Potential Savings in the Public Sector from Effective Use of Big Data

Many in the American public have been captivated by the Obama campaign’s efforts to use big data analytics to close the fairly narrow gap between candidates in the 2012 election. By evaluating four key metrics, the campaign was able to identify key voters in swing states and allocated campaign resources (canvassers, phone bankers, email messages, etc.) where they were most critically needed.

Some have argued that the advantage given by this campaign was not as decisive as it is often claimed – with swing-state democratic voters beating repulican voter turnout by only 1.6 points. This statistic, however, has not diminished the interest in how big data analytics can affect campaigning – and by extension government. The lieutenant governor of California, Gavin Newsom, a proponent of a more data-driven, tech-centric public sector has stated that he wishes President Obama “governed as he campaigned.”

What benefits do governing with the aid of big data yield? A recent report from the McKinsey group has brought to light the future potential of big data to any class of organization in which innovation and efficiency is central to success. It leads off with the telling assertion that the governments of Europe “could save more than €100 billion ($149 billion) in operational efficiency improvements alone by using big data, not including using big data to reduce fraud and errors and boost the collection of tax revenues.”

McKinsey breaks down the value of big data in the public sector into the following categories:

  • Transparency
    One of the core components of public trust is ready availability of government-held data. This capability can also translate into efficiency. For instance, there is tremendous redundancy in the fact that government tax agencies store personal data that is duplicated all over the private sector. The Swedish Tax Agency offers services in pre-filling of forms with personal data in a manner that reduces processing times.
  • Discovery of Needs, Variability, and Performance
    The number of agencies, actors, and variables across government bodies is difficult to manage effectively against organizational missions. Data-driven performance engines can help boost efficiency by considerable margins.
  • Segmentation
    Segmentation is common in marketing and private sector customer interaction, but poses issues for government since it is regarded that services should be offered equally to all members of the public. However, the German Federal Labor Agency made effective use of segmentation in social assistance by using data to provide more targeted interventions for the unemployed.
  • Algorithms for Decision Making
    Though it will perhaps always be unnerving for some to think of the prospects of automated decision making, there are areas that easily warrant it such as detection of tax fraud in large sets of internal revenue data.
  • Innovating New Business Models
    Given the potential openness of public data, businesses can discover new markets that provide value with such data. For example, a startup called BrightScope used data from the US Department of Labor to determine that small businesses were paying far greater management fees for 401(k) plans than larger companies, leading it to develop an online 401(k) rating tool.

The prospects of using big data analytics to improve government are convincing, although it is concerning that there is a projected 1.5 million person shortfall in the near future of managers and analysts that are trained to provide skill and leadership in this realm. Hopefully, the public sector will strive to address this gap and meet the tremendous demand for big data skills, bringing success in the categories that the report above has outlined.

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