© 2005 ESP Solutions Group Max Yield Data™ Max Yield Data™ (MYD) simply means “data that everyone agrees are worth the effort.” Max Yield Data™ have been standardized, collected, and presented such that the maximum use can be made of them for decision making and reporting mandates.

© 2005 ESP Solutions Group The Goal of Max Yield Data™ Agreement among teachers, school site administrators, program managers, and central office staff that a required report yields such useful information that all the effort put into the collection and reporting of that data is worthwhile.

© 2005 ESP Solutions Group The Four Rules of Max Yield Data™ 1. Get the right data. –(Standards, Validity) 2. Get the data right. –(Data Quality) 3. Get the data right away. –(Cycle Time) 4. Get the data the right way. –(Best Practices, Automation)

© 2005 ESP Solutions Group Shared Characteristics To be Max Yield, data must have these characteristics: 1.High Quality 2.Managed Accessibility 3.Certification 4.Interoperability 5.Utility 6.Affordability 7.Granularity

© 2005 ESP Solutions Group To be Max Yield, data must have these characteristics: 1. High Quality Timely Valid Reliable Complete Clearly Defined Aligned Periodicity Trusted and Relied Upon

© 2005 ESP Solutions Group To be Max Yield, data must have these characteristics: 2. Managed Accessibility Authority Designations Confidentiality Designations Reliability Designation Ubiquitous Access (location, time) Query, Analysis Capability Pre-calculated Statistic OLAP Cubes for Selected Data

© 2005 ESP Solutions Group To be Max Yield, data must have these characteristics: 3. Certification Official Status Official Reports Official Indicators and Statistics

© 2005 ESP Solutions Group To be Max Yield, data must have these characteristics: 4. Interoperability Linkability Comparability Clearly Defined

© 2005 ESP Solutions Group To be Max Yield, data must have these characteristics: 5. Utility Actually Used Applicable to Information Needs Trusted and Relied Upon

© 2005 ESP Solutions Group To be Max Yield, data must have these characteristics: 6. Affordability Funded Collection or Consolidation Expenses Consolidated Collection Practical to Collect Alignment with Data Provider Needs, Work Flow, Systems Automated Collection with Authentication and Verification Rules

© 2005 ESP Solutions Group To be Max Yield, data must have these characteristics: 7. Granularity Lowest Unit of Analysis Appropriate Unit of Analysis

© 2005 ESP Solutions Group Technical Infrastructure for MYD Max Yield Data™ must be supported by an adequate technical infrastructure. Such an infrastructure must support the implementation of the characteristics of MYD described above and facilitate the management of the systems within which the MYD exist.

© 2005 ESP Solutions Group An adequate MYD infrastructure must have these characteristics: Storage Sufficient Storage Capacity Efficient (Fast) Data Access Speed

© 2005 ESP Solutions Group An adequate MYD infrastructure must have these characteristics: Compilation Automated Submission Processes

© 2005 ESP Solutions Group An adequate MYD infrastructure must have these characteristics: Transfer Data Exchange Standards Telecommunications

© 2005 ESP Solutions Group An adequate MYD infrastructure must have these characteristics: Policy Clear Policy for Data Management

© 2005 ESP Solutions Group An adequate MYD infrastructure must have these characteristics: Funding Adequate Design and Development Funds Adequate Training and Implementation Funding Adequate Maintenance Funding Adequate Enhancement Funding

© 2005 ESP Solutions Group An adequate MYD infrastructure must have these characteristics: Human Resources Skilled and Knowledgeable Staff Training and On-Going Development

© 2005 ESP Solutions Group An adequate MYD infrastructure must have these characteristics: Security Managed Access Redundancy

© 2005 ESP Solutions Group Summary Max Yield Data™ represent the best yield or return on the investment made to compile them. –Yield means the use and benefit derived from the data. –Investment means the direct costs and all the in-kind resources required to compile them. –Compile means the process of submitting, collecting, cleaning, and storing the data.

© 2005 ESP Solutions Group About ESP Solutions Group Exclusively focused on K-12 education data systems National firm – Have assisted all 52 state education agencies Pioneered concept of K-12 “Data Driven Decision Making” (D3M) in the 1970’s Offices in Austin and Washington DC Major focus on SEA and Federal data systems Provides consulting services and software products that help education agencies achieve MYD and D3M