I would therefore encourage you to start thinking about using the enormous amount of  data that exists out there or suggest collecting them to guide our decision making. It goes without saying that when it comes to data, we need to be extremely careful to respect the privacy issues. So, simply because the technology allows us to collect data should not mean that we can be careless about these issues. We need to make sure to consult with the appropriate offices if we are talking about data that involves our own community.

I can provide some simple examples of where we have successfully used the data to guide us or can potentially use the data to guide us.

• We looked at how many students were forwarding their email elsewhere and to which service and consulted with WSA and move the students to Google Apps for Education.
• We have been looking at the network usage by the students between 9 PM and 2 AM to reshape the bandwidth by tweaking per user allocation and other techniques so they can have a better experience. We have engaged our student staff in both the decision making (OK, we were late to do this, but we are doing it now) and testing. We are also trying to purchase additional bandwidth just during this period from the state (I wish they would move a little faster!!!)
• We also have other network monitors that we use to do capacity planning. But we need to do more. For example, we increased wireless access points in Park Washington and plan to do the same in High Rise. The network flow data we have should have told us that there are some issues with both the extent of coverage and overcrowding, but we started to look at them after we began receiving complaints.
• We have a plan to use our own Web logs, Link analyzers as well as Google Analytics to help us archive literally thousands of web pages on our web site. We are preparing a proposal to the Cabinet on this (as recommended by the Web Committee) so we can work with individual departments to do this “Operation Clean Start” (this is not an official name!!!)
• Using the web logs provides us some unique perspectives on the visitors to our websites – for example, we know that the predominant monitors used for viewing our website is of resolution 1024 x 768 or better. Of course, many of us probably see this in our own experience, but seeing the actual data from a diverse set of users goes a long way to help design our websites. Similarly, there are other useful data such as the types of browsers the users are using that should help guide the application development process.
• We are beginning to use our Keyserver as a source of data (this data has been collected for a while, we just have not had an opportunity to analyze it yet) to understand the public computer lab usage. After we have enough data, we will prepare a proposal (or not, depending on what the data says) on how best to reconfigure the computers in the labs to reflect the usage data. For example, can we replace some of them with thin clients? Armed with the data, we can have a more meaningful conversation with the WSA and ATAC when we make proposals. Otherwise, it will simply be incomplete data (”Whenever I walk by, I see the Science Tower Lab not full”).

Most of these examples refer to data that is collected already and we try hard not to ask questions that crosses privacy boundaries. In other words, the analyses on web usage, for example, are summaries and do not necessarily have personal identities associated with them. In the end, these summary data are much more useful for what we are trying to do than any data that has personal information associated with it.

We should also be looking at other sources of data to help understand the trends – ECAR (EDUCAUSE Center for Applied Research), The Horizon Report to name a couple, which have tremendous amount of data. I also  poll our colleagues in CLAC (Consortium of Liberal Arts Colleges) when I want to get a sense of what they are doing. I typically get 25-35 responses, while not a lot, very valuable because of our proximity to each others in terms of size and educational philosophy.

The past few months have been very stressful for a lot of us – wherever you went on campus, the topic of conversation was the budget issues. They are real and the plans that are being developed by the senior administration to deal with them will have serious consequences all around. Two things are clear – the problem we are currently facing will have fairly long term consequences; all of us who are supporting the core academic business of the University will be challenged to do things very differently than in the past.

During the first week of January, I plan to discuss some of the budget cuts for ITS in more detail and the idea of having to deliver services differently as a result will become clearer. Now, on to other things…

An Exciting PDA Application

I happened to hear from a friend about ShopSavvy for Google Android - it lets you take the picture of a barcode which is sent online for price comparison. What a great idea. Here you are, in Best Buy, you snap the picture of that gadget that you badly wanted, send it over the net for price comparison and within a few minutes you know exactly how much it costs elsewhere. If it is considerably cheaper, you can go ahead and order it right from your PDA.

When I mentioned this to Jim Kamm, he told me that something similar existed for iPhone from Amazon. So I downloaded Amazon.com mobile for iPhones (from the Appstore) and have been testing it. It works differently. You can take the picture of any object for which you need further information and send it to Amazon. Within a few minutes, you receive an email with a link which tells you if Amazon was able to identify the object, if so, how much it costs in Amazon. Not Bad. So far, my success rate with this has been 60% when I did it. My children and nephews have been going crazy with it (like taking the picture of thai food and beer cans) which has driven down the rate far lower. One could take the picture of a book or the ISBN number of a book and do comparison shopping too.

Barcorama for Windows Mobile devices seem to do the same thing by doing comparison through PriceGrabber or Google.

I can see how this will eventually play out – the vendors will either agree to match the lowest prices or completely block wireless data access from within the brick and mortar store (which will not work in the end!)

Super Crunchers by Ian Ayers

How about figuring out the quality of Bordeaux wine using the commonly available data and the equation:

12.145 + .00117 * Winter Rainfall + .0614 * average growing season temperature – .00386 * harvest rainfall

Make sure to specify the rainfall in millimeters and the temperature in degree Celsius. This index is more useful as a relative number than absolute, so you need to measure it relative to some of the earlier vintages. You can read more about this in Orley Ashenfelter’s paper. Apparently, this method has outperformed some of the respected wine tasters by predicting the quality way before the wines are even ready for tasting.

The same way, how about the new measure of On Base Percentage as a better indicator of batting efficiency than the simple Batting Average?

The book called Super Crunchers, which was one of my holiday gifts, written by Ian Ayers from Yale uses several examples such as these to make the point that data driven decision making is influencing a lot of fields seeped in intuition and decision making by experts.

I am a big fan of this methodology and I have been asking for a lot of data whenever possible to make informed decisions. Google Analytics is a step in that direction. For example, while confirming some of the conclusions several of us seem to have arrived at based on our own experiences, it also provides several new insights.

I have been asking academic computing services to provide me with actual usage data from the public computing labs to make decisions regarding the best way to purchase hardware for these labs. what are the usage patterns? Are these computers being used simply to read email and do routine word processing type of activities or are they actually being used to access the specialized instructional software? Collecting these types of data and analyzing them should be the driving force behind how exactly to configure these labs and not what any of us conclude based on what we “see” in the labs.

We are pretty good in tracking network stats using various tools; similarly, we are tracking the CPU and memory usage of servers; we track various budget numbers over time; I look at all of these on a regular basis. They provide so much visual information in many cases and trending can be easily understood.

So, let us become super crunchers too… Let us capture the trouble calls in ways we can learn if there is a particular question that gets repeated, so we can proactively train the users; let us use random trials