2e:null 2f:["$","title",null,{"children":"A²CM² | Advanced Analytics Capability Maturity Model | Aaron Kyle Dennis | Observable"}] 34:T15bc,aacmm = [{ "title": "Advanced Analytics Capability Maturity Model", "acronym": "A²CM²", "hierarchy": [ "attribute", "category", "subcategory" ], "attributes": [ { "name": "Analytic Opportunities", "description": "Identifies new and existing use cases to further apply advanced analytics to improve organization mission and operations.", "categories": [ { "name": "Develop Opportunities", "subcategories": [ "Opportunity Identification", "Opportunity Selection" ] }, { "name": "Manage Projects", "subcategories": [ "Project Portfolio", "Project Resources", "Project Review", "Project Validation" ] }, { "name": "Execute Solutions", "subcategories": [ "Solution Implementation", "Solution Evaluation" ] } ] }, { "name": "Data", "description": "Identifies opportunities to leverage new and existing data sets and better manage and govern data in support of advanced analytics projects.", "categories": [ { "name": "Data Management", "subcategories": [ "Data Management Strategy", "Data Governance Model", "Data Requirements Lifecycle" ] }, { "name": "Data Operations", "subcategories": [ "Data Standards & Procedures", "Data Access", "Data Collection", "Data Sourcing", "Data Persistence" ] }, { "name": "Data Quality", "subcategories": [ "Data Quality Framework", "Data Quality Assurance" ] } ] }, { "name": "Analytic Techniques", "description": "Identifies the analytic tradecraft and techniques that may be applied in order to generate insights from data.", "categories": [ { "name": "Data Preparation & Manipulation", "subcategories": [ "Organize Structured Data", "Organize Unstructured Data" ] }, { "name": "Analytic Tradecraft", "subcategories": [ "Data Analysis", "Data Visualization", "Reporting and Distribution" ] } ] }, { "name": "People", "description": "Identifies the set of human capital programs required to develop a talented and capable team of advanced analytics practitioners.", "categories": [ { "name": "Talent Definition", "subcategories": [ "Role Definition", "Position Requirements" ] }, { "name": "Talent Recruitment", "subcategories": [ "Attracting Talent", "Sourcing Talent", "Hiring Talent" ] }, { "name": "Talent Placement", "subcategories": [ "Workforce Planning", "Workforce Management", "Workforce Design" ] }, { "name": "Talent Development", "subcategories": [ "Talent Management Strategy", "Career Development", "Performance Management", "Retention Strategies" ] } ] }, { "name": "Technology", "description": "Identifies the optimal ways to leverage new and existing technologies including applications, data platforms, and infrastructure to perform advanced analytics projects.", "categories": [ { "name": "Planning & Development", "subcategories": [ "Analytics Technology Strategy", "Planning Review", "Technology Research", "Internal Development", "Purchasing New Tools", "Implementation & Deployment", "Maintenance & Support" ] }, { "name": "Infrastructure", "subcategories": [ "Physical Resources", "Resource Abstraction", "Core Services" ] }, { "name": "Data Management", "subcategories": [ "Data Repository", "Data Sources" ] }, { "name": "Analytics Services & Interaction", "subcategories": [ "Analytics Services", "Tools & Software" ] }, { "name": "Human Insights & Actions", "subcategories": [ "Visualization Tools", "Interfaces" ] } ] }, { "name": "Culture", "description": "Identifies the set of organizational mechanisms that reinforce, communicate, and share the importance of advanced analytics to support evidence-based decision making.", "categories": [ { "name": "Engagement", "subcategories": [ "Communications", "Marketing & Branding", "Leadership", "Recognition" ] }, { "name": "Organizational Enablers", "subcategories": [ "Structural Mechanisms", "Policies & Procedures", "Community", "Learning" ] } ] } ] }]35:Ta57,The Social Security Administration (SSA) Analytics Center of Excellence created the Advanced Analytics Capability Maturity Model (A²CM²) to serve as an organizational assessment framework to help federal agencies understand, strengthen, and systematically improve their capacity to use data and analytics. Published on February 6, 2020, the model responds to Office of Management and Budget guidance calling on agencies to evaluate their data-related policies, practices, infrastructure, workforce, and organizational culture; identify capability gaps; and use the findings to prioritize investments and improvement actions. A²CM² treats analytics capability as an enterprise-wide organizational system—not simply a matter of acquiring better software or hiring data scientists. It evaluates six mutually supporting dimensions: 1. **Analytic Opportunities:** identifying, selecting, governing, implementing, and evaluating useful analytics projects. 2. **Data:** managing, governing, accessing, sourcing, storing, and assuring the quality of data. 3. **Analytic Techniques:** applying appropriate methods to analyze, visualize, report, and communicate information. 4. **Technology:** providing the strategy, infrastructure, platforms, tools, and interfaces needed to support analytical work. 5. **People:** developing the roles, skills, staffing practices, training, and career structures required for a capable workforce. 6. **Culture:** establishing leadership support, organizational norms, collaboration, communication, and incentives for evidence-informed decision-making. Each dimension is divided into categories and detailed subcategories, which are assessed against five evidence-based maturity levels. These levels progress from a capability that has not been addressed, through ad hoc and formally defined practices, to consistently governed practices and, ultimately, continuous improvement. The model also distinguishes between improvements that an individual organizational component can achieve and those requiring enterprise-level governance or shared institutional action. A²CM² is therefore best understood as both a diagnostic framework and a planning tool. It can provide a point-in-time picture of organizational capability, expose unevenness across different dimensions, clarify the evidence needed to demonstrate maturity, and support development of a sequenced improvement roadmap. Its central premise is that sustainable analytics capability emerges when mission needs, data, methods, technology, people, and organizational culture mature together—not when any one of these areas advances in isolation.36:T530, ## How the model works The A²CM² has four structural layers: |Layer|What it represents| | --- | --- | |**Attribute**|One of the six broad organizational dimensions| |**Category**|A major capability area within an attribute| |**Subcategory**|A specific practice or capability that can be assessed| |**Maturity level**|The organization’s current degree of capability for that subcategory| The model contains **6 attributes, 19 categories, and 59 subcategories**. Each subcategory is evaluated against five levels. |Level|General meaning| | --- | --- | |**1 — Initial**|The capability has not meaningfully been addressed| |**2 — Managed/ad hoc**|It is performed inconsistently or reactively| |**3 — Defined**|A formal, repeatable process exists| |**4 — Governed**|The process is consistently applied, monitored, and controlled| |**5 — Optimizing**|Results and processes are regularly reviewed for continuous improvement| A particularly important observation in the presentation is that **moving from Level 2 to Level 3 is usually the hardest and most resource-intensive step**. This is where informal practices must become documented roles, standards, procedures, systems, and organizational commitments. Moving from Level 4 to Level 5 may require more refinement and efficiency than substantial new resources. 37:T44f, ## What A²CM² says a mature organization must possess |Dimension|What maturity means in practice| | --- | --- | |**Analytic opportunities**|A formal way to identify, select, resource, govern, validate, implement, and evaluate analytics projects| |**Data**|Enterprise strategies, governance structures, standards, access processes, sourcing, storage, and quality assurance| |**Analytic techniques**|Repeatable data preparation, analysis, visualization, reporting, and model-validation practices| |**People**|Defined roles, recruitment pipelines, workforce planning, career paths, performance measures, and retention strategies| |**Technology**|Strategic planning, architecture, platforms, APIs, tools, deployment processes, maintenance, and user interfaces| |**Culture**|Leadership behavior, communications, incentives, policies, communities of practice, and organizational learning| At higher maturity levels, these practices become enterprise-wide, aligned with business objectives, monitored by governance bodies, integrated into future planning, supported by automation, and regularly improved. 38:T407, ## Attribute definitions | Attribute | Definition | |---|---| | **Analytic Opportunities** | Identifies new and existing use cases to further apply advanced analytics to improve organization mission and operations | | **Data** | Identifies opportunities to leverage new and existing data sets and better manage and govern data in support of advanced analytics projects | | **Analytic Techniques** | Identifies the analytic tradecraft and techniques that may be applied in order to generate insights from data | | **People** | Identifies the set of human capital programs required to develop a talented and capable team of advanced analytics practitioners | | **Technology** | Identifies the optimal ways to leverage new and existing technologies including applications, data platforms and infrastructure to perform advanced analytics projects | | **Culture** | Identifies the set of organizational mechanisms that reinforce, communicate, and share the importance of advanced analytics to support evidence based decision making | 39:T4b4,html` `3a:T659,

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and\n* turn assessment findings into a sequenced improvement roadmap.\n\nThe presentation connects this purpose to OMB expectations that maturity assessments examine governance, management, culture, systems, analytics, workforce capacity, resources, and legal or policy compliance.\n\nIt is therefore **not just a diagnostic scorecard**. Its purpose is to support decisions about what capabilities should be built, standardized, governed, measured, and improved.\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":110,"value":"$36","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":111,"value":"$37","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":9,"value":"\n## One of its most useful ideas: enterprise versus component responsibility\n\nThe model recognizes that an individual office can improve many practices itself, but **some maturity levels can only be achieved by the enterprise**. For example, an office cannot independently create an agency-wide governance model, common architecture, enterprise resource-management function, or standardized workforce system.\n\nThe A²CM² therefore marks certain levels as “enterprise” levels. A component should not be penalized for failing to achieve a capability that requires agency-wide authority, funding, policy, infrastructure, or governance.\n\nThis distinction is highly valuable because it separates:\n\n* **capabilities an office controls;**\n* **capabilities requiring cooperation among offices;** and\n* **capabilities requiring executive or enterprise action.**\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":27,"value":"# Complete Definitions","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":115,"value":"\n## Extraction summary\n\n| Definition type | Count |\n|---|---:|\n| Attributes | 6 |\n| Categories | 19 |\n| Subcategories | 59 |\n| Subcategory maturity-level criteria | 295 |\n| Generic maturity-level descriptions | 5 |\n| Structural terms | 4 |\n\nWhitespace and line wrapping were normalized, and obvious PDF extraction joins were corrected. Source wording was otherwise retained.\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":116,"value":"\n## Model structure\n\n| Term | Definition |\n|---|---|\n| **Attribute** | The six main categories that must be covered to build an analytics capability; their definitions describe what each attribute includes and why it is important. |\n| **Category** | The areas in which the organization’s maturity is assessed and explained, typically including 2-6 sub-categories. |\n| **Sub-category** | The smallest elements of the model; each represents an area in which the organization should seek maturity. |\n| **Maturity level** | For each sub-category, five levels of maturity (1-5) are provided. An N/A option is relevant for sub-organizations with no responsibility in a given area. |\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":117,"value":"\n## Generic maturity levels\n\n| Level | Name | General definition |\n|---:|---|---|\n| 1 | Initial | The sub-category has not been addressed |\n| 2 | Managed | The sub-category has been addressed in an ad hoc manner |\n| 3 | Defined | The sub-category has been addressed formally |\n| 4 | Quantitatively Managed | The sub-category is consistently addressed and its use is governed |\n| 5 | Optimizing | The sub-category is reviewed regularly to enable continuous improvement |\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":118,"value":"$38","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":64,"value":"$39","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":128,"value":"\n## Category and subcategory definitions\n\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":98,"value":"$3a","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":120,"value":"$3b","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":202,"value":"## Subcategory maturity-level definitions","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":123,"value":"$3c","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":32,"value":"import {pdfView} from \"@aaronkyle/pdf-view\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":60,"value":"a2cm2AllDefinitions = FileAttachment(\"a2cm2-all-definitions.json\").json()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":61,"value":"a2cm2CapabilityModel = FileAttachment(\"a2cm2-capability-model.json\").json()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":205,"value":"import {toc} from \"@aaronkyle/toc\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W3d","stdlib":"1","titling":"auto"}} 33:"$32:body"