Max Yield Data

1
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.

2
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.

3
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)

4
Shared Characteristics

• To be Max Yield, data must have these
  characteristics
• High Quality
• Managed Accessibility
• Certification
• Interoperability
• Utility
• Affordability
• Granularity

5
To be Max Yield, data must have these
characteristics

• 1. High Quality
• Timely
• Valid
• Reliable
• Complete
• Clearly Defined
• Aligned Periodicity
• Trusted and Relied Upon

6
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

7
To be Max Yield, data must have these
characteristics

• 3. Certification
• Official Status
• Official Reports
• Official Indicators and Statistics

8
To be Max Yield, data must have these
characteristics

• 4. Interoperability
• Linkability
• Comparability
• Clearly Defined

9
To be Max Yield, data must have these
characteristics

• 5. Utility
• Actually Used
• Applicable to Information Needs
• Trusted and Relied Upon

10
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

11
To be Max Yield, data must have these
characteristics

• 7. Granularity
• Lowest Unit of Analysis
• Appropriate Unit of Analysis

12
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.

13
An adequate MYD infrastructure must have these
characteristics

• Storage
• Sufficient Storage Capacity
• Efficient (Fast) Data Access Speed

14
An adequate MYD infrastructure must have these
characteristics

• Compilation
• Automated Submission Processes

15
An adequate MYD infrastructure must have these
characteristics

• Transfer
• Data Exchange Standards
• Telecommunications

16
An adequate MYD infrastructure must have these
characteristics

• Policy
• Clear Policy for Data Management

17
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

18
An adequate MYD infrastructure must have these
characteristics

• Human Resources
• Skilled and Knowledgeable Staff
• Training and On-Going Development

19
An adequate MYD infrastructure must have these
characteristics

• Security
• Managed Access
• Redundancy

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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.

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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 1970s
• 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
• www.espsolutionsgroup.com