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Data Warehouse User Engagement Readout

Data Warehouse User Engagement Readout. Daniel Gold, Project Manager. Agenda:. Executive Summary Study Methodology and Participants Tool Needs and How They Align to Pyramid Common Reporting Tasks Process Opportunities What is Needed for Success Summary and Next Steps. Executive Summary.

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Data Warehouse User Engagement Readout

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  1. Data Warehouse User Engagement Readout Daniel Gold, Project Manager

  2. Agenda: • Executive Summary • Study Methodology and Participants • Tool Needs and How They Align to Pyramid • Common Reporting Tasks • Process Opportunities • What is Needed for Success • Summary and Next Steps

  3. Executive Summary

  4. Methodology • Two user engagement sessions were held • 12 participants on 7/15 • 18 participants on 7/18 • Participants were broken into small groups and led through a series of activities including: • Brainstorm and categorization of data needs • Completing a “reporting story” form • Extracting tool features and process enhancements from their stories • Prioritization of features and process changes

  5. Participant Population Areas Represented: • College of Arts and Sciences • Institutional Research • College of Engineering • eCampus • Extended Studies • College of Health • Registrar • College of Health Sciences • Provost • College of Education • College of Social Sciences and Public Affairs • Admissions • Honors College • University Financial Services • BSU Foundation • STEM • OIT Roles Represented: • 5 directors • 3 associate directors • 3 business managers • 2 administrative assistants • 2 data analysts • 1 adjunct faculty coordinator • 1 advisor • 1 associate registrar • 1 business operations manager • 1 chair • 1 coordinator • 1 financial technician • 1 management assistant • 1 management systems coordinator • 1 program information coordinator • 1 project coordinator • 1 project manager • 1 senior business manager • 1 vice provost HR and Finance under-represented! Further investigation to needs of these teams required.

  6. Agenda: • Executive Summary • Study Methodology and Participants • Tool Needs and How They Align to Pyramid • Common Reporting Tasks • Process Opportunities • What is Needed for Success • Summary and Next Steps

  7. Requested Tool Features Top 10 Prioritized Features: • Drill to Detail (that I need) • Snapshots (compare points in time) • Dashboards • Build in Calculations • Easy export to Excel and PDF • Trend over time • Ability to combine multiple reports • Sort/filter data in web tool • Data “Table of Contents” and improved logical structure • Ability to add charts/graphs in web tool • Support for custom reports (MyViews) • Distribute reports to email audience from tool

  8. Pyramid Can Address Our Tool Needs

  9. Agenda: • Executive Summary • Study Methodology and Participants • Tool Needs and How They Align to Pyramid • Common Reporting Tasks • Process Opportunities • What is Needed for Success • Summary and Next Steps

  10. Report Frequent Flyers • 4 report categories made up nearly 2/3rds of all reporting stories written by participants. • Short Term: Understanding the usage of reports in these categories and improving them could have a significant impact to user satisfaction and eliminate needless effort • Long Term: Consider prioritizing the creation of dynamic dashboards in Pyramid for these common reporting tasks The “Core Four”

  11. Recommendations: • Recognize the “core four” reporting needs and prioritize enhancements for these areas • Form tiger teams for each area and investigate reporting enhancements • Identify standard reporting tasks for the “core four” that will be good candidates for dashboards when Pyramid is released What’s a Tiger Team? “ A team of undomesticated and uninhibited technical specialists, selected for their experience, energy, and imagination, and assigned to track down relentlessly every possible source of failure” - Program Management in Design and Development

  12. Common Data Manipulation Tasks • Pain Points: • Lack of complete data (HR, Finance, shadow systems) in data warehouse leads to users having to combine DW reports with queries from other sources • Comparing data for particular points in time (aka snapshots) requires running multiple reports • Drill to detail often provides significantly more data than is needed and excess rows/columns must be deleted • Lack of built in calculations and sort/filter options in web tool makes exporting data to excel mandatory • Lack of native graph building capabilities makes exporting data to excel mandatory User comment: All this would be better if… “we were able to gather point in time comparison and make the comparisons in a more efficient manner. Right now this takes 2 people approximate 6-8 hours every week to complete.”

  13. Recommendations: • Utilize tiger teams to understand why reports frequently need to be combined. • Make snapshot data available to users where it exists • Review report frequent flyers to determine how simple changes in formatting can reduce manual manipulation

  14. Use of Production Queries • 52% of participants rely on queries against the production PeopleSoft system • Expected for data that is not in the warehouse (HR, Finance, and Financial Aid) • Expected for data that needs to be real-time • 35% of participants rely on queries for student data that is in the warehouse • Unexpected since this data is available Potential Reasons for production queries: Historical point in time comparisons (snapshots) Validate data obtained through MyInsights or ProClarity Familiarity with querying production over using DW tools

  15. Recommendations: • Utilize tiger teams to understand why production queries are needed to support the “core four” • Is data missing in the warehouse? • What kind of snapshots are needed for comparison? • Are we missing key data elements like type/rank of faculty? • Ensure that Pyramid is marketed well and encourage users to begin using the warehouse to meet reporting needs

  16. Agenda: • Executive Summary • Study Methodology and Participants • Tool Needs and How They Align to Pyramid • Common Reporting Tasks • Process Opportunities • What is Needed for Success • Summary and Next Steps

  17. Data Integrity During group discussions two types of data integrity / validation issues emerged: • Trust in the accuracy of the data in the warehouse (checking for warehouse errors) • Trust that manual manipulation performed on data had not corrupted the report (checking for user errors) User Comments: “I think the most complex part of the reporting is validating the accuracy of the data. So much of what we do is this it takes the most time and is the most frustrating.” “[M]anualmanipulation in excel is time consuming and there is risk of error. Data validation.” All of this would be better if… “[It] didn't take extensive manipulation each time. Confidence that the data was correct.” “[N]umerousproclarity reports are referenced in order to create the summer report. Difficult to identify the criteria used to create the ProClarity report and difficult to validate the data. Time consuming to create report.” 1 in 4 participants cited data validation as a time consuming and required step.

  18. Recommendations • Look for ways to limit the need to combine multiple reports in excel through enhancements to current reports • Build trust in data warehouse reports by consistently validating data with data stewards and stating explicitly on reports when validation took place in each report

  19. Data Definitions • Users reported difficulty interpreting the data due to irregular naming conventions and inconsistent, unavailable, or out of date definitions. • Knowing which fields should be used in a report was often difficult when data from multiple sources had to be combined. User Comment: All this would be better if… “You could get a clear definition for what "active" means (e.g. not discontinued on PS, or what?!)” User Comment: “have you seen the terminology? there are five categories for each line. Things like STEM secondary non-STEM major”

  20. Recommendations • Determine what information needs to be stored in each data definition to aid users in making decisions when building reports • Ensure that updating data definitions is built into the development teams “definition of done” any time a report is altered or created • Improvedata definition discoverability by creating links or embedding definitions in reports

  21. Data Access and Integration Access: • Access to data was not a wide spread issue, and most users who spoke about access were concerned with limiting it (security). • A small number of users stated that they needed access to HR data to perform their job functions Integration: • Integrating HR, Finance and Student data into the data warehouse was a frequent request • Many non-BIRS supported reporting systems are used on campus. Frequently these are used for storing snapshot data for comparisons.

  22. Recommendations • Leverage the Identity and Access Management Project to help define role based data access authorization • Continue roadmap work to bring in HR and Finance data into the warehouse • Investigate commonly used reporting systems and determine if it would be reasonable to bring the data into the warehouse

  23. Process Enhancements Top 10 Prioritized Process Enhancements • Data validation • Data integration • Data definitions • Data access • Clear report structure • Standardize reports for wider usage • Make the data current (where is a student now) • Migrate custom views to new tool • Improve report request workflow • Map tools to user needs

  24. Recommendations • Continue with roadmap work to bring HR and Financial data into the warehouse • Establish a holistic “definition of done” for reports that includes data validation and data definitions for every report • Utilize Identity and Access Management project to help define roles for data access • Leverage tiger teams to standardize reports for wider use • Develop a clear and logical hierarchy for reports • Revise and evangelize report request intake process with a simple workflow that that takes into consideration requirements gathering and prioritization • Begin working to establish a “data doctor” program that includes support from subject matter experts as well as BIRS • Begin developing a rollout strategy for Pyramid that will help map training and tool sets to groups of users based on their reporting needs

  25. Agenda: • Executive Summary • Study Methodology and Participants • Tool Needs and How They Align to Pyramid • Common Reporting Tasks • Process Opportunities • What is Needed for Success • Summary and Next Steps

  26. Success Requires… • Hands on training for users • Levels of training (novice, power user, expert) • Robust documentation and tutorials • An accessible reporting expert • Data Dr. from BIRS • Peer groups • Migrate existing ProClarity reports into new tool • Clearly define what tool should be used for what task • Early adopter program for new tool • More report building resources on the BIRS team

  27. Agenda: • Executive Summary • Study Methodology and Participants • Tool Needs and How They Align to Pyramid • Common Reporting Tasks • Process Opportunities • What is Needed for Success • Summary and Next Steps

  28. Tool Implementation User Rollout Track Development Track Early adopter rollout End User Rollout

  29. Recommended Next Steps • Stay the Course for Roadmap Activities • Continue to move forward with Pyramid purchase and implementation • Continue to integrate HR and Finance data into the warehouse • Pause Report Development and Modernize Process • Define and evangelize project intake process • Refine the team “definition of done” • Respond to user engagement requests by generating specific enhancement projects for “core four” report issues identified in sessions • Identify Goals and Participants for Tiger Teams • Develop specific and measurable goals for tiger teams • Identify subject matter experts, power users, and developers to participate • Establish a timeline for tiger teams to provide actionable recommendations (likely post-roadmap)

  30. Daniel Gold, Project Manager Email daniellgold@boisestate.edu Thank You

  31. Backup

  32. Breakdown of the Core Four The above items represent the report or report goal that participants identified in their reporting story forms. Duplicates intentionally included.

  33. Tiger Teams Tiger teams work best when they are small hand-picked groups focused on a specific task (e.g. simplifying enrollment reporting). The team should include not only subject matter experts and power users, but also report and back-end database developers to speed up the process of weighing out potential solutions. These “tigers” are easily identified by being the go-to people in their area when a problem arises. The activity should be time-boxed and the output should be a list of enhancements the team can prioritize and implement with the goal of delivering on the specific task assigned.

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