering through the millions of records.
Filtering by size alone is not enough. Did you know small businesses with 50 or fewer employees represent 98% of all the businesses? Conversely, searching by job postings, which are self-selected businesses participating in that forum, represent a small sample of the companies in your community. Neither of these methods is a performance-based approach and does not include any meaningful insights.
A multi-layered, flexible filtering system can overlay critical search criteria such as location, sector, size, risk, growth, and diversity. This level of insight enables rapid analysis and decision-making in seconds. More importantly, you can target the right business and contact with the right message for a more successful outcome. Imagine how your batting average and on-base percentage will improve if you know the pitcher’s condition. Consider the runs scored if you understand the company’s financial condition and who to contact before your first call. Imagine if you know who is:
Understanding business dynamics is essential to accelerate business engagement. I’m confident that tracking business conditions within your priority sectors are equally, if not more important than knowing what those priority sectors are. For example, if the manufacturing industry is growing, does it mean all businesses within that sector are? No, it doesn’t! Therefore, knowing which companies are driving the growth and who are not will help you play at a championship level all season long. We know job placements in healthy companies increase the potential for future successful engagements, improve wages, increase retention, and a greater possibility of the employee entering a career pathway.
Using the Moneyball analogy, predictive data enables you to look across the league (state, region, local area, and all sectors) as well as show who is growing and the opportunities for engagement strategies. Just like baseball, you can set a winning game plan for each.
Access to a comprehensive business database and predictive, forward-looking indicators results in rapid analysis and action within seconds. Specifically, predictive analytics enables:
As a WDB, you always want more job seekers to get on base and score. Or, in layman’s terms, get and keep a quality job. Predictive analytics can improve what you’re doing already by helping you be more efficient and effective, yielding more significant outcomes.
How do WDBs measure success? Here are just a few examples:
Bottom line, WDBs are the designated hitters for meeting business needs.
Predicting a company’s financial condition accelerates business engagement. As a result, there are more quality job placements and improved outcomes across the system. That’s playing championship baseball year-round – for the WDB, the job seekers, and the businesses within the community.
PHOTO CREDIT: "Ball Impact. UNF Baseball vs. Florida Gulf Coast University" by DeusXFlorida is marked with CC BY 2.0