Sr Demand Planning Analyst

Amsive•Bolingbrook, IL

2d•Hybrid

About The Position

The Senior Demand Planning Analyst is a highly analytical role responsible for translating demand signals, operational data, and financial information into actionable insights that improve capacity utilization, labor efficiency, profitability, and overall business performance. This position will partner closely with Sales, Operations, Finance, Supply Chain, Manufacturing, and Technology teams to develop demand forecasts, evaluate production capacity, identify operational constraints, and support fact-based decision-making across the organization. The ideal candidate is intellectually curious, highly proficient in data analysis, and motivated to modernize how the organization uses information. This individual should have a strong desire to learn and apply artificial intelligence, automation, advanced analytics, and modern data tools to improve forecasting accuracy, increase organizational speed, and create scalable decision-support capabilities.

Requirements

Bachelor’s degree in Supply Chain, Operations Management, Industrial Engineering, Finance, Economics, Statistics, Data Analytics, Business, or a related field.
2+ years of experience in demand planning, supply planning, manufacturing analytics, operations finance, capacity planning, or a similar analytical role.
Advanced Microsoft Excel skills, including complex formulas, pivot tables, scenario modeling, and data analysis.
Experience using business-intelligence or visualization tools such as Power BI, Tableau, Dataroma, or a similar platform.
Familiarity with AI-enabled productivity and analytical tools.
Excellent written and verbal communication skills with the ability to influence and collaborate with stakeholders at all levels.
Analytical thinker with strong problem-solving skills and the ability to draw insights from complex data.
Ability to manage multiple priorities in a fast-paced and evolving environment.

Responsibilities

Develop and maintain short-, medium-, and long-range demand forecasts by customer, product, facility, production line, or other relevant business segment.
Consolidate historical demand, sales pipeline information, customer forecasts, seasonality, market trends, and operational inputs into an integrated demand plan.
Analyze forecast accuracy, bias, variability, and key demand drivers.
Identify significant changes in demand patterns and communicate potential operational and financial implications.
Develop detailed capacity models across facilities, production lines, equipment, labor groups, and shifts.
Compare forecasted demand against available production capacity to identify constraints, excess capacity, and potential service risks.
Evaluate the impact of customer growth, new business opportunities, product mix changes, equipment downtime, staffing changes, and productivity assumptions.
Perform scenario analysis to support decisions related to overtime, shift structures, capital investments, outsourcing, facility utilization, and production scheduling.
Create forward-looking capacity dashboards that provide leadership with visibility into anticipated utilization and bottlenecks.
Analyze labor performance, including labor hours, units per labor hour, earned versus actual hours, overtime, staffing levels, and utilization.
Identify productivity trends, labor inefficiencies, and performance gaps across facilities, shifts, departments, and production lines.
Evaluate the impact of product mix, run size, setup time, downtime, training, absenteeism, and staffing levels on labor performance.
Support workforce planning by identifying future labor needs, productivity opportunities, and potential staffing risks.
Analyze customer, product, job, facility, and production-line profitability.
Identify margin improvement opportunities and areas of financial underperformance.
Support customer pricing, contract evaluations, business reviews, and new-business assessments with fact-based financial and operational analysis.
Partner with Finance to improve cost-to-serve, contribution margin, and unit-economic models.
Build and maintain dashboards, models, and recurring reporting that provide clear visibility into demand, capacity, labor, productivity, service, and profitability.
Convert complex data into concise insights and recommendations for operational and executive leadership.
Develop standardized performance metrics and ensure consistent definitions across departments.
Perform root-cause analysis on operational and financial performance variances.
Identify emerging trends, risks, and opportunities before they materially affect business results.
Actively learn and apply artificial intelligence, machine learning, automation, and advanced analytics to demand planning and operational decision-making.
Identify opportunities to automate manual reporting, recurring analysis, data preparation, and forecasting processes.
Experiment with AI-enabled tools to improve forecast accuracy, detect anomalies, summarize performance drivers, and accelerate decision-making.
Promote responsible, secure, and practical use of AI and modern data tools.