A few weeks back you might remember news about a higher education rating system proposal from the Obama administration. As I've discussed previously, political and stakeholder pressures to improve outcomes and increase transparency are stronger than ever before. The executive branch proposal is intended to make progress in this area. Quoting from the proposal itself, "The ratings will be based upon such measures as: Access, such as percentage of students receiving Pell grants; Affordability, such as average tuition, scholarships, and loan debt; and Outcomes, such as graduation and transfer rates, graduate earnings, and advanced degrees of college graduates.”

This is going to be quite complex, to say the least. Most notably, higher ed is not monolithic. From community and other 2-year colleges, to small private 4-year, to professional schools, to large public research institutions…the many walks of higher ed life are, well, many. Designing a ratings system that doesn't wind up with lots of unintended consequences and collateral damage will be difficult. At best you would end up potentially tarnishing the reputation of certain institutions that were actually performing well against the metrics and outcome measures that make sense in their "context" of education. At worst you could spend a lot of time and resources designing a system that would lose credibility with its "customers".

A lot of institutions I work with already have in place systems like the one described above. They are tracking completion rates, completion timeframes, transfers to other institutions, job placement, and salary information. As I talk to these institutions there are several constants worth noting:

• Deciding on which metrics to measure is complicated. While employment and salary data are relatively easy to track, qualitative measures are more difficult. How do you quantify the benefit to someone who studies in one field that may not compensate him or her as well as another field but that provides huge personal fulfillment and reward is a difficult measure to quantify?

• The data is available but the systems to transform the data into actual information that can be used in meaningful ways are not. Too often in higher ed information is siloed. As such, much of the data that need to be a part of a comprehensive system sit in multiple organizations, oftentimes outside the reach of core IT.

• Politics and culture are big barriers. One of the areas that my team and I spend a lot of time talking about with higher ed institutions all over the world is the imperative to optimize for student success. This, like the tracking of the students’ achievement after graduation, requires a level or organizational capacity that does not currently exist. The primary barrier is the culture of "data islands" in higher ed, and the need for leadership to drive out the divisions between departments, schools, colleges, etc. and institute academy-wide analytics and data stewardship initiatives that will enable student success.

• Data quality is a very big issue. So many disparate systems exist (some on premise, some "in the cloud") that keep data about "persons" using different means to identify them. Establishing a single source of truth about an individual and his or her data is difficult without some type of data quality policy and tools. Good tools actually exist but are seldom leveraged.

Don't misunderstand - I think it's a great idea to drive additional transparency and accountability into the system of higher education. And not just at home, but globally. Students and parents need access to key data to make informed, responsible choices. The tools exist to not only enable this kind of information to be shared but to capture the very metrics stakeholders care most about and in a way that makes sense in the context of a given institution's "place" in the overall higher ed panoply.