Press Release: U.S. Department of the Treasury Approves Mentor-Protégé Agreement for IBM and ASR Analytics

September 30, 2008 | Leave a Comment

Potomac, MD, September 30, 2008: ASR Analytics LLC, a consulting firm providing advanced analytic services to public and private sector clients, recently entered into a Mentor-Protégé agreement with IBM Global Business Services (NYSE: IBM), under the U.S. Department of the Treasury, Office of Small and Disadvantaged Business Utilization, Mentor-Protégé program. Through this 10 month agreement (with the option to extend), IBM will provide developmental assistance and mentoring to ASR in areas such as corporate management and infrastructure and performance management. The Mentor-Protégé relationship will also foster increased collaboration between ASR and IBM in delivering consulting services to the Department of Treasury, helping the department modernize, manage performance, and provide outstanding service to taxpayers.

The Treasury Mentor-Protégé program was created to motivate and encourage firms to assist small businesses, including HUBZone small businesses, small disadvantaged businesses, women-owned small businesses, veteran-owned small businesses, and service disabled veteran-owned small businesses. The program is also designed to improve the performance of Department of the Treasury contracts and subcontracts, foster the establishment of long-term business relationships between these entities and Treasury prime contractors, and increase the overall number of these entities that receive Treasury contract and subcontract awards.

According to Mike Stavrianos, a founding principal of ASR Analytics, the partnership will be mutually beneficial for all parties. “ASR is proud to have been selected by IBM Global Business Services and the U.S. Department of Treasury for the Mentor-Protégé program,” said Stavrianos. “While ASR will certainly benefit from the opportunity afforded by this innovative program, we plan to contribute greatly to make this a win-win-win partnership for all involved.”

IBM has participated in the Treasury Mentor-Protégé program since 2001, having served as a mentor to a select group of small businesses. IBM is a major provider of business and IT consulting services to the federal government and has extensive experience working with the Department of Treasury.
“ASR’s domain expertise surrounding tax policy and tax system administration, combined with their expertise in advanced analytics solutions will enhance IBM’s ability to provide unique solutions to its current and future clients within the Department of Treasury,” said Mona Kotlarsky, Executive Project Manager at IBM Global Business Services.

For more information about ASR Analytics solutions for government clients, visit: http://www.asranalytics.com/solutions/government/

About ASR Analytics, LLC
ASR Analytics LLC (ASR) provides customized business intelligence and analytic consulting services to clients in the public and private sectors. ASR aims to provide policy makers with self-service decision support tools to ensure regulatory compliance and increase organizational effectiveness. To learn more about our solutions visit: http://www.asranalytics.com/.

Press Release: ASR Analytics Puts Predictive Analytics Directly into the Hands of Enrollment Managers

September 29, 2008 | Leave a Comment

Seattle, WA, September 25, 2008: While attending the National Association for College Admission Counselors (NACAC) 64th Annual Conference, ASR unveiled its new Predictive Analytics Solution for Recruitment and Admission. The new solution is designed to put the power of advanced analytics directly into the hands of enrollment management professionals for better evidence-based decision making. ASR’s Recruitment Analytic Models leverage institution specific data to estimate statistically valid forecasts of future enrollment, net tuition revenue, and even retention rates. These models provide enrollment managers with evidence based predictions for shaping the incoming class with the ‘ideal’ students for their institution.

ASR’s solution is different. Admissions professionals will be able to interact with the models to build various enrollment scenarios and change the model’s assumptions. This helps them understand the inevitable trade-offs that can happen when they simulate various policy ‘levers.’ ASR’s solution focuses on making these models accessible to non-technical admissions professionals. Most of the solutions on the market require an IT professional to extract data in a specific file format to provide to a third party that estimates an analytic model. The institution receives a static report to guide planning decisions, but it doesn’t let them simulate a variety of scenarios.

ASR’s new Predictive Analytics Solution for Recruitment and Admission will help the institution develop its recruitment strategy and at the same time enable better day-to-day tactical decision making. The solution will help institutions to:

  • Identify causal factors for enrollment
  • Analyze a prospect pool for more effective list purchases
  • Simulate a multitude of enrollment scenarios
  • Forecast enrollment on a daily basis throughout the recruitment lifecycle
  • Perform decision impact analysis and assessment

There were three main goals in development of the framework:

  1. Provide a user-friendly way for busy enrollment management professionals to interact with predictive models to aid in institutional planning.
  2. Produce a solution that works with existing tools and technology already in use at the institution.
  3. Eliminate the need for clients to pay new recurring software license fees.

The secret to successfully meeting these goals lies in ASR’s ability to develop analytic solutions that help institutions integrate their people, process, and technology. “We think it’s critically important that advanced analytics are put directly into the hands of those that do the planning and make the decisions” said, Dr. Peter Arena, ASR’s founding principal and chief statistician for higher education. “Using simple, point-and-click interfaces – enrollment professionals can bring data and information to life. The result is a rich user experience that makes it easier to visualize data, simulate decisions before they are made, and ultimately optimize recruiting.”

To learn more about ASR’s solutions for higher education visit:

ASR’s Predictive Analytics Solution for Recruitment and Admissions: http://www.asranalytics.com/solutions/education/recruitment-analytics/

ASR’s solutions for Higher Education: http://www.asranalytics.com/solutions/education/

ASR’s business intelligence blog: http://www.asranalytics.com/category/blog/

About ASR Analytics, LLC

ASR Analytics LLC (ASR) provides high-end business intelligence and analytic consulting services to clients in higher education. ASR aims to provide institutional decision makers with self-service decision support tools to help them be more effective in their recruitment, retention, and accountability initiatives. To learn more about our solutions visit: http://www.asranalytics.com/

7 Recommendations for BI Success

September 9, 2008 | Leave a Comment

One of the biggest reasons a BI initiative fails is lack of ownership by the ‘business’ units of an organization. A recent article in DM Review provides seven recommendations in an attempt to remedy the situation. The article provides a few new and interesting ways to think about this problem, that I like, however, the authors lay it out a little more verbosely than I would like. I’ll summarize the main points below:

The authors do a good job articulating the causes of user satisfaction or dissatisfaction with BI:

  1. The pace at which users receive answers to questions.
  2. The degree of relevance between the answer and the question asked. (An answer with little or no relevance to the user’s question is as good as no information at all.)
  3. The (perception of) reliability of the answer. (Do I trust the answer enough to use it?)
  4. The cost of information compared to its value. (Users are not interested in answers where the cost exceeds the value of the information.)

The article continues with seven recommendations to resolve these problems, however, I’m not so sure that - in the end - the recommendations squarely address the causes articulated above. Still, the recommendations in their own right are worthy of consideration. For purposes of clarity I will paraphrase the recommendations in my own words:

  1. Create an organizational unit that is responsible for the design, development, and support of your business intelligence initiative.
  2. Funding for the BI foundation should come from IT or another central budget source, while funding for individual subject area reporting and analysis should come from the business unit.
  3. Develop a federated enterprise data warehouse - make sure it is flexible and can grow as the business unit’s needs grow.
  4. Use technology that helps you manage the BI foundation when data structure changes are needed.
  5. Use an iterative approach to BI application development - seek frequent user feedback and deploy in days and weeks, not months and years.
  6. BI tools provided by your enterprise software provider (ERP) are useful for creating an Operational Data Store (ODS), not an Enterprise Data Warehouse (EDW).
  7. Create a data governance group that is led by your BI Organizational Unit.

I’d be interested to hear what others think about some of these recommendations and the counter arguments they may have.