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With the supply of talent growing fast, make the most of opportunities inside and outside your company. By Chris Brahm, Arpan Sheth, Velu Sinha and Jessica DaiSolving the New Equation for Advanced Analytics Talent Chris Brahm is a Bain & Company partner in San Francisco and leads the firm’s Global Advanced Analytics practice. Arpan Sheth is a Bain partner based in the Bangalore office and leads the firm’s Information Technology practice in Asia-Pacific. Velu Sinha is a Bain partner in Shanghai, and Jessica Dai is a principal based in San Francisco. Copyright © 2019 Bain & Company, Inc. All rights reserved. 11 Inthexwoyxayrxs,glwt hxb uxpfnlhdyfxphlIvwtdcxilIyhwxAt a Glance In the next two years, the global supply of advanced analytics talent will double, with India’s talent pool growing especially quickly. In the US, talent shortages will persist for experienced hires and certain key jobs, like data engineers and architects. Companies will struggle to hire experts away from the analytically mature sectors that are the most attractive to employees and that themselves plan to expand quickly. A successful tiered talent strategy incorporates new hires and internal retraining, while also tapping data hubs, third-party service firms and crowdsourcing. Innovation in analytics is a priority for almost every organization today. Yet bottlenecks in the key areas of talent, data and analytics strategy often block progress. In order to better understand the talent bottleneck and how to release it, Bain & Company assessed the global market for analytics talent—both supply and demand—interviewing practitioners and experts, reviewing job boards and profes-sional community listings, and studying educational program statistics.We found a workforce on the verge of dramatic change. For years, companies have been stuck chasing either a limited supply of experienced professionals or new university graduates. Today, however, the global supply of advanced analytics talent is about to explode. By 2020, the advanced analytics talent pool is expected to reach 1 million people, up from half a million in 2018. The growth in advanced analytics talent arises from a pivot in traditional and nontraditional educa-tion so rapid that it’s hard to find a historical precedent. The best comparison may be the 1990s, when India invested heavily in training programmers, especially in legacy systems, ahead of Y2K sys-tems upgrades. That was when the subcontinent became the outsourcing giant it remains today. Once again, India is taking the lead, but this time through a combination of retraining and a flood of graduates with advanced degrees in subjects suited to advanced analytics work, like computer science and data science. By the end of 2020, Bain estimates that India will have three times as many candi- 21 Inthexwoyxayrxs,glwt hxb uxpfnlhdyfxphlIvwtdcxilIyhwxdates for advanced analytics work as it did in 2018, expanding from 65,000 people to more than 200,000 in just two years. The analytics talent supply will climb in China, Western Europe and North America as well, but not quite as quickly. This ramp-up, however, won’t entirely solve the advanced analytics talent challenge. Many countries will still have fewer analytics experts than needed. Most available advanced analytics talent has re-cently graduated, but people with greater tenure, who are needed to lead and manage these teams, are in short supply. The United States will suffer shortages in certain critical roles, like data engi-neers and architects, while facing a possible oversupply of data scientists.Additional long-term demand will come from sectors like retail, media, consumer goods, and industrial goods and services, as companies apply analytics capabilities to their businesses. According to Bain’s research, among banks today, slightly more than 1% of white-collar employees work in advanced ana-lytics, on average. By contrast, technology companies average nearly 3% of staff aligned with advanced analytics, and the most analytically advanced digital native companies have 10% (see Figure 1). The business models differ greatly across these sectors, of course, but it’s clear that, in nearly every large enterprise, the analytic intensity of the employee base is increasing.Figure 1: In order to compete, all US sectors will need to increase staff aligned with advanced analyticsAverage share of AA-aligned full-time employees, 2018 3.6%10%Digitalnatives2.9%Technology2.2%Insurance1.1%Banking2.2%Telecom1.6%Healthcare1.4%Industrialgoods andservices1.1%1.1%Media0.6%RetailLevels of AA talent vary amongindividual companies, reaching ashigh as 10% for digital nativesNotes: Share of employees calculated as a percentage of total white-collar US FTEs; average calculated based on a sample of companies in each industrySources: LinkedIn; S&P Capital IQ; company websites; company annual reportsConsumergoods 31 Inthexwoyxayrxs,glwt hxb uxpfnlhdyfxphlIvwtdcxilIyhwxBuilding an advanced analytics te