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Solving The Advanced Analytics Talent Problem

Around the world, select urban areas dominate the advanced analytics talent pool. If your headquarters doesn’t happen to be in Silicon Valley, Beijing, or Bangalore, however, there’s hope.

In the age of big data and AI, building strong advanced analytics capabilities is a strategic imperative for companies. But advanced analytics talent is hard to find, even in the cities that have the most of it. For companies operating outside of the centers of tech gravity — university-fed cities like San Francisco and Beijing — filling machine-learning or analytics posts can be a challenge, but it’s one that forward-thinking companies are meeting with a mix of creative approaches.

Among U.S. technology workers, there’s a clear preference for jobs in cities with strong technology hubs and at companies with well-established track records in analytics. Recent Bain & Company research shows this tendency of advanced analytics talent to cluster in big cities is actually a global phenomenon. (See “Advanced Analytics Talent Clusters in Major Cities.”) In the U.S., 10% of the pool of advanced analytics talent sits in greater metropolitan New York City, and 14% is in the San Francisco Bay area. Similarly, more than a quarter of India’s advanced analytics talent pool is located in Bangalore, with another 13% in Delhi. And the concentration is even more pronounced in China, where two cities — Shanghai and Beijing — account for fully half of the country’s analytics talent.

So, what actions can organizations outside of these power centers take?

Create Dedicated Outposts Within Tech Hubs

One traditional approach is to establish dedicated centers of analytics excellence within these tech hubs. One large retailer, for example, has established labs in Silicon Valley and Bangalore, in addition to a team at headquarters that includes the company’s chief digital officer. Though talent is expensive in the hypercompetitive Bay Area, the company’s management has concluded it would be too difficult to build enough scale elsewhere, so their most sophisticated advanced analytics professionals, especially in data science, are located there. In Bangalore, a less-competitive and less-expensive market than Silicon Valley, the company taps into skilled local technologists. The analytics team at headquarters focuses on applying technology and building the company’s technology systems. In all three locations, business partners work alongside the technologists, coordinating with their counterparts in the other offices.

Advanced Analytics Talent Clusters in Major Cities

Advanced analytics professionals are most interested in working for companies with well-established track records in analytics. This contributes to the concentration of advanced analytics talent in major cities, a global phenomenon that’s especially pronounced in China and India.

Invest in Academic Centers

In addition to staking outposts in established hubs, companies, including large digital natives, increasingly go further afield, investing in emerging analytics centers to meet their growing needs. With some companies hiring thousands of data professionals, more and more universities are adding and expanding artificial intelligence and data-science programs today.

The most mature sectors for advanced analytics are the ones planning to expand their teams the fastest, and they are following the talent. Cities like Toronto, Montreal, Atlanta, and Pittsburgh have become important centers for Google, Facebook, Amazon, and Uber, based on the strengths of their university programs, and now smaller cities like Louisville, Kentucky, are beginning to enjoy a similar dynamic. Recently, Microsoft announced that Louisville — the home of the University of Louisville and a center for manufacturing and health care — would be the company’s new regional hub for artificial intelligence, data science, and work on the internet of things.

Expand Reach With a Hybrid Approach

Besides broadening their geographical reach, companies can also address hiring challenges by tapping into a tiered talent strategy that leverages the expertise of outside partners. In this structure, a core, in-house analytics team focuses on developing critical mass in strategic tasks such as data-science team leadership and model development. Offshore data hubs, third-party service firms, and crowdsourcing can then handle less-critical advanced analytics work like tactical data management and model maintenance.

Combining internal and external analytics capabilities, companies are creating a hybrid model that matches the breadth of advanced analytics expertise they’ll need in the future. Today, only 30% of companies handle all advanced analytics in-house. The other 70% augment their internal skills with some combination of offshore outsourcing, freelancers, advanced analytics consultants, and crowdsourcing.

Originally posted by Chris Brahm 

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