Do More With Analytics. Do Better With Labor Market Interventions.

Public employment services leaders want to help secure their country’s economic competitiveness today by closing the skills gap, and ensure preparedness for tomorrow by cultivating lifelong skills that can keep citizens sustainably employed and supporting employers with counseling services that help them fill middle-skills jobs. These are ambitious goals considering trends in US and Europe.

Labor market experts estimate five million US jobs will be unfilled in 2020 due to the skills gap1 and Europe expects a shortfall of 900,000 skilled information and communications technology workers by 2020.2 Additionally, 66 percent of public employment service officials surveyed across 11 countries believe they have only limited insight into future skill needs of companies.3

To address these issues and deliver public service for the future, public employment agencies are investing vast resources in labor market interventions centered on matching people with available jobs. However, agencies have little insight into whether these interventions are working. The answers may be right beneath their noses, buried in layers of data.

How to do better with labor market interventionsAgencies that mine their data using analytics can do better with their labor market interventions. To better understand the use of analytics among public employment agencies globally, Accenture surveyed employees at labor organizations around the world (in France, Germany, India, Ireland, Norway, Singapore, Sweden, the United Kingdom and the United States) to learn about how these agencies define and measure success, and how they use and perceive analytics in this context.4 The results revealed ample room for improvement. These are the most important ways in which they could do better.

1. Do more than have systems to measure success; successfully use those systems to pinpoint the best labor market interventions.

Labor organizations recognize indicators of success—they view increased job

Analytics Users

Measurement of outcomes of workforce development programs

Employee performance and development

Identify risk areas for unemployment or changing labor market conditions

Minimization of costs/ Maximization of resources

Relationship management

Labor market forecasting

Fraud detection and prevention

Customer segmentation

Supporting lifelong learning efforts

Other

Figure 1. More agencies are using analytics to measure outcomes, rather than plan for the future.

Source: Accenture Labor Organization Research 2015

placements and improved skills matches as key markers of success. And 80 percent have a system in place to measure program success, yet only 9 percent say that system is very effective.

More than half (54 percent) say they are lacking tools, training and resources to appropriately measure the success of labor market interventions. Interestingly, those in Europe are more likely than those in the US or Singapore to say their agencies do not have what they need to appropriately measure success.

By more proactively using analytics in a forward-looking way, agencies can tailor and improve labor market interventions. For example, the German Federal Employment Agency (Bundesagentur für Arbeit) set up the Labour Market Monitor (LMM) to help deal with the uncertainty over the future of employment. The aim was to create transparency over regional labor market dynamics, offer a space for dialogue over market activities, support strategic approaches to solve regional

unemployment, bring in partners and demonstrate expertise. Germany also created the Specialist Radar, a tool for skills shortage analysis. It allows for present estimations and medium-run forecasts. All the data can be manipulated and visualized for each individual user. It is a central tool that allows experts and employers to save time, money and share vital intelligence.5

2. Do more than measure current outcomes; plan for the future using predictive analytics.

The good news is that more than 8 in 10 (84 percent) public employment agencies say their organization uses analytics. But the unfortunate news is that while many are already using analytics to measure outcomes, few are applying it to more forward-looking planning (see Figure 1.)

Only 38 percent are using analytics to support lifelong learning efforts. Lifelong learning is a critical success factor to closing the skills gap. However, agencies

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61

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Gap between current and potential benefits

-17 -9-10 -6 -3

Potential benefit of greater use of analytics

Increasing speed of job placements

Increasing volume of job placements

Improving skill match of job placements

Detecting/ reducing fraud

Current benefit of analytics Potential benefit of greater use of analytics

1. J. Benitez; “Closing the skills gap with a talent supply chain;” September 2014; http://www.uschamberfoundation.org/closing-skills-gap-talent-supply-chain2. DigitalEurope; FACTS AND FIGURES; http://www.digitaleurope.org/Ourwork/BoostingDigitalGrowth/eSkillsinEurope/FactsandFigures.aspx3. Accenture Public Employment Officials Survey 20134. Accenture Labor Organization Research 20155. Accenture; “Delivering Employment Services for the Future: Rethinking the Role of the Public Employment Service”; 2013; http://www.accenture.com/SiteCollectionDocuments/PDF/Accenture-Delivering-Employment-Services-for-the-Future-Report.pdf6. Ohio Governor’s Office of Workforce Transformation; Jobs Forecasting; http://www.workforce.ohio.gov/JobsForecasting.aspx

Figure 2. The gap between current benefits and full analytics potential.

Source: Accenture Labor Organization Research 2015

(81 percent) are more focused on using analytics to measure the success of programs that link job seekers and potential employers. Only 44 percent are measuring the impact of programs that shape the curriculum of education/training the needs of employers and job seekers.

If public employment agencies look to the future and use predictive analytics, they can identify how the labor market will evolve, what skills are in demand and what programs can best support lifelong learning. These insights equip agencies to solve unemployment challenges.

The Singapore Workforce Development Agency has a vision to build a skilled, competitive workforce that includes lifelong learners. They are investing in the foundation of analytics to one day support data-driven lifelong learning approaches for citizens.

3. Do more than settle for basic benefits from analytics; achieve your full analytics potential.

Current use of analytics is benefitting some key areas, but significant gaps exist between current benefits and full analytics potential (see Figure 2). This gap is even wider among countries in Europe.

So what’s stopping these countries from achieving full analytics benefits? Lack of sufficient resources is a major inhibitor. A majority (80 percent) say use of analytics would help the agency/department improve outcomes of its labor market interventions/ programs, but they don’t have the right resources to do so:

• 78 percent need more employees skilled in analytics

• 68 percent need better data

• 61 percent need better technology

Agencies can close the gap between current benefits and potential benefits by developing the right capabilities (analytics talent and technology solutions). For example, the Governor’s Office of Workforce Transformation in Ohio deployed a statewide jobs forecasting tool that allows top businesses to share their most critical job needs in the next year, three years and five years. The data gathered through the forecast tool is aggregated and combined with existing historical job data to better align the in-demand jobs with the education and training providers and Ohio’s workforce development system.6

Taking action with analyticsLabor market challenges won’t be solved overnight, but analytics can quickly reveal what is working—and what isn’t—so public employment agencies can redirect resources to the most valuable labor market interventions.

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For more information contact:Rainer BinderGlobal Employment LeadAccenture Health & Public Servicerainer.binder@accenture.com

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