OMB

Background.  Early in the Obama Administration, OMB announced an initiative to create a small handful of High Priority Performance Goals in each agency, as a replacement for the Bush Administration’s

Since 2001, Dr. Behn has visited dozens of governmental organizations that are using the PerformanceStat model – some well, and some poorly.  His bold objective was to answer the research question of whether PerformanceStat really makes a difference in improving performance, and how it works.  In short, his answer is:  it depends, and it’s complicated.

Creating Organizational Self-Defense

First, a reflection of events from Sep 11, 2001: I was the career deputy advisor for OMB on IT and E-Government issues. On that day, our office was working closely with the Council for Excellence in Government (CEG) to host a meeting of international IT leaders – one of the early meetings of CIOs and equivalent executives from multiple countries, done in partnership with CEG (which for many years led government, industry, academia, non-profits, and civil society groups generally on technology and management excellence initiatives).

Other federal agencies also face a wide range of risks. Some are external, others are internal. Some are financial (such as having to deal with managing under Sequester or the market impact on external investments in pension funds, which could affect federal pension guarantees). Some are operational, such as those faced by FERC, or cybersecurity threats, or even insider threats. And some are reputational, such as the recent accusations of Patent Office telework abuse, or the General Services Administration’s lavish conferences scandal.

Previous to her experience with OMB, Ms. Danzig worked with the Department of Housing and Urban Development (HUD) and helped develop and lead its acclaimed HUDStat program. Prior to that, she led strategic planning for New York City’s housing programs. She has an MBA and is a former community organizer. She shares her four top tips on creating and using analytics, based on her combined experiences on data and analytics. They include: Tip 1: Choose Smart Goals. Performance management requires a commitment to the continuous improvement of best practices.

The initial premise twenty years ago was that if performance information was made readily available, it would be used by agency decision-makers.  That turned out to not be true.  

Background.  A recent GAO study conclude that the “use of performance information has not changed significantly” in surveys of federal managers between 2007 and 2013.  More specifically:

Senator Coburn has long campaigned against the seeming incomprehensibility of the federal government’s many programs. He sponsored two pieces of legislation in 2010 to address his concerns. The first bill requires the Government Accountability Office (GAO) to annually assess the fragmentation, overlap and duplication of federal programs. The second bill requires the Office of Management and Budget (OMB) to create and publish on the Internet an inventory of all federal programs. Background.

Dr. Boston, visiting the U.S. on a Fulbright Scholarship, sums up some of his initial research on how the U.S. and several other democratic countries address long-term policy issues, in a recent presentation at American University. Background. Dr. Boston says that there are a number of important societal problems that reach beyond the span of an election cycle, and that for political leaders there can be “a temptation for intergenerational buck-passing.

In this final installment, we provide highlights from these federal leaders on the most important ingredients for a successful analytics program. (You can watch the video of the panel discussion and listen to each of the seven podcast interviews too.) The executives profiled complex programs in several agencies that have a wide impact on citizens, who benefit greatly from leveraging data as a strategic asset in program operations. What follows are some highlights from those executives on salient take-aways for government and stakeholder groups who are implementing key data-driven programs.