Disruptive technologies will prove instrumental to effectively dealing with emerging government challe
Sebastian Lagana
SEP 12, 2014 00:46 AM
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TBR perspective

The 2014 Public Sector for the Future Summit, developed by Leadership for a Networked World and hosted by the Technology and Entrepreneurship Center at Harvard University in collaboration with Accenture, marked a shift from previous years in which the key topic addressed creating efficiencies using shared services. While shared services remain an important component of government efficiency, many practitioners have moved beyond the conceptual and early integration stage, generating successful cost-saving outcomes in their respective organizations and confirming the efficacy of shared services to government agencies. Given this context, summit leaders set out to broaden the discussion beyond the consolidation and streamlining of existing functions, focusing on innovations and evolving organizational models for delivering public service and disruptive technologies that are enabling agencies to shift from reactive to prescriptive operating models at a lower cost. 

While economic and budgetary conditions have generally improved in 2014, agencies remain encumbered by a trinity of converging factors:

1.      An aging population has increased demand for social services.

2.      The budgetary climate demands better service for the same or less money.

3.      Newly involved decision makers need to address budget constraints with demand for services improvement through technology transformation.

The conference topics revolved around how to take advantage of cross-organizational collaboration and disruptive technologies such as predictive analytics to improve government services delivery through more efficient and innovative IT technology enablement. Reflecting its association with this annual gathering, Accenture is among the private sector leaders helping government agencies leverage analytics to track and drive program outcomes more cost-effectively. Accenture has been analyzing and working with public sector organizations on structural shifts agencies have been making to address resource constraints and improve program outcomes through advances toward personalized services, insight-driven operations, public entrepreneurship and cross-organizational approaches.

Increasing adoption of predictive analytics will drive improved outcomes while maintaining agencies' cost structures

Technology has traditionally been leveraged in the public sector for two purposes: to complete back-office tasks designed to manage a given agency's internal operations and to capture legacy key performance indicators (KPIs) to gauge the success of various agencies and programs based on an input/output method of ROI analysis. While these are effective tools to inform decision makers of what has taken place, traditionally used single-variant data inherently limits the amount of actionable insight that can be gained to enhance service provision. Increasing the use of multivariant data from across agencies will improve program outcomes; however, government leaders must remain cognizant that there will be a significant learning curve associated with the ramp up of new methodologies as well as adapting to new decision-making frameworks and evolving approaches to the way work gets done. Numerous challenges to full adoption remain, but many will be relatively simple, capable of being solved through patience and a realistic understanding of the immediately visible impacts of these programs beyond the framework of legacy performance measurement metrics.

This was best laid out in an example centered on the deployment of firemen to inspect potentially hazardous buildings. Through the use of analytics, a municipality was better able to identify buildings constructed in a time frame with more lax building standards, positioning the buildings at heightened risk for incidents. Although fire inspectors were able to better target their inspections, the analytics group realized a decline in related KPIs due to inspections taking longer, despite a higher success rate in identifying fire hazards in buildings. Instead of calling the project a failure, however, it was deemed that the legacy KPIs were no longer applicable given the improved outcomes, resulting in the creation of new KPIs based on information not previously available.

While a simple example, this illustrates the type of predictive model that will help agencies better anticipate, and plan for, shifts in service requirements based on multivariant data. As aging populations and other factors increase demands for social services, budget realities are straining agencies' abilities to deliver at increasing scale, while simultaneously maintaining, or in many cases reducing, spending levels. The ability to effectively use enterprise-level analytics to understand and plan for shifts in agency service requirements will increase efficiency and effectiveness of service delivery to citizens.

How can we drive cultural change to facilitate disruptive technology adoption? 

There are a broad range of cultural and operational hurdles to new technology adoption and utilization, however, many of which were voiced by summit participants. Concerns around cross-agency data governance, for example, are not easy to overcome but are manageable. Healthcare agencies have the additional complexity of legal and privacy requirements. Other hurdles, such as taking down inefficient government data silos or the desire to have, as one event panelist phrased it, the "late mover" advantage, should be structurally easier to resolve.

Summit participants had a broad range of solutions to overcoming cultural hurdles in the adoption of disruptive technologies. Some participants espoused the value of using legislation and policy to cement change in a given agency or state; although, this only works if those in positions to affect this change are interested in doing so and understand the learning curve involved. Others cited the value of simple proof-of-concept tests such as pilot programs using only publically available data, creating tangible evidence to dispel anecdotal resistance. Some cited success gaining agency-level consensus and pushing upward from there, which often helped gain the support of the administrative side and avoided the perception that the push was coming from the IT department.

Skill and fresher resource shortages also pose a unique challenge to the public sector. Individuals with disruptive technology skills command a premium in the private sector, while heavily structured government pay grades do not easily accommodate rapid compensation gains or salary repositioning for those with skills in high-demand areas such as analytics. While particularly notable as it relates to disruptive technologies such as analytics, it's worth mentioning this problem pervades the sector as a whole, with an aging workforce, termed by a presenter as the "silver tsunami," getting ready to retire without a sufficient number of candidates to backfill new openings. This was one of few problems for which the panelists and contributors had limited solutions, knowing that increasing public sector compensation would be very difficult. Instead, a reliance on the intrinsic value of civil service, a focus on new employee development and retention policies, and the reality government agencies also will need to continue to leverage analytics expertise from the private sector were the key tenets of assuaging the problem.

Skepticism about adopting disruptive technologies is an old story with a predictable ending

The oft-made comparison between analytics adoption in baseball and the public sector is regularly referenced, largely romanticized through the Oakland Athletics and General Manager Billy Beane's model as a result of Michael Lewis' book Moneyball. There is an even starker example of how the use of advanced statistics, data and analytics capabilities has driven positive outcomes, however, in the 2008 Tampa Bay Rays. Using many of the analytics principles adopted by Beane and the Athletics earlier in the decade, on an even smaller payroll, the Rays were able to defeat Boston and Chicago, whose team salaries were 305% and 276% higher, respectively, to make it to the World Series. Ultimately, the Rays lost to Philadelphia, and their 224% larger salary; however, it represented a great triumph for an organization using analytics to effectively produce its "services" at a broad scale under the constraints of an extremely tight budget. As more resource-strapped teams realized success with this methodology, bigger teams adopted it, effectively facilitating a new normal.

Interestingly enough, the biggest parallel between the public sector and baseball is not necessarily smaller budget organizations realizing success through innovative use of technology, but rather the existence of significant cultural hurdles. In baseball there have long been two distinct camps: those who believe in the use of advanced metrics and verifying anecdotal information through data-driven findings and those who believe in more traditional statistics and informal information. While an increasing number of fresher talents have helped drive the adoption of analytics-driven decision making in the majority of organizations, there is still a small component of individuals in the game who have reservations about the shift in how the business of baseball is conducted. This cultural impediment to adopting analytics, as well as other disruptive technologies, is also not uncommon in the public sector, where the adoption of change, particularly related to structural changes in how programs and agencies are measured, has always been a remarkably cumbersome undertaking.

Despite the many hurdles, disruptive technologies such analytics will be critical to moving forward with a more efficient, predictive government

The change in focus from consolidating similar operations to the adoption of disruptive technologies will play a major role in shifting government from a reactive mindset to a predictive operating model. It also will ultimately drive more effective delivery of citizen services. Analytics, in particular, will facilitate the maturation of government, allowing agencies to prepare for a new wave of challenges that will accompany budgetary constraints and the ongoing demographic shift in many western countries. While there will be significant challenges to address — culturally, financially and in resource retention and development — the summit was an encouraging reminder that there are many individuals, in government and in organizations such as Accenture and Harvard that serve them, who are cognizant of emerging challenges and are collaboratively seeking and identifying solutions.

Technology Business Research, Inc. is a leading independent technology market research and consulting firm specializing in the business and financial analyses of hardware, software, professional services, telecom and enterprise network vendors, and operators. Serving a global clientele, TBR provides timely and actionable market research and business intelligence in a format that is uniquely tailored to clients' needs. Our analysts are available to further address client-specific issues or information needs on an inquiry or proprietary consulting basis. 

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