Managing the Enterprise on Limited Resources Using ERPs

Oh, no! You won't be getting a printed SCUP–45 Preliminary Program in the mail this year. Instead, SCUP is going green and regularly updating this digital version (PDF), which you can download at any time.

Check it out! You don't want to miss higher education's premier planning conference, and your one chance this year to assemble with nearly 1,500 of your peers and colleagues: July 10–14, Minneapolis.

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SCUP Link

Tim Goral of University Business examines the use of Enterprise Resource Planning systems (ERPs) in the current economic climate by interviewing several campus leaders and some experts from the corporate world:

We’ve all heard the mantra: Do more with less. In the current economy, colleges and universities are continually being asked to be more productive and effective with ever-shrinking resources. A key to accomplishing that is to have a solid information system—an intergrated Enterprise Resource Planning (ERP) system that can help them toward that goal in numerous ways.

[And . . . ]

The other big difference is a fundamental shift in the way our staff is being used. When we had our legacy system, most of our development staff was in maintenance and repair mode. Now we’re almost completely out of that mode and looking at how to create value-adding projects for our university.

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SCUP's Planning Institute: Enjoy the F2F company of your colleagues and peers while you engage in one of the three SCUP Planning Institute Steps. In addition to being offered on demand, on campuses to teams of campus leaders, the institute steps are also offered to all professionals at varying times and venues. Currently scheduled are:

• May 22–23, Ann Arbor, MI - Step I
• July 10, Minneapolis, MN - Step I (in conjunction with SCUP–45)
• October 2, Ann Arbor, MI - Step I
• January 21–22, Tuscon, AZ - Step II and Step III

Time Is Lost, Confusion Results, and Money Is Spent

In the recent SCUP survey of members' use of social media, a common complaint by those who do not use social media, or who have tried to and loathed it, was that it is a "waste of time." In this recent Economist article, the manager of a Connecticut manufacturing firm is auoted complaining about the effects of the telephone . . . in 1917: 'Time is lost, confusion results and money is spent.' but goes on to say "Yet what is happening now goes way beyond incremental growth. The quantitative change has begun to make a qualitative difference." (Don't worry, SCUPers, as we move forward in social media use, our traditional communications channels - website and email - will still be there for you.) Many SCUPers spend a lot of time with data and are well aware of the new capacities to collect it, analyze it, and display it:

This shift from information scarcity to surfeit has broad effects. 'What we are seeing is the ability to have economies form around the data—and that to me is the big change at a societal and even macroeconomic level,' says Craig Mundie, head of research and strategy at Microsoft. Data are becoming the new raw material of business: an economic input almost on a par with capital and labour. 'Every day I wake up and ask, ‘how can I flow data better, manage data better, analyse data better?' says Rollin Ford, the CIO of Wal-Mart . . . 'The data-centred economy is just nascent . . . You can see the outlines of it, but the technical, infrastructural and even business-model implications are not well understood right now.' This special report will point to where it is beginning to surface.

What Does It Mean to Say That a Group of Institutions Are 'Comparable'

Writing in the TLT Group's blog, Steve Ehrmann muses about a thread he has been following in the ASSESS email list in which some are questioning the value of collecting certain kinds of comparable data from comparable institutions. To Ehrmann, the biggest reason for caution is research by Howard Bowen:

Howard Bowen tested the hypothesis that higher education instruction has a production function, i.e., that there is some normal relationship between spending and outcomes. When someone remarks that "I can't run a program with that budget; it's too little money," or enviously comments about another program, "With that endowment and budget, they must be wasting a lot of money," or simply spends time collecting comparable data in order to compare their program with the norm (can we boast our results are 5% better than those achieved by other programs that have about our same budget? can we use below average budgets to justify a request for an increase?) --- all of those imply a faith in a production function . . . [He]found no such evidence to support the belief in a production function.

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Regional SCUP Events! Enjoy the F2F company of your colleagues and peers at one of three SCUP regional conferences this spring:

• March 14–16: Baltimore, MD
• March 24–26: Cambridge, MA
• April 5–7, San Diego, CA

States Collect Information on Students, Report Says, but Don't Use It Enough

The DQC's website is useful, including a set of resources on ARRA funding resources that can be used for data-related activities. "Since 2005, the Data Quality Campaign (DQC) has supported state development of longitudinal data systems that provide policymakers with information to create and adjust policies and practices to improve student achievement." The DQC conducts an annual survey about what student data states are collecting, and how they are using it, then matches the states' actions to its own 10 Essential Elements. The results of that survey are available on its website. Here is a brief item in The Chronicle of Higher Education by Eric Kelderman titled "States Collect Information on Students, Report Says, but Don't Use It Enough."

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Regional SCUP Events! Enjoy the F2F company of your colleagues and peers at one of three SCUP regional conferences this spring:

• March 14–16: Baltimore, MD
• March 24–26: Cambridge, MA
• April 5–7, San Diego, CA

ECAR Study: Institutional Data Management in Higher Education

The EDUCAUSE Center for Applied Research (ECAR) has issued a new report, Institutional Data Management in Higher Education, based on a previous survey. It should be of interest to planners and others who collect, manipulate, analyze, or use institutional data for decision making. If your campus is an ECAR subscriber, you should be able to download the entire report. Even if not, you can access the Table of Contents, Key Findings, Roadmap, and the Survey Instrument. ECAR describes the report in this way:

This 2009 ECAR study of institutional data management examines the policies and practices by which higher education institutions effectively collect, protect, and use digital information assets to meet academic and business needs. Importantly, it also explores the impact of the "data big bang" on colleges and universities and the way information technology (IT) organizations deal with it. While the overall guiding concept is data management, the definition of data management that informs this study refers broadly to information assets in digital form. The study takes a multipart approach that includes a literature review to examine data management frameworks and definitions and to define issues and establish research questions; consultation with higher education IT administrators and data management experts to identify and validate survey questions; a quantitative web-based survey of EDUCAUSE member institutions that received 309 responses, 78% of which were from the institution CIO or equivalent; qualitative interviews with 23 higher education IT leaders and staff; and two case studies, one examining a sensitive data risk reduction initiative at the University of Virginia, and one concerning Chronopolis, a multi-institutional grid-based project for the long-term preservation of research data.

[more]

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Regional SCUP Events! Enjoy the F2F company of your colleagues and peers at one of three SCUP regional conferences this spring:

• March 14–16: Baltimore, MD
• March 24–26: Cambridge, MA
• April 5–7, San Diego, CA

Dashboards Deliver Data Visually at ASU

Arizona State University is now also a leader in dashboard use. This is a nice article from Campus Technology magazine by Linda L. Briggs:

ASU currently has some 30 dashboards across 25 subject areas, drawing on thousands of key data items. The popularity of various dashboards is cyclical, Rome said, but currently, a dashboard that summarizes CRM help desk support ranks high in use, as does a high-level financial report dashboard, along with dashboards summarizing HR reports and one on research grants and awards.

An enrollment management dashboard allows the user to drill down on courses and information on prospective students, then, with the right permission, to link to the Oracle PeopleSoft program to update student data. Another dashboard offers a visual monitor of class enrollment, so that when a class reaches a certain size, a red dot indicates that the class is near capacity. A quick visual scan can indicate the red dots that suggest where to consider adding supplementary classes.

Of special interest is the use of students in developing dashboards.

Accountability Measures

Subtitled, "States rely on new "data systems" to track institutional success and student outcomes," this author concludes that it does not require "new ways of doing things" for states to do a better job of collecting data about institutional performance—models that work exist right now, they're just not widely distributed. More institutions are using what some call information analytics:

What state accountability systems don't tend to do is the one and only thing that accountability systems are ultimately for: improve colleges and universities on behalf of students and the public at large. This we know because affordability is declining, graduation rates are stagnant, and the few indicators of college student learning we can find, such as the National Assessment of Adult Literacy, are so terrifying (most college graduates aren't proficient on a test of prose literacy) that we all but pretend they don't exist.

Fortunately, there are reasons to be optimistic. While most states are not gathering useful information about teaching and learning in higher education, some are. While most states do not use the information they gather to create real incentives for institutional change, some do. If every state did nothing but adopt the best practices that already exist elsewhere, higher education accountability in America would be greatly improved. This possibility is further enhanced by the single biggest difference between 1986 and the present: the explosion in availability of inexpensive, timely and reliable information.

'Flowing Data': Strength in Numbers

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SCUP's newest book is A Guide to Planning for Change by Donald M. Norris and Nick L. Poulton. In it they address data analysis and reporting in support of decision making, and speak of what they call "analytics for the masses," meaning "A new generation of tools supporting analytics and alignment enables planners and strategists to rigorously measure, assess, and refine their strategies throughout cascading cycles of expeditionary execution. These analytics are not just for so-called 'power users,' but for all administrators, faculty, and staff." (p. 32)

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Many kinds of SCUPers are interested in data: collecting it, analyzing it, displaying it, using it for decision making. Flowing Data is a website devoted to cool ways of reporting and using data - data visualization. Browsing in here you can get glimpses of what a future life with more and more information analytics will be like. Many people post here. The owner describes it to newbies this was:

The greatest value of a picture is when it forces us to notice what we never expected to see. If you're new here, welcome to FlowingData. A good place to start is the archives where you'll find FlowingData's most popular posts or take a look at the FlowingData beginner's guide. If you like what you see, subscribe to the feed. It'll only cost $1 million to do so. Yes, I'm totally serious. Really - which makes me a trillionaire.

Business Intelligence: From Data to Information

An interesting article, with a couple of mini-case studies and some bulleted specific "what to look for" suggestions about purchasing systems:

“Historically we had programmers, and we could ask them some specific questions, and they’d go off, and if we were lucky they’d come back sometime in our lifetime with the answer to our questions,” recalls Richard Burnette, FSU’s director of student information management. “Or else we had a number of fixed reports that we’d been using for years to track where we were and plan strategically off of them. That’s not very flexible.”

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Only within the last decade, says industry analyst Nicole Engelbert of Datamonitor, has higher education began effectively exploiting BI solutions. Even then, it was something of a luxury reserved for the largest institutions. But external trends have made BI much more attractive to a wider range of IHEs. “Institutions are under a lot of pressure from a productivity and efficiency perspective,” she says. “There’s a lot of push for accountability—from the federal government, state governments in some cases, accrediting bodies, even from the U.S. News & World Report. ... That’s pushed high-level decision-makers to think, ‘How can we do better? How do we know if we’re doing better, and what should we do to do better?’”

The End of Theory: The Data Deluge Makes the Scientific Method Obsolete

A quick read of this article will inform you that it is not just in assessment and learning outcomes that the world is turning to data and more data; although you will learn in SCUP's new book, A Guide to Planning for Change, about the immense importance of information analytics. From this article:

At the petabyte scale, information is not a matter of simple three- and four-dimensional taxonomy and order but of dimensionally agnostic statistics. It calls for an entirely different approach, one that requires us to lose the tether of data as something that can be visualized in its totality. It forces us to view data mathematically first and establish a context for it later. . . . This is a world where massive amounts of data and applied mathematics replace every other tool that might be brought to bear. Out with every theory of human behavior, from linguistics to sociology. Forget taxonomy, ontology, and psychology. Who knows why people do what they do? The point is they do it, and we can track and measure it with unprecedented fidelity. With enough data, the numbers speak for themselves.

California Community College GIS Collaborative

What a great example of a systemwide collaborative effort in support of planning and information sharing! This gets great information out in the hands of whoever needs it, in the spirit of providing information for analysis and planning: "Starting with working with district leaders to find written legal descriptions to knitting together the final 72 maps from a composite set of 1.5 million polygons, a lot of time and effort has gone into completing this first version of the final map. Thanks to this collaborative endeavor, we have gained an important resource for better understanding and serving the California Community Colleges."

I am excited to announce that a statewide map of all 72 CCC district boundaries has been completed and is available for download here. Select the map on the left to view an enlarged image.

This set of GIS maps is a critical data analysis tool being used to integrate many different CCC data sets to answer questions important to the mission of the California Community Colleges. These maps can be used for research about regional demographics and population growth, election histories and bond election planning, enrollment forecasting, enrollment patterns of neighboring districts, traffic and public transit impacts to students and colleges, workforce development, and facilities planning and maintenance. They also can provide tools for the classroom; a GIS course at Rio Hondo College is already putting them to good use.

The Petabyte Age: Because More Data Isn't Just More - More Is Different

This collection of related articles from Wired magazine is required reading—that is, required if you want to risk overstimulation of your brain about major changes in the ways we collect and record large amounts of data:

Sensors everywhere. Infinite storage. Clouds of processors. Our ability to capture, warehouse, and understand massive amounts of data is changing science, medicine, business, and technology. As our collection of facts and figures grows, so will the opportunity to find answers to fundamental questions. Because in the era of big data, more isn't just more. More is different.