bkjohn2018
- 71 skills
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- ▌ Sop Writing · bkjohn2018Writes governance-ready standard operating procedures with precise scope, role accountability, step controls, and audit-ready evidence requirements. Use when users ask to draft, improve, or standardize SOPs for operational, finance, or data governance processes.
- ▌ Data Profiling · bkjohn2018Profiles datasets to establish structural fitness — structure, completeness, uniqueness, distributions, and anomalies — as a prerequisite gate, not an analytical finding in itself. Per Tukey's original framing (Bruce, Bruce & Gedeck, *Practical Statistics for Data Scientists*), exploratory data analysis presupposes data already "processed and manipulated into a structured form"; this skill is what establishes that, for either a data engineering build or an analytics project — it is not EDA itself. Use when onboarding a new table, validating source readiness, or when users ask for a data profile.
- ▌ Problem Triage · bkjohn2018Routes ambiguous business, data, process, organizational, or technology problems to the lightest useful response mode. Use before deeper diagnosis when deciding between quick answer, focused diagnostic, full diagnostic, facilitation guide, executive brief, or artifact.
- ▌ System Sensing · bkjohn2018Describes what a business, data, process, organizational, or technology system appears to be showing before diagnosing causes. Use when symptoms may reflect deeper patterns across people, process, technology, data, governance, incentives, or timing.
- ▌ Data Governance · bkjohn2018Designs and operationalizes DAMA-DMBOK aligned data governance, including readiness assessment, operating framework, decision rights, policy lifecycle, glossary ownership, issue management, and regulatory alignment. Use when users need to establish or strengthen data governance programs. Use data-standards-management for detailed data standard requirements and control mappings.
- ▌ Edge Diagnostics · bkjohn2018Diagnoses stressed relationships before blaming people, tools, or teams. Use when analyzing handoffs, feedback loops, ownership boundaries, definitions, timing, incentives, trust, governance, data lineage, interfaces, or informal workarounds.
- ▌ Discovery Analyst · bkjohn2018Operates as a Discovery Analyst to convert ambiguous raw material into classified, structured project artifacts. Extracts requirements, documents assumptions, drafts specifications, and prepares promotion-ready artifacts. Use when working in a project discovery workspace, classifying intake material, drafting requirements or specs, or preparing a promotion assessment.
- ▌ Evidence Planning · bkjohn2018Defines the evidence needed to validate diagnostic claims, root-cause hypotheses, and intervention choices. Use when diagnosing business, data, process, organizational, governance, or technology issues where confidence depends on interviews, data pulls, process traces, logs, lineage, observations, or decision history.
- ▌ Metric Governance · bkjohn2018Governs specific metric definitions, calculation rules, ownership, and approval lifecycle. Use when resolving metric disputes, documenting official KPI definitions, or publishing metric governance records. Use data-standards-management when defining enterprise-wide metric standard requirements.
- ▌ Discovery Workspace · bkjohn2018Operate inside a structured Discovery Workspace for project discovery, analysis, and planning. Enforces folder discipline, draft status, promotion criteria, sensitive-material handling, and an end-of-pass report. Use when the user is doing discovery, intake, requirements, specs, or asks to promote files to a formal repository.
- ▌ Facilitation Design · bkjohn2018Designs facilitation flows for diagnosing business, data, process, organizational, governance, or technology issues with stakeholders. Use when a user needs to lead a workshop, retrospective, governance session, operating review, or stakeholder alignment discussion.
- ▌ Intervention Sizing · bkjohn2018Sizes recommendations for business, data, process, organizational, governance, or technology issues as quick fixes, controlled pilots, structural changes, or transformations. Use when moving from diagnosis to action while avoiding oversized solutions.
- ▌ Dimensional Modeling · bkjohn2018Designs dimensional models using Kimball-first methods, including the four-step process, star schema patterns, conformed dimensions, and bus matrix planning, while incorporating complementary Hoberman techniques for clarity and quality. Use when building analytical marts, defining fact/dimension structures, or standardizing enterprise-ready dimensional models.
- ▌ Learning Loop Design · bkjohn2018Designs feedback loops, indicators, review cadence, and decision checkpoints to determine whether a system intervention is working. Use after recommendations, pilots, controls, governance changes, process repairs, or technology changes where sustained improvement must be monitored.
- ▌ Metadata And Lineage · bkjohn2018Documents technical and business metadata plus upstream/downstream lineage for specific data assets, metrics, dashboards, reports, or integrations. Use when users ask for lineage mapping, impact analysis, or asset-level metadata documentation. Use data-standards-management when defining enterprise metadata requirements or standards.
- ▌ Data Issue Management · bkjohn2018Manages data issues through triage, severity scoring, owner assignment, remediation tracking, and closure validation. Use when users need an issue workflow for data defects.
- ▌ Data Quality Controls · bkjohn2018Designs preventive and detective controls for data quality with thresholds, alerts, and owner response playbooks. Use when implementing data correctness monitoring, validation rules, defect alerts, or remediation routing. Use internal-control-design for broader COSO-style control matrices, risk-control mapping, evidence, deficiencies, and remediation.
- ▌ Analytics Storytelling · bkjohn2018Converts analytical findings into decision-oriented narratives and focused visuals using Storytelling with Data principles, including context, decluttering, attention guidance, and action-focused messaging. Use when users ask for insight communication, visual narrative design, or stakeholder-ready analysis summaries.
- ▌ Babysit · bkjohn2018Keep a PR merge-ready by triaging comments, resolving clear conflicts, and fixing CI in a loop.
- ▌ Build Governance Bundle · bkjohn2018Orchestrates a complete governance package across multiple writing, data governance, and analytics skills. Use when users ask for an end-to-end governance bundle for a domain such as AP, AR, CM, or GL analytics.
- ▌ Data Quality Assessment · bkjohn2018Assesses data quality across completeness, validity, consistency, timeliness, and uniqueness. Use when users ask for data quality scoring, readiness decisions, or remediation priorities.
- ▌ Data Strategy Lifecycle · bkjohn2018Creates and manages enterprise data strategy from minimum viable data governance through a mature data management Center of Excellence. Use when developing data strategy, data management strategy, MVDG, data governance roadmap, data capability roadmap, or CoE transition plans.
- ▌ Data Strategy Scorecard · bkjohn2018Defines scorecards for data strategy, governance, data management maturity, CoE performance, quality, metadata, adoption, value, and risk reduction. Use when measuring data strategy execution, MVDG progress, roadmap outcomes, or CoE effectiveness.
- ▌ Internal Control Design · bkjohn2018Designs and reviews internal controls for finance, reporting, compliance, data governance, analytics, and operational processes using COSO-style internal control concepts. Use when mapping risks to controls, assessing control completeness across control environment, risk assessment, control activities, information and communication, and monitoring, or defining control owner, performer, reviewer, frequency, evidence, deficiency, and remediation requirements. Use data-security-and-privacy-controls for NIST-style security/privacy controls and data-quality-controls for data correctness monitoring.
- ▌ Pbip Build Verification · bkjohn2018Checks a built Power BI project (.pbip / TMDL / PBIR) against its approved `_brief/report-spec.md` (the `powerbi-report-planning` + `powerbi-report-design` output) and reports spec-versus-build divergence — field bindings, sort policy, color-map/conditional-formatting conformance, and semantic-model governance. Use when a Power BI report has been built or modified from an approved report spec and needs a pre-reload or pre-handoff check. Use dashboard-metric-semantics instead when the metric definitions themselves still need to be authored, not verified; use dashboard-frontend-implementation instead for generic (non-Power BI) dashboard UI; use powerbi-report-design instead to author or revise the brief itself.
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- ▌ Data Coe Operating Model · bkjohn2018Designs a data management or analytics Center of Excellence operating model with charter, services, roles, intake, advisory reviews, standards, enablement, community practices, metrics, and continuous improvement. Use when creating or maturing a Data CoE, governance CoE, analytics CoE, or data management shared service.
- ▌ Diagnostic Scope Control · bkjohn2018Defines scope, unknowns, decision support, owner, and time horizon for diagnostic work. Use when a business, data, process, organizational, or technology problem could expand beyond the user's real decision need.
- ▌ Finance Dashboard Design · bkjohn2018Designs finance, governance, and operating dashboards around governed metrics, decision workflows, and clear visual hierarchy. Use when building or improving KPI-heavy dashboards for leadership and operating teams, especially when metric trust and drill-path clarity matter.
- ▌ Reconciliation Analytics · bkjohn2018Performs reconciliation analysis between systems, ledgers, and reports to identify breaks, root causes, and corrective actions. Use when validating financial consistency across sources.
- ▌ Dashboard Product Framing · bkjohn2018Frames dashboard and analytics webspace work around users, decisions, operating workflows, and business value. Use when users provide a screenshot, vague dashboard idea, or request to design a dashboard before metrics, pages, or frontend implementation are defined.
- ▌ Data Standards Management · bkjohn2018Defines and maintains enterprise data standards for classification, access, quality, metadata, lineage, retention, integration, reference/master data, metrics, and analytical models. Use when creating a data standards catalog, mapping standards to DAMA-DMBOK capabilities and NIST SP 800-53 control considerations, or deciding what baseline requirements data products must satisfy. Use data-security-and-privacy-controls for asset-level security/privacy control design, policy-and-standard-writing for final mandatory language, and domain skills for implementation.
- ▌ Executive Summary Writing · bkjohn2018Produces concise executive summaries that emphasize decision context, material findings, business impact, and recommended actions. Use when users need leadership-ready summaries for analysis, governance updates, audits, or transformation initiatives.
- ▌ Dashboard Metric Semantics · bkjohn2018Defines dashboard KPI semantics, status logic, thresholds, comparators, and drill-down meaning so metrics remain trustworthy and actionable. Use when dashboards need metric cards, trend indicators, health rings, status chips, or governed KPI definitions.
- ▌ Finance AI Safe Use Policy · bkjohn2018Creates and maintains AI Safe Use Policy requirements for finance and accounting teams, including permitted and prohibited use, approval tiers, data handling, human review, disclosure, exceptions, and review cadence. Use when drafting or updating AI safe-use boundaries, policy requirements, standards, or governance guidance for finance AI use.
- ▌ Finance AI Use Case Intake · bkjohn2018Captures and triages proposed AI use cases for finance and accounting teams before use, build, purchase, or deployment. Use when evaluating AI requests, AI pilots, embedded vendor AI, assistants, copilots, models, automations, or agents for business purpose, data sensitivity, process impact, risk tier, approvals, and required assessments.
- ▌ Systems Failure Mode Check · bkjohn2018Checks diagnostic and recommendation failure modes in complex business, data, process, organizational, governance, or technology issues. Use before finalizing recommendations when symptoms may be misleading, data may reflect broken processes, or fixes may shift burden elsewhere.
- ▌ Data Capability Roadmapping · bkjohn2018Builds phased data capability roadmaps across DAMA-DMBOK areas, sequencing initiatives by business value, risk, maturity, dependencies, feasibility, and adoption readiness. Use when turning a data strategy, maturity assessment, MVDG launch, or CoE target state into an actionable roadmap.
- ▌ Data Governance Mvdg Launch · bkjohn2018Launches minimum viable data governance with lightweight sponsorship, priority scope, decision rights, ownership, glossary, standards, issue management, and adoption measures. Use when starting data governance pragmatically, creating an MVDG plan, or moving from informal data ownership to repeatable governance.
- ▌ Data Management Foundations · bkjohn2018Applies DAMA-DMBOK aligned data management foundations across strategy, architecture, governance, quality, metadata, security, and lifecycle controls. Use when users ask for enterprise data management frameworks, operating models, role design, or maturity roadmaps. Use data-standards-management for detailed standards catalogs and data control requirements.
- ▌ Data Model Scorecard Review · bkjohn2018Reviews conceptual, logical, and physical data models using Data Model Scorecard categories to produce structured findings, scores, and remediation plans. Use when users request model quality validation, review readiness checks, or formal data model QA.
- ▌ Financial Variance Analysis · bkjohn2018Analyzes actual-vs-plan and period-over-period financial variances against predefined dimensions (entity, account, product, region) using standard volume/rate/mix decomposition, with business interpretation. Use when finance teams need variance narratives and action-focused insights explained against known categories. Use `predictive-model-development` instead when the explanatory grouping itself is unknown and must be discovered (e.g., clustering or segmentation to find which vendors, invoice types, or processors are driving a pattern).
- ▌ Governance Ppt Deck Writing · bkjohn2018Structures governance presentation decks with clear decision narrative, control status, risk signals, and action tracking. Use when preparing steering committee, risk committee, audit, or executive governance slide decks.
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- ▌ Policy And Standard Writing · bkjohn2018Writes formal governance policies and standards in mandatory, approvable language with control intent, scope boundaries, accountability, exceptions, and review cadence. Use when converting approved requirements into policy documents, standards, or addendums. Use data-standards-management first when deciding data standard domains, requirements, evidence, or NIST/DAMA control mapping.
- ▌ Business Glossary Management · bkjohn2018Defines and maintains governed business terms, canonical metric language, and approved synonyms across domains. Use when creating or updating a business glossary, resolving terminology conflicts, or standardizing definitions used in analytics, finance, and governance artifacts.
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- ▌ AI Agent Readiness Assessment · bkjohn2018Assesses whether an AI agent or agentic workflow is ready for finance and accounting use based on autonomy, tool access, data sensitivity, control impact, human approval, failure modes, logging, monitoring, rollback, evidence, and recertification. Use before deploying, approving, expanding, or materially changing an AI agent.
- ▌ Architecture Ppt Deck Writing · bkjohn2018Structures architecture, operating model, capability model, governance framework, and transformation concept decks with clear visual hierarchy, decision narrative, layered explanation, reusable patterns, and implementation path. Use when turning architecture guides, governance models, operating models, or framework visuals into executive or stakeholder PowerPoint decks.
- ▌ Process And Procedure Writing · bkjohn2018Writes clear process and procedure documentation with roles, steps, controls, and handoff criteria. Use when documenting repeatable operational workflows.
- ▌ Question Driven Data Projects · bkjohn2018Frames analytics work around business questions, strategic objectives, available data realities, and decision value. Use when defining analysis scope, shaping data projects, or when users ask to start with the right questions before selecting methods, models, or AI.
- ▌ Root Cause Hypothesis Testing · bkjohn2018Frames possible root causes as testable hypotheses for business, data, process, organizational, or technology problems. Use after system sensing or edge diagnostics, or when the user explicitly asks for root-cause hypotheses.
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- ▌ Executive Diagnostic Synthesis · bkjohn2018Produces concise leadership-ready summaries from system diagnostic work. Use after system sensing, edge diagnostics, root-cause hypotheses, evidence planning, or intervention sizing when a user needs an executive brief, answer-first diagnostic synthesis, evidence confidence, risks of premature action, or immediate next steps.
- ▌ Governance Writing Style Guide · bkjohn2018Applies consistent governance writing standards for tone, structure, terminology, and policy clarity. Use when drafting or editing governance documents, controls narratives, and standards.
- ▌ System Aware Diagnostic Kernel · bkjohn2018Guides system-aware business, data, process, organizational, and technology diagnosis. Use when a user asks to diagnose a complex, recurring, ambiguous, cross-functional, political, or high-risk issue without rushing to premature solutions.
- ▌ Adoption And Ownership Planning · bkjohn2018Defines ownership, decision rights, stakeholder roles, communication narrative, resistance, trust-building moves, and sustainment responsibilities for diagnostic recommendations. Use when business, data, process, governance, control, or technology changes must be adopted and operated by people.
- ▌ Finance AI Risk Control Mapping · bkjohn2018Maps finance and accounting AI risks to governance, security, privacy, data, and internal control requirements using NIST AI RMF, NIST SP 800-53 concepts, DAMA-DMBOK, and finance control practices. Use when assessing AI use cases, agents, models, assistants, vendor AI, or automation for control objectives, owners, evidence, residual risk, and approval conditions.
- ▌ Finance Documentation Lifecycle · bkjohn2018 bundleControls the lifecycle of finance and accounting documentation after or alongside content authoring: intake, metadata, review, approval, publishing, access, version control, retention, revision, retirement, and audit evidence. Use when users need ISO 9001:2015 clause 7.5-aligned document governance for SOPs, control procedures, reconciliation guides, reporting documentation, data definitions, analytics documentation, or work instructions. For drafting the document content itself, use the more specific SOP, procedure, policy, glossary, metadata, metric, dashboard, or analytics skills first.
- ▌ Dashboard Frontend Implementation · bkjohn2018Implements dashboards and analytics webspaces through reusable frontend components, data contracts, mock-first development, and clear interaction states. Use when building the actual UI for dashboard pages, app shells, KPI cards, filters, and drill-down views.
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- ▌ Dashboard Information Architecture · bkjohn2018Designs page hierarchy, navigation, section structure, and drill paths for analytics webspaces and operational dashboards. Use when translating dashboard requirements into page architecture, app shell design, or drill-down flows.
- ▌ Data Security And Privacy Controls · bkjohn2018Designs data security and privacy controls for sensitive, regulated, financial, and business-critical data using NIST SP 800-53 Rev. 5 control concepts. Use when assessing or defining controls for data access, privacy, PII handling, encryption, logging, monitoring, sharing, retention, segregation of duties, or security exceptions. Use data-standards-management for enterprise standard requirements and use data-governance for operating model and decision rights.
- ▌ Governance Dashboard Content Model · bkjohn2018Defines the domain objects, relationships, statuses, and lifecycle states needed for governance and finance-led operating dashboards. Use when designing dashboards for policies, controls, evidence, issues, certifications, lineage, or audit readiness.
- ▌ Data Management Maturity Assessment · bkjohn2018Assesses data management maturity across DAMA-DMBOK capability areas and produces scored findings, gaps, priorities, and maturity improvement recommendations. Use when evaluating current data capability, governance maturity, metadata maturity, quality maturity, or readiness for a data strategy or CoE.
- ▌ Data Model Requirements And Quality · bkjohn2018Captures and validates data model requirements using Hoberman-style conceptual/logical framing plus Data Model Scorecard quality categories, designed to complement Kimball dimensional delivery. Use when users need better model clarity, scope control, and formal model quality scoring before implementation.
- ▌ System Diagnostic Command Reference · bkjohn2018Orchestrates modular system-aware diagnostic skills into command-style workflows such as quick scan, focused diagnostic, full diagnostic, edge map, root-cause hypotheses, evidence plan, facilitation guide, executive brief, and artifact builder.
- ▌ People Process Technology Diagnostics · bkjohn2018Maps People, Process, and Technology interactions in complex business, data, operational, governance, or technology issues. Use when a problem spans ownership, decision rights, workflow, handoffs, controls, systems, data, integrations, reports, automation, or adoption.
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