关注人才紧缺问题把握中国分析领域发展机遇（英文）.docx

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1、BAIN & COMPANY Solving the New Equation forAdvanced Analytics TalentWith the supply of talent growing fast, make the most of opportunities inside and outside your company.By Chris Brahm, Arpan Sheth, Velu Sinha andJessica DaiShared Ambition, True ResultsBain & Company is the management consulting fi

2、rm that the worlds business leaders come to when they want results.Bain advises clients on strategy, operations, technology, organization, private equity and mergers and acquisitions. We develop practical, customized insights that clients act on and transfer skills that make change stick. Founded in

3、 1973, Bain has 57 offices in 36 countries, and our deep expertise and client roster cross every industry and economic sector. Our clients have outperformed the stock market 4 to 1.What sets us apartWe believe a consulting firm should be more than an adviser. So we put ourselves in our clients, shoe

4、s, sellingoutcomes, not projects. Wealign our incentives with our clientsJ by linkingour fees to their results and collaborate to unlock the full potential of their business. Our Results DeliveiyR process builds our clients , capabilities, and our True North values mean we do the right thing fbr our

5、 clients, people and communitiesalways.For more information, visit Amsterdam Atlanta Bangkok Beijing Bengaluru Berlin Boston Brussels Buenos Aires Chicago Copenhagen Dallas Doha Dubai Dusseldorf Frankfurt Helsinki Hong Kong Houston Istanbul Jakarta Johannesburg Kuala Lumpur Kyiv Lgos London Los Ange

6、les Madrid Melbourne Mexico City Milan Moscow Mumbai Munich New Delhi New York Oslo Palo Alto Paris Perth Rio de Janeiro Riyadh Rome San Francisco Santiago SAo Paulo Seattle Seoul Shanghai Singapore Stockholm Sydney Tokyo Toronto Warsaw Washington. DC ZurichChris Brahm is a Bain & Company partner in

7、 San Francisco and leads the firms Global Advanced Analytics practice. Arpan Sheth is a Bain partner based in the Bangalore office and leads the firms Information Technology practice in Asia-Pacific. Velu Sinha isa Bain partner in Shanghai, and Jessica Dai is a principal based in San Francisco.Copyr

8、ight 2019 Bain & Company, Inc. All rights reserved.At a GlanceIn the next two years, the global supply of advanced analytics talent will double, with Indias talent pool growing especially quickly. In the US, talent shortages will persist for experienced hires and certain key jobs, like data engineer

9、s 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,

10、third-party service firms and crowdsourcing.Innovation in analytics is a priority fbralmosteveryorganization today. Yetbottlenecks inthe 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 as

11、sessed the global market for analytics talent一 both supply and demandinterviewing practitioners and experts, re vie wing job boards and professional community listings, and studying educational program statistics.We found a workforce on the verge of dramatic change.For years, companies have been stu

12、ck 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 growt

13、h in advanced analytics talent arises from a pivot in traditional and nontraditional education so rapid that ifs 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 systems upgrades

14、. 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.

15、 By the end of 2020, Bain estimates that India will have three times as many candidates 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 n

16、ot quite as quickly.This ramp-up, however, wont entirely solve the advanced analytics talent challenge. Many countries will still have fewer analytics experts than needed. Most available advanced analytics talent has recently graduated, but people with greater tenure, who are needed to lead and mana

17、ge these teams, are in short supply. The United States will suffer shortages in certain critical roles, like data engineers 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 good

18、s and services, as companies apply analytics capabilities to theirbusinesses. According to Bains research, among banks today, slightly more than 1 % ofwhite-collar employees work in advanced analytics, on average. By contrast, technology companies average nearly 3% of staff aligned with advanced ana

19、lytics, and the most analytically advanced digital native companies have 10% (see Figure 1). The business models differ greatly across these sectors, of course, but ifs clear that, in nearly every large enterprise, the analytic intensity of the employee base is increasing.Figure 1： In order to compe

20、te, all US sectors will need to increase staff aligned with advanced analyticsAverage share of AA-aligned full-time employees, 2018Notes： Share of employees calculated as a percentage of total white-collar US FTEs; average calculated based on a sample of companies in each industry Sources: Linkedln;

21、 S&P Capttal IQ： company websites: company annual reportsFigure 2： An effective advanced analytics talent pool includes eight key rolesThese four roles make up more than 70% of any given advanced analytics team across US industriesData engineerAggregates, integrates and summarizes large data sets co

22、mbining structured and unstructured informationMachine learningengineerDevelops scalable tools and technologies specifically for machine learning use casesoData architectCore data architect: Decides and executes data architecture strategy; oversees data management tasksData scientistEngages in explo

23、ratory analysis to understand trends that will create value for the business: generates analytical approaches and modelsDatabase administrator:Manages data infrastructure day to dayUse case product managerOversees execution of advanced analytics use cases from development through productionUse case

24、product managerOversees execution of advanced analytics use cases from development through productionData analystPrepares dashboards for internal and external communicationDevOps engineerSupports continuous deployment of use cases into scalable production environment, automating processes where poss

25、ible(BUI developerCompletes process by translating algorithms into tools, reports and other automated solutionsSources： The Business-Higher Education Forum, *The Quant Crunch, 2017; International Institute for Analytics; Linkedln search; industry interviews; Bain AA Talent Survey (n=226)Building an

26、advanced analytics teamCompanies should not expect to fill this gap entirely by wooing experienced talent from other employers. The most analytically mature sectors plan to expand their teams fastest, and employees are most interested in working fbr companies with well-established track records in a

27、nalytics, our recent survey of more than 200 industry participants found.Creative, flexible approaches fbr expanding the talent base include building centers of excellence fbr poolsofhired analytics experts, andalsoretrainingcapableexistingemployees and givingthemaccess to automation tools. Importan

28、tty, rather than trying to do everything in-house, a tiered talent strategy should focus a core, in-house analytics team on strategic tasks while tapping offshore data hubs, third-party service firms and crowdsourcing for other work. Even the most sophisticated companies leverage a combination ofint

29、ernal and external supply chains for analytics capabilities.What is the optimal blend of advanced analytics roles? How are teams best configured? The exact balance varies depending on the sector and maturity of a companys analytics practice, but teams will draw from eight key roles (see Figure 2). W

30、ith companies hiring to create balanced advanced analytics teams, certain skills are in higher demand.Figure 3： Global advanced analytics talent is expected to double by 2020Current and projected advanced analytics talent in four regions20202018WesternA mixed global 盟田睨k-170,000-125,000Small to medi

31、um gap expectedChina-190,000-75,000Medium to large gap expectedexpanding the talent pb即 ams of study emphasizepowers are catchiTheoMW 那么 s pool. Mrs!TThe growth in advanced analytics-trained talent will occur primarily outside the US (see Figure 3). Long the largest market for analytics talent, the

32、US will retain that top spot, but other global techFIR触 ia, wherelhtne雅女抑 graduate degree Holders data招踊圈港联需器稠瞬戊toJoin屈w的网6注加榴限蝴 Augmenting that is Indias曲序曲讪部的电旃电击 information technology, especially in programming and systemsNote: Advanced analytics talent refers to data architects, data scientists

33、, data engineers and machine learning engineersSources: Linkedln： National Center for Education Statistics; UNESCO; International Institute for Analytics; Council on Integrity in Results Reporting; India Ministry of Human Resource Development; China Ministry of Education; Edison Project; Bain AA Tal

34、ent Survey (n=226): industry participant interviews integration. Outsourcing firms and the India IT centers of global corporations house many ideal candidates for learning new advanced analytics skills. These two sources have combined to make India a vital hub of analytics expertise and have fueled

35、the growth of its analytics outsourcing industry.The future is less clear fbr China. Thanks to its relatively supportive regulatory environment and access to consumer data, China is often described as winning the race to dominate artificial intelligence and advanced analytics. But on advanced analyt

36、ics talent, the country may need to accelerate. Recent trends point to a growing focus on talent in China, including a significant expansion in data sciencebachelors degree programs and high levels ofUS recruiting and pay among Chinese digital natives and technology companies. Without an expansion i

37、n supply, talentcould become a bottleneck, slowing analytics progress in China, especially for companies in traditional sectors.Breaking the talent bottleneckThe historical shortage of analytics talent has caused many organizations to rely on a combination of internal and external advanced analytics

38、 expertise. This hybrid model also turns out to be a good match for the breadth of advanced analytics expertise needed in the future. A multilayered approach will continue to make more sense than full vertical integration for many companies. When possible, companies should develop critical mass inte

39、rnally in the most important aspects of advanced analytics, such as data-science team leadership and model development, and tap the external supplychain forless- critical skills, like tactical data management and model maintenance. Today, only 30% of companies are fully integrated in advanced analyt

40、ics. The other 70% augment their internal skills with some combination of offshore outsourcing, freelancers, advanced analytics consultants and crowdsourcing.Part of developing this talent ecosystem involves harnessing shadow analytics talent-that is, taking people currently walking the halls and he

41、lping them develop new analytical skills. Existing employees already know the company, the industry and how to operate effectively across the organization.Part of developingthis talent ecosystem involves harnessing shadowanalytics talentthatis, taking people currentlywalking the halls and helping th

42、em develop new analytical skills. Existing employees already know the company, the industry and how to operate effectively across the organization. Many have the quantitative background to learn analytical skills, and nearly a quarter ofBain survey respondents report that their companies have implem

43、ented advanced analytics training programs.IBMs Data Scientist Academy, for example, is an eight-day boot camp followed by individual online learning, and includes shadowing IBM data scientists and a capstone project. Airbnbs Data University offers more than 30 classes in data awareness, collection,

44、 visualization and data at scale, and more than 500 employees (1 out of every 8) took part during the universit/s first six months. Other training options include free MOOCs-massive open online coursesand paid retraining programs.Some companies with a good data science workbench and the right set of

45、 data engineering tools also use advanced analytics automation to enable people without strongcoding skills to build models and engineer data. Of survey respondents currently using technologies to automate advanced analytics tasks, more than half say these technologies enable existing staff to be ra

46、pidly trained to take on responsibilities of a data scientist or data engineer.Fostering the talent ecosystemEmbracing this tiered approach will help companies today and in the future. It allows them to tap into the rapidly growing global talent supply and to create a more flexible model, all while leaving room to redeploy existing talent in new and creative ways. Companies cannot afford to let a bottleneck in analytics talent slow them down, and they dont have to.