Note: I started this blog series to share my reflections and create a dialogue on how the role of the CIO must adapt to meet the information management challenges that face us as we move deeper into the 2nd decade of the millennium.

Summers within the Federal landscape do not mean a slower pace of work in spite of Washington’s often stifling humidity. At HUD, we’re working on solidifying the gains made by the reforms we initiated last year so we can get on to the next round of improvements. At the same time, we’re preparing our budget submission and expect close scrutiny due to the constant budget tightening and increased demand for transparency. We can transform HUD in the face of fiscal unknowns by creating a transparent IT management framework and using data more intelligently.

CIOs have to find innovative ways to produce new value from existing sources in these times of fiscal constraint and increasing customer demand. Our data is one of the places we will look for creating this value. Enriching business intelligence throughout HUD and across the Federal government will be a critical priority for confronting budget. By building links among data where none now exist, we can create new intelligence at low cost that can contribute significant business value to our customers. Our customers need good information to help them make sound decisions however data by itself is just a series of points along a set of roads with no discernable interaction. Intelligence is making logical connections from those points on those roads, using maps, legends, traffic conditions, and the latest construction updates to generate optimal turn-by-turn directions, to enable us to get where we need to go.

Take HUD’s partnership with the Department of Veteran Affairs (VA) on the Homelessness Analytics Initiative (HAI) as an example. For years, various agencies have been collecting data on homelessness counts, shelter performance, unemployment rates, and other social and economic factors. Each agency collected the data without consideration for interoperability. The HAI is combining all of these separate datasets and building a network of intelligence into a predictive model that we can soon use to forecast homelessness patterns, monitor shelter performance, and address critical concerns such as chronic homelessness among veterans. The first iteration of this model will be launched by the end of 2011.

HAI will allow us to anticipate changes in the environment and to respond to those changes with agility. A narrow focus on what is essential today may satisfy the watchful budget eye, but innovative approaches like HAI create new solutions to old problems that are directly tied to mission performance and consume fewer resources than building the same intelligence from scratch. Transformation is about being more efficient and effective, lowering costs, and doing more with less. Optimizing existing data, to help us make more informed decisions, will help us deliver increased value with fewer dollars.

To enable this data optimization at HUD, we are building a strong IT management framework that embeds a repeatable, consistent approach to prudent decision-making into our environment. With the Clinger-Cohen Act as our underpinning, we are creating a strong foundation with explicit guidance on how HUD manages investments to achieve the results we expected in the timeframe we specified. As we apply this framework, I am focused on five things we need to do to maximize the value of our data:

1.  We have to know what data we have…therefore architecture is critical
2. Implement the necessary policies, procedures, standards, and guidelines to link our data intelligence efforts with overall mission (which is very clear in the HAI situation since homelessness is an administration goal that has been assigned to HUD and VA).
3. Treat data as a national asset, getting over any “ownership” issues in order to share openly
4.  Exploit and reward innovative thinkers who creatively use data to address issues
5. commit constant attention to security and privacy

Doing these five things will create new value from existing sources for small incremental costs.