Last year, McKinsey came out with a report that continues to reverberate around computer science and data analytics circles, predicting shortages of 140,000 to 190,000 data analysts in the US by 2018, along with falling short another 1.5 million managers and analysts who can understand and use big data to make informed decisions. Businesses as well as governments have latched on to big data to increase efficiency and customer and/or citizen satisfaction, so demand for employees has exploded. How can the public sector, particularly lower-level governments, keep up? In this series of articles we’re discussing this mounting issue, exploring currently successful approaches and looking into the future.
With limited fiscal resources compared to the private sector, governments will have to attract talent with much shallower pockets. This is especially true at the state and city level, where more limited resources put more constraints on the compensation that can be offered. The public sector is at a substantial disadvantage against the tech companies and multinationals also seeking to capture skilled workers.
A first question to address is whether or not lower levels of government should even attempt to add trained data scientists to their payrolls. On one hand, data analytics is only becoming more useful and crucial to good government, particularly versatile and influential on the local and city level. However, prohibitively high salaries usually rule this out, cutting into city revenues in a way that outweighs the benefits of a staff data-analyst.
A number of strategies can be used to clear this hurdle. Citizen programmers can be engaged through periodic civic coding contests and open data resources. While there may be some revolving-door issues, tech companies can be approached to allow their employees to bill volunteer hours to city agencies and donate their skills, or loan programmers for longer periods of time as fellows. Lastly, a public-private partnership can bring in the expertise of an outside entity to set-up, train, and manage a data analytics center, to be staffed by public employees.
Key here is realizing the power of pro-social motivation, rather than monetary compensation, in mobilizing data and computer scientists. Long a mainstay in government and non-profit management theory and practice, pro-social motivation brings workers to these professions despite often dramatically lower salaries than the private sector. The pro-socially motivated worker sees themselves as altruistic, and seeks to devote their time and attention to the good of their communities, hoping for a respectable salary but more so appreciation in compensation. Understanding that monetary compensation is often playing second fiddle to altruism has allowed for improved public-sector management: in recruiting government workers, and retaining and motivating them in order to get the most out of the workforce.
Many levels of government have taken advantage of pro-social motivation to attract often young, urban-minded computer scientists to use data analytics to solve problems while requiring minimal budgetary resources. Code for America offers a year-long fellowship with a living-wage stipend and benefits that programmers compete for even though they could earn dramatically more in the private sector. As the website informs applicants, they are also applying for a “chance to be a hero”. New York City’s BigApps Competition drew nearly 100 competitive entries despite offering only $50,000 spread across 11 prizes. Contests not only allow cities to save money by offering high praise in place of high salaries, but to garner more innovative responses than what would be generated in-house alone, as shown by the results of dozens of problem-solving contests hosted by the federal government on challenge.gov. Companies like IBM and Delloitte allow their employees to donate volunteer hours to lend their technical assistance to good causes.
With the understanding that pro-social motivation is playing such a crucial role in attracting programmers to code for the public sector, governments should work to reinforce these tendencies. Improved results or better talent are unlikely to be brought about by increasing the dollar amounts of prizes, however workers and volunteers can be otherwise motivated to deliver more. Direct contact with and acknowledgement by beneficiaries have had proven effects on the efficiency and quality of work produced by pro-socially motivated employees. Increasing this kind of contact between coders and citizens could have the same positive effect while costing very little. Regular, verbal reinforcement from government and community leaders – as peers rather than superiors – could help bring about and maintain high levels of productivity and innovation.
As data analytics becomes more integral to good government, alternatives to traditional staffing such as coding contests, fellowships, and volunteer hours may continue to be the best-choice solution. It will be important, however, to keep in mind the perspectives from which these engaged programmers are working. Understanding their pro-social motivation and what kinds of management can reinforce, reduce, or remain neutral to this phenomenon will be crucial to guaranteeing this sustainable stream of low-cost innovation.