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Key Responsibilities and Required Skills for a Production Analyst

💰 $65,000 - $95,000

AnalyticsOperationsData AnalysisManufacturingSupply Chain

🎯 Role Definition

The Production Analyst is the analytical heart of our operations, acting as a critical link between raw production data and strategic business decisions. You are the detective and the storyteller, digging into complex datasets to identify trends, uncover inefficiencies, and pinpoint opportunities for improvement. Your insights directly impact production efficiency, product quality, and the bottom line. This role isn't just about crunching numbers; it's about translating those numbers into actionable strategies that empower production teams, guide leadership, and drive a culture of continuous improvement across the organization. You'll be the go-to expert for understanding "what" is happening on the production floor and "why."

📈 Career Progression

Typical Career Path

Entry Point From:

  • Junior Data Analyst
  • Production Coordinator
  • Quality Control Technician

Advancement To:

  • Senior Production Analyst
  • Operations Manager
  • Continuous Improvement Manager

Lateral Moves:

  • Supply Chain Analyst
  • Business Intelligence (BI) Analyst

Core Responsibilities

Primary Functions

  • Monitor, analyze, and report on key production metrics, including but not limited to throughput, cycle time, yield, scrap rates, and Overall Equipment Effectiveness (OEE).
  • Develop and maintain comprehensive dashboards and performance scorecards using BI tools like Tableau or Power BI to provide leadership with real-time visibility into operational performance.
  • Conduct deep-dive root cause analysis on production variances, equipment downtime, and quality issues, presenting findings and recommending robust corrective actions.
  • Collaborate with production planning and supply chain teams to analyze production capacity and constraints, ensuring alignment with demand forecasts and material availability.
  • Identify and champion process improvement opportunities by applying methodologies like Lean Manufacturing or Six Sigma to reduce waste, shorten lead times, and enhance product quality.
  • Translate complex production data into clear, concise, and actionable insights for non-technical stakeholders, including plant managers and executive leadership.
  • Build and automate data collection and reporting processes to improve data accuracy and reduce manual effort, freeing up time for more value-added analysis.
  • Analyze production cost structures, including labor, materials, and overhead, to identify cost-saving opportunities and support budgeting and forecasting activities.
  • Create detailed models to simulate the impact of process changes, new equipment, or altered workflows on production output and efficiency before implementation.
  • Partner with IT and engineering teams to ensure the integrity and reliability of data captured from Manufacturing Execution Systems (MES) and Enterprise Resource Planning (ERP) systems.
  • Prepare and present regular operational performance reviews, highlighting key trends, achievements, and areas requiring attention.
  • Support new product introductions (NPI) by analyzing production trial data, establishing baseline metrics, and identifying potential manufacturing challenges.
  • Develop standard operating procedures (SOPs) for data analysis and reporting to ensure consistency and best practices across the team.
  • Manage the production database, performing queries (SQL) to extract, manipulate, and validate data for various analytical projects.
  • Evaluate the effectiveness of implemented process improvements by tracking pre- and post-change performance metrics and reporting on ROI.
  • Forecast future production volumes and resource requirements based on historical trends, sales forecasts, and market analysis.
  • Serve as a subject matter expert on production data, providing training and support to floor supervisors and operators on data interpretation and usage.
  • Investigate material usage variances by comparing standard bill of materials (BOM) against actual consumption, identifying sources of waste or inefficiency.
  • Participate in cross-functional project teams aimed at strategic initiatives, such as factory automation, system upgrades, or supply chain optimization.
  • Create and maintain documentation for all analytical models, reports, and dashboards to ensure business continuity and knowledge sharing.
  • Perform time studies and work sampling to establish labor standards and identify opportunities for improving workflow and ergonomics on the production line.
  • Track adherence to the production schedule, analyze deviations, and work with planners to understand the impact on customer delivery dates and inventory levels.

Secondary Functions

  • Support ad-hoc data requests and exploratory data analysis from various business units.
  • Contribute to the organization's broader data strategy and roadmap.
  • Collaborate with business units to translate their data needs into technical and engineering requirements.
  • Participate in sprint planning, retrospectives, and other agile ceremonies within the data and analytics team.

Required Skills & Competencies

Hard Skills (Technical)

  • Advanced Excel Proficiency: Mastery of complex formulas, pivot tables, Power Query, and VBA for data manipulation and modeling.
  • SQL: Strong ability to write complex queries to extract, merge, and transform data from relational databases.
  • BI & Data Visualization Tools: Hands-on experience creating impactful dashboards and reports in platforms like Tableau, Power BI, or Qlik.
  • ERP/MES Systems: Familiarity with enterprise systems such as SAP, Oracle, or specific Manufacturing Execution Systems for data extraction and process understanding.
  • Statistical Analysis: Knowledge of statistical methods for process control (SPC), regression analysis, and hypothesis testing, often using tools like Minitab or R.
  • Python or R: Experience in using scripting languages for data cleaning, automation, and advanced statistical modeling is a significant plus.
  • Process Improvement Methodologies: Understanding and practical application of Lean, Six Sigma (Green Belt preferred), or other continuous improvement frameworks.
  • Data Modeling: Ability to structure and model data to support repeatable and scalable analytics.
  • Forecasting Techniques: Experience with time-series analysis and other methods to predict future production trends and resource needs.
  • Cost Accounting Principles: A solid grasp of how to analyze production costs, variances, and the financial impact of operational changes.

Soft Skills

  • Analytical Mindset: An innate curiosity and a structured approach to breaking down complex problems into manageable components.
  • Exceptional Problem-Solving: The ability to move beyond identifying problems to methodically developing and evaluating potential solutions.
  • Clear Communication: Can effectively translate technical findings into compelling stories and actionable recommendations for both technical and non-technical audiences.
  • Meticulous Attention to Detail: A commitment to data accuracy and a sharp eye for catching inconsistencies that others might miss.
  • Collaborative Spirit: A team player who excels at building relationships with production staff, engineers, and management to achieve common goals.
  • Stakeholder Management: Skilled at understanding business needs, managing expectations, and influencing decisions without direct authority.
  • Time Management & Prioritization: Adept at juggling multiple requests and projects in a fast-paced environment, focusing on the most critical tasks.

Education & Experience

Educational Background

Minimum Education:

  • Bachelor's Degree in a relevant field.

Preferred Education:

  • Master's Degree or certifications in Data Analytics, Supply Chain (e.g., APICS), or Continuous Improvement (e.g., Six Sigma Green/Black Belt).

Relevant Fields of Study:

  • Business Administration
  • Industrial Engineering
  • Supply Chain Management
  • Data Science or Analytics
  • Statistics or Mathematics
  • Finance or Economics

Experience Requirements

Typical Experience Range: 2-5 years in an analytical role within a manufacturing, production, or supply chain environment.

Preferred: Direct experience working with manufacturing data (e.g., OEE, yield, scrap), participating in continuous improvement projects, and a proven track record of using data to drive operational results.

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