As a part of the global industrial organization Marmon Holdings—which is backed by Berkshire Hathaway—you’ll be doing things that matter, leading at every level, and winning a better way. We’re committed to making a positive impact on the world, providing you with diverse learning and working opportunities, and fostering a culture where everyone’s empowered to be their best.
The Fleet Management Data Analyst (SIOP) owns the coordination, integrity, and readiness of data that powers the Sales, Inventory & Operations Planning process. This role ensures a single source of truth for demand, supply, and inventory, orchestrates data gathering across functions and time zones, validates inputs prior to each SIOP cycle, and publishes trusted datasets and dashboards that drive decisions. The ideal candidate blends strong analytics skills with supply chain process knowledge, brings financial acumen for cross-functional alignment between Operations and Accounting/Finance and stakeholder facilitation.
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Data Intake & Integration
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Coordinate ingestion and refresh of data from ERP, CRM, WMS, MRP/APS, supplier portals, and other internal/external sources.
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Partner with Data Engineering/IT to define robust, documented pipelines (e.g., ETL/ELT, Power Query, ADF/Synapse/Databricks).
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Maintain source-to-target mapping, data lineage, refresh frequency, and cutover windows aligned to the SIOP calendar.
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Data Quality & Governance
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Define and operationalize data quality rules (accuracy, completeness, consistency, timeliness, uniqueness) and exception handling.
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Build automated validation and reconciliation checks (e.g., bookings-to-billings, shipments vs. inventory movements, open orders, backlogs, BOM/route consistency).
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Serve as a steward for master data (items/SKUs, customer hierarchies, locations/plants, calendars, units of measure); coordinate fixes and change controls.
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SIOP Calendar & Readiness
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Own the data readiness checklist for demand review, supply review, pre‑SIOP, and executive SIOP.
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Enforce cutoffs, freeze windows, and audit trails; publish “data is green” status and issues list before each meeting.
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Coordinate cross-functional inputs from Sales, Operations, Procurement, Finance, and Logistics.
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Analytics, KPIs & Reporting
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Design, develop, and maintain dashboards and analytical models to support SIOP decision-making and performance measurement.
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Define, track, and report on key SIOP and fleet management metrics, ensuring alignment with business goals and continuous improvement initiatives.
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Maintain and continuously improve KPI definitions and calculations, including:
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Forecast Accuracy (MAPE/WAPE), Forecast Bias
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Service Level, OTIF/Fill Rate, Backorder Rate
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Inventory Turns, Days of Inventory on Hand (DOH), Excess & Obsolete (E&O)
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Plan Adherence, Schedule Attainment, Capacity Utilization
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Integrate financial data into operational analytics to provide insights on cost drivers, budget adherence, and profitability across the fleet equipment/product group portfolio.
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Partner with Accounting/Finance to interpret financial statements, forecast impacts of operational decisions, and translate findings into actionable recommendations for cross-functional teams.
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Variance & Root-Cause Analysis
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Investigate demand spikes/dips, supply constraints, lead-time shifts, and inventory discrepancies; quantify business impact.
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Facilitate corrective actions with owners, document and track to closure.
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Change Management & Enablement
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Create SOPs, data definitions, and process playbooks, train super-users and planners on new datasets, checks, and tools.
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Champion continuous improvement to reduce manual effort, increase transparency, and shorten SIOP cycle time.
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Compliance & Controls
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Maintain audit-ready documentation for key data transformations and KPI calculations.
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Support internal control requirements for data changes, approvals, and segregation of duties.
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Bachelor’s degree in a related field is preferred
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Experience with Microsoft Dynamics 365 Finance & Operations (D365 F&O) (e.g., sales order, inventory/on-hand, InventTrans, demand forecast, master planning entities).
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Cloud data stack exposure: Azure Data Factory, Synapse/Databricks, Data Lake; or equivalent.
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SIOP Planning tools exposure (e.g., Kinaxis RapidResponse, SAP IBP, o9, Anaplan, or similar).
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Python or R for advanced data validation or statistical analysis; familiarity with time-series methods.
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Power Automate or similar workflow tools for exception routing and approvals.
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Experience integrating external signals (e.g., POS, distributor sell‑thru, market indices) into demand or inventory analyses.
Following receipt of a conditional offer of employment, candidates will be required to complete additional job-related screening processes as permitted or required by applicable law.