By rbewtra-Oracle on Aug 07, 2014
Author: John Siegman
How do you know if you have a Master Data Management (MDM) or Data Quality (DQ) issue on your campus? One of the ways is to listen to the concerns of your campus constituents. While none of them are going to come out and tell you that they have a master data issue directly, by knowing what to listen for you can determine where the issues are and the best way to address them.
What follows are some of the key on-campus domains and what to listen for to determine if there is a MDM or DQ issue that needs to be resolved.
Student: Disconnected processes lacking coordination
· Fragmented data across disparate systems, disconnected across groups for:
- data collection efforts (duplicate/inconsistent student/faculty surveys)
- data definitions, rules, governance
- data access, security, and analysis
· Lack of training around security/access further complicated due to number of sources
· No information owner/no information strategy
· Student attributes maintained across many systems
Learning: Does not capture interactions
· Cannot identify students at risk. Do not capture interactions with students and faculty, and faculty interactions for research support, etc.
· No way to track how many undergraduates are interested in research
· Don't do any consistent analytics for course evaluations
· Difficult and time consuming to gather information because of the federated nature of the data – for example, job descriptions in HR are different than what is really being used
· There is no view of Student experience
HR: Process inconsistencies, lack of data standards complicates execution
· Faculty not paid by the university are not in the HCM system, while students receiving payments from the university are in the HCM system
· Disconnected process to issue IDs, keys, duplicate issues
· Given multiplicity of data sources, accessing the data is a challenge
· Data analytics capabilities and available reports are not properly advertised, so people do not know what is available. As a consequence an inordinate amount of time is spent generating reports
· Faculty/Staff information collection is inconsistent, sometimes paper-based. Implication: lose applicants because it is too difficult to complete the application process
Research: Getting from data to insight is a challenge
· Very time consuming to determine: Which proposals were successful? What type of awards are we best at winning?
· Difficult to understand: number of proposals, dollar value, by school, by department, by agency, by time period
· Data challenges in extracting data out of the system for grants, faculty, and making it centrally available
Deans & Officers: Reporting is a challenge
· Significant use of Excel, reporting is becoming unstable because of the amount of data in the files
· Information charter, a common retention policy does not exist
· A lot of paper is generated for the domains we are covering. Converting paper to digital is a challenge
· Collecting information on faculty activity (publications) is a challenge. Data in documents requires validation
· Data requests result in garbage. Donors receiving the wrong information.
Finance: Has little trust in data
· Do not have workflow governance processes. Implication, information goes into the system without being reviewed, therefore errors can make it into the records
· Systems connected to ERP systems do not always give relevant or requested info
· Closing the month or quarter takes too long as each school and each department has its own set of GLs.
Facilities: Efficiencies are hampered due to data disconnects
· Do not have accurate space metrics due to outdated system, schools not willing to share their info with Research Administrators and Proposal Investigators
· Do not have utility consumption, building by building
· No clear classroom assignment policy (a large room may be assigned to a small number of students)
· Not all classes are under the registrar's control
· No tool showing actual space for planning purposes
· Difficult to determine research costs, without accurate access to floor plans and utilization
· Cannot effectively schedule and monitor classrooms
If your campus has data, you have data issues. As the push for students becomes more competitive, being able to understand your current data, mine your social data, target your alumni, make better use of your facilities, improve your supplier relationships, and increase your student success will be dependent on better data. The tools exist to take data from a problem filled issue to a distinct competitive advantage. The sooner campuses adopt these tools, the sooner they will receive the benefits of doing so.