A consistent, repeatable, and measurable strategy model for assessing the maturity of national and regional Spatial Data Infrastructures
•Download as PPTX, PDF•
1 like•383 views
Regional and National Spatial Data Infrastructures (SDIs) are essential in delivering the foundation spatial data layer that underpins the evidence base enabling policy analysis, planning and development. Such a trusted, complete, and authoritative evidence base, drives improved decision making and reduces the cost of regional and national government operations. Strategic approaches to establishing and further developing SDIs need to consider the current and desired maturity of the SDI environment. They need to have measurable outcomes, and be consistent with international best-practice, to allow progress tracking and comparisons. To date, such approaches are relatively rare. This paper presents an evidence-based, proven SDI maturity model that will enable such strategies to be developed, implemented and monitored. This paper will examine some of the challenges in the changing landscape of geospatial information, and its role in regional and national decision-making. It will then present the geospatial model used to assess an SDI’s maturity. As the model comes with documentation and templates, it can be easily applied across multiple geographies to compare approaches and best-practices. The model defines five key Strategic Components: data, technology, governance, standards and people; and includes definitions of Maturity for each of the components. The model is then applied in a in a four-stage assessment methodology: 1: As-Is Analysis & Best Practice study 2: Strategy Development 3: National or Regional Geospatial Policy Development 4: Implementation Planning The paper will conclude with a number examples where the model has been applied to assess the maturity development of several national SDIs
Recommended
Recommended
More Related Content
More from Maurits van der Vlugt
More from Maurits van der Vlugt (8)
Recently uploaded
Recently uploaded (20)
A consistent, repeatable, and measurable strategy model for assessing the maturity of national and regional Spatial Data Infrastructures
- 1. A CONSISTENT, REPEATABLE, AND MEASURABLE STRATEGY MODEL FOR ASSESSING THE MATURITY OF SPATIAL DATA INFRASTRUCTURES Stream: Spatial Infrastructures Presented by: Maurits van der Vlugt Email: Maurits.vandervlugt@mercuryps.com.au Twitter: @mvandervlugt Co-Authors: • Dr. Vanessa Lawrence CB • Gilles Albaredes • John Schonegevel
- 4. Inter-operable Geospatial Data 4 Elevation Positioning (geodetic) Imagery Adm. borders Water Transport Buildings Health Etc. Economy Educational attainment Air quality Population Flood areas . Foundation Data Supplemental Data
- 5. The Economic Impact of Geospatial Services In the study “what is the economic impact of Geo-services”, Oxera estimated the global revenues generated by the geospatial services in the year of 2012 to be $270Bn1 1. What is the economic impact of Geo services? Prepared for Google, Oxera 2013
- 6. SDI’s are Coming of Age National, Regional, Local, Organisational No longer just academic Core Business enabler Reliable service levels, quality, currency
- 7. C-level is taking notice, and asking questions: What is the ROI? How do we stack up? What are our targets? Where is the evidence? How are we progressing?
- 8. A Strategic Need for SDI Maturity Modeling Assess current maturity (where are we now?) What do we aim for (final & intermediate goals)? Comparable Repeatable Measurable Evidence-based
- 9. Underlying Concepts Strategy Components Model Capability Maturity Model (CMM) Analysis
- 10. Strategy Components Model © Dr. Vanessa Lawrence CB, Gilles Albaredes, 10
- 13. A Capability Maturity Levels Analysis 13 Standards
- 14. Maturity Levels Strategy Components Level 1 - Ad Hoc Level 2 - Repeatable Level 3 - Defined Level 4 - Managed Level 5 - Optimized Not coordinated or repeatable Based on the previous successful methodology Successful processes documented to guide consistent performance Documented processes measured and analyzed Defined & managed processes refined by ongoing process improvement activities Geospatial Data & Metadata: Internally focused Geospatial Data management Emerging, peer-to-peer Geospatial Data sharing arrangements Single-Point-Of-Truth principles Foundation Geospatial Data published, shared and maintained Ongoing monitoring and continuous improvement Geospatial Data duplication Some (meta) Geospatial Data publication Foundation Geospatial Data Themes defined All Geospatial Data published with compliant metadata Growing spatial Geospatial Data and open Geospatial Data usage throughout community Project-by-project Geospatial Data and metadata collection Open Geospatial Data policies established Open Geospatial Data policies implemented Maturity level Framework 14
- 15. Maturity level Framework 15 Maturity Levels Strategy Components Level 1 - Ad Hoc Level 2 - Repeatable Level 3 - Defined Level 4 - Managed Level 5 - Optimized Not coordinated or repeatable Based on the previous successful methodology Successful processes documented to guide consistent performance Documented processes measured and analyzed Defined & managed processes refined by ongoing process improvement activities Organizational: No inter organizational or No cross-government governance framework in place Initial whole-of- government coordination initiatives Whole-of- government governance structures established Mandates and legal frameworks in place Ongoing monitoring and continuous improvement No standard operating procedures (SOPs) identified, compliance and tracking not consistent Custodianship and stewardship principles defined SOPs consistently tracked and verified Formal custodianship and stewardship roles defined Measuring ROI and benefits realization Project-by-project funding Some SOPs documented Defined Strategy and Implementation Plan Strategy Implemented, KPIs monitored Case-by-case partnerships Some whole-of- government funded initiatives Whole-of- government investment plan Business case driven investments No market coordination or focus Public-Private partnerships Operational budget allocations No successful initiative in Geospatial Data Sporadic Geospatial Data sharing Inconsistent Geospatial Data sharing with Geospatial Data sharing in place but still immature Geospatial Data sharing is consistent, mature
- 16. Tried and Tested – an example from one country 47 Organizations visited Interviewed more than 150+ People 39 completed Questionnaires received 1000 Sample Datasets received 16
- 19. © Dr. Vanessa Lawrence CB, Gilles Albaredes, Key Findings: Current Maturity Levels for a country 19
- 20. Maturity Levels Strategy Components Level 1 - Ad Hoc Level 2 - Repeatable Level 3 - Defined Level 4 - Managed Level 5 - Optimized Not coordinated or repeatable Based on the previous successful methodology Successful processes documented to guide consistent performance Documented processes measured and analyzed Defined and managed processes refined by ongoing process improvement activities Data Standards People Organizational Technology Maturity Level Development 20 Once Maturity has been assessed, one can match one’s country or organization against ‘best practice’ from other countries or organizations to see the impact of implementing a SDI
- 21. Maturity Levels Strategy Components Level 1 - Ad Hoc Level 2 - Repeatable Level 3 - Defined Level 4 - Managed Level 5 - Optimized Data Standards People Organizational Technology Best Practice Maturity Levels– Combined 21
- 22. Also applied elsewhere, e.g. State Government
- 23. Now we have…. A defined, repeatable methodology Consistent & Measurable Evidence-based Tried & Tested So that we can…. Know where we are Measured by 5 dimensions Knowing how we ‘stack-up’ Set strategic goals & make plans Credible & Realistic Consistent with Best Practice Costed Implementation Plans Measure progress Against goals Comparative to others
- 24. THANK YOU Presented by: Maurits van der Vlugt Email: Maurits.vandervlugt@mercuryps.com.au Twitter: @mvandervlugt Co-Authors: • Dr. Vanessa Lawrence CB • Gilles Albaredes • John Schonegevel
Editor's Notes
- Overview: Spatial Infrastructures. Been around for a while, but are getting more important, and higher maturity levels are being demanded A method for assessing maturity practical example Where does that leave us? Abstract: Regional and National Spatial Data Infrastructures (SDIs) are essential in delivering the foundation spatial data layer that underpins the evidence base enabling policy analysis, planning and development. Such a trusted, complete, and authoritative evidence base, drives improved decision making and reduces the cost of regional and national government operations. Strategic approaches to establishing and further developing SDIs need to consider the current and desired maturity of the SDI environment. They need to have measurable outcomes, and be consistent with international best-practice, to allow progress tracking and comparisons. To date, such approaches are relatively rare. This paper presents an evidence-based, proven SDI maturity model that will enable such strategies to be developed, implemented and monitored. This paper will examine some of the challenges in the changing landscape of geospatial information, and its role in regional and national decision-making. It will then present the geospatial model used to assess an SDI’s maturity. As the model comes with documentation and templates, it can be easily applied across multiple geographies to compare approaches and best-practices. The model defines five key Strategic Components: data, technology, governance, standards and people; and includes definitions of Maturity for each of the components. The model is then applied in a in a four-stage assessment methodology: 1: As-Is Analysis & Best Practice study 2: Strategy Development 3: National or Regional Geospatial Policy Development 4: Implementation Planning The paper will conclude with a number examples where the model has been applied to assess the maturity development of several national SDIs
- Every location is now a beacon that can be sensed remotely by multiple devices
- Spatial is becoming integrated in BI, dashboards. Divide between spatial and non-spatial is disappearing
- Certain Geospatial Datasets are known as Foundation Datasets and others as Supplemental Datasets (the ones for decision making)
- Data as a factor of production
- No longer playpen & sandbox. Data as a factor of production
- developing SDIs need to consider the current and desired maturity of the SDI environment. They need to have measurable outcomes, and be consistent with international best-practice, to allow progress tracking and comparisons
- This model consists of five interrelated components, designed to ensure that the Strategy and Implementation Plans cover all the elements required for success, set within a user driven context, taking on board the local conditions in place The five components are: Organizational Data Technology Standards People
- Regional and National Spatial Data Infrastructures (SDIs) are essential in delivering the foundation spatial data layer that underpins the evidence base enabling policy analysis, planning and development. Such a trusted, complete, and authoritative evidence base, drives improved decision making and reduces the cost of regional and national government operations. Strategic approaches to establishing and further developing SDIs need to consider the current and desired maturity of the SDI environment. They need to have measurable outcomes, and be consistent with international best-practice, to allow progress tracking and comparisons. To date, such approaches are relatively rare. This paper presents an evidence-based, proven SDI maturity model that will enable such strategies to be developed, implemented and monitored. This paper will examine some of the challenges in the changing landscape of geospatial information, and its role in regional and national decision-making. It will then present the geospatial model used to assess an SDI’s maturity. As the model comes with documentation and templates, it can be easily applied across multiple geographies to compare approaches and best-practices. The model defines five key Strategic Components: data, technology, governance, standards and people; and includes definitions of Maturity for each of the components. The model is then applied in a in a four-stage assessment methodology: 1: As-Is Analysis & Best Practice study 2: Strategy Development 3: National or Regional Geospatial Policy Development 4: Implementation Planning The paper will conclude with a number examples where the model has been applied to assess the maturity development of several national SDIs