Key Responsibilities and Required Skills for Item Analyst

🎯 Role Definition

The Item Analyst is responsible for deep, SKU-level analytics and item master stewardship that drive assortment decisions, pricing, replenishment, and inventory optimization. This role blends quantitative analysis, business partnering with merchandising and supply chain teams, and hands-on data management to improve item profitability, reduce stock inefficiencies, and deliver timely, actionable insights to commercial stakeholders. The Item Analyst converts large data sets into operational recommendations using SQL, Excel, BI tools (Power BI, Tableau), forecasting techniques, and strong domain knowledge of retail/wholesale item lifecycles.

📈 Career Progression

Typical Career Path

Entry Point From:

Junior Data / Inventory Analyst
Merchandising Analyst or Planning Coordinator
Business Analyst with retail or supply chain experience

Advancement To:

Senior Item Analyst / Lead SKU Analyst
Merchandising Manager / Category Manager (Analytics track)
Inventory Planning Manager or Demand Planning Manager
Analytics Manager (Retail or Supply Chain)

Lateral Moves:

Pricing Analyst
Assortment Planner
Supply Chain Business Analyst
Product Data Manager

Core Responsibilities

Primary Functions

Perform SKU-level sales and inventory analysis to identify slow-moving, seasonal, and high-velocity items; produce prioritized action plans for assortment optimization and SKU rationalization to reduce carrying costs and improve sell-through.
Maintain and govern the item master (SKU attributes, categories, hierarchies, vendor mappings, cost, UPCs) across ERP and downstream systems, ensuring data integrity and reconciliation between merchandising, finance, and supply chain systems.
Build, validate, and maintain SQL-based extracts and data pipelines to provide repeatable item-level metrics (turn, sell-through, OTB impact, forecast accuracy) for daily, weekly and monthly reporting cycles.
Create and distribute executive and operational dashboards (Power BI, Tableau, Looker) that surface KPIs such as SKU profitability, margin contribution, inventory days, stockouts, overstocks, and vendor performance by item.
Develop and execute demand forecasting and statistical models for new and existing items; collaborate with demand planners to translate forecasts into replenishment recommendations and order planning.
Lead SKU rationalization projects, including hypothesis construction, A/B analysis, simulation of assortment scenarios, and business case development to discontinue or consolidate underperforming SKUs.
Partner with merchants and category managers to evaluate promotional lift, markdown optimization, and pricing elasticity at the item level; quantify trade-offs between margin, velocity, and inventory risk.
Run ad hoc analyses to quantify the impact of promotions, price changes, and display placements on item performance; present clear, data-driven recommendations for promotional scheduling and pricing adjustments.
Monitor in-season performance against plan; detect and triage supply issues, returns spikes, product defects, and sudden demand shifts; recommend rapid mitigations (expedite, cancel, transfer, markdown).
Define and measure item lifecycle stages (introduction, growth, maturity, decline) and create playbooks for treatment of items at each stage including replenishment, promotion, or delisting.
Analyze vendor lead times, fill rates, and PO performance at the SKU level to identify supply-side risks and opportunities for improved service and cost savings.
Conduct margin and profitability analyses at SKU and assortment levels; identify margin leakage drivers (cost errors, promotions, repricing) and propose corrective actions with finance and trading partners.
Lead cross-functional projects involving merchandising, buying, planning, supply chain, and finance to operationalize data-driven assortment, pricing, and inventory decisions.
Implement and maintain automated alerts and anomaly detection for item-level KPIs (sudden sales dips, negative margin, inventory divergences) to enable proactive stakeholder responses.
Prepare concise, senior-ready briefings and slide decks summarizing item performance, strategic recommendations, and KPI trends for weekly and monthly business reviews.
Execute new item introductions and phase-ins by validating item data, initial demand estimates, introductory pricing, and supply readiness to minimize stockouts and overstocks.
Work with data engineering and IT teams to prioritize and scope enhancements to item master systems, reporting platforms, and analytics tooling to improve data accessibility and reporting cadence.
Perform cohort and lifecycle analyses to inform assortment strategies, customer segmentation at item level, and targeted merchandising initiatives to increase customer retention and basket sizes.
Conduct markdown and clearance optimization analyses, modeling the impact of timing and depth of markdowns on sell-through and margin recovery for slow-moving SKUs.
Provide mentorship and training to junior analysts and merchandising partners on how to interpret SKU-level analytics, use BI reports, and implement recommended actions.
Validate and reconcile item cost, landed cost, and promotional accounting entries with finance to ensure gross margin and P&L accuracy for items.
Support compliance and catalog governance efforts, ensuring product descriptions, images, and classification meet marketplace or regulatory requirements where applicable.
Maintain a prioritized backlog of item analytics requests, balancing recurring deliverables, strategic projects, and urgent business needs with clear SLAs.

Secondary Functions

Support ad-hoc data requests and exploratory data analysis.
Contribute to the organization's data strategy and roadmap.
Collaborate with business units to translate data needs into engineering requirements.
Participate in sprint planning and agile ceremonies within the data engineering team.
Assist with UAT for item master system changes and BI report releases to ensure accurate SKU-level outputs.
Facilitate periodic cross-functional calibration sessions (merchandising, supply chain, finance) to align on SKU classification, thresholds, and governance rules.

Required Skills & Competencies

Hard Skills (Technical)

Advanced SQL (writing complex joins, window functions, performance tuning) for SKU-level extraction and transformation.
Expert Microsoft Excel skills (pivot tables, advanced formulas, macros/Power Query) for ad-hoc analyses and prototyping.
Experience building dashboards and visualizations in Power BI, Tableau, or Looker to present SKU and assortment insights.
Familiarity with statistical forecasting methods and libraries (time series forecasting, Croston, exponential smoothing) and hands-on experience applying them to item demand.
Experience with Python or R for data manipulation, automation, and advanced analytics (pandas, numpy, scikit-learn).
Item master, product information management (PIM), and ERP familiarity (SAP, Oracle NetSuite, JDE, Microsoft Dynamics).
Knowledge of inventory optimization concepts: days of supply, safety stock, reorder point, EOQ, and replenishment logic.
Experience with assortment planning, SKU rationalization frameworks, and merchandising analytics.
Exposure to pricing and promotion analytics, elasticity modeling, and markdown optimization techniques.
Ability to write efficient queries against large data warehouses (Redshift, Snowflake, BigQuery) and work with data pipelines/ETL processes.
Basic understanding of SQL-based reporting tools, version control (Git), and ticketing systems for collaboration with engineering teams.
Data governance and data quality management experience (deduplication, attribute normalization, reconciliation).

Soft Skills

Strong stakeholder management and ability to communicate analytic findings to commercial and executive audiences in simple, actionable terms.
Problem-solving and critical thinking with a bias toward practical, prioritized recommendations.
High attention to detail and data accuracy; rigorous approach to validation and reconciliation.
Prioritization and time management to balance recurring reporting, project work, and urgent escalations.
Cross-functional collaboration and facilitation skills to drive decisions across merchandising, planning, and supply chain.
Ability to translate business problems into analytic requirements and vice versa.
Curiosity and continuous improvement mindset; proactive about automating repetitive work.
Presentation and storytelling skills—capable of building executive decks and leading business reviews.
Adaptability in fast-paced retail or distribution environments with shifting priorities.
Coaching and mentorship capabilities for junior analysts and business users.

Education & Experience

Educational Background

Minimum Education:

Bachelor's degree in Business Analytics, Supply Chain, Economics, Statistics, Mathematics, Computer Science, or related field.

Preferred Education:

Bachelor’s with concentration in Retail Analytics, or a Master’s degree / MBA with analytics, supply chain, or merchandising emphasis.

Relevant Fields of Study:

Analytics / Data Science
Supply Chain Management / Logistics
Economics / Applied Statistics
Business / Marketing
Computer Science / Information Systems

Experience Requirements

Typical Experience Range:

2–5 years of experience in SKU/item analytics, inventory analysis, merchandising analytics, demand planning, or related roles in retail, wholesale, or distribution environments.

Preferred:

3–7+ years of progressive experience with demonstrated ownership of item master programs, forecasting and replenishment projects, cross-functional merchandising partnerships, and production analytics reporting. Experience with large-scale e-commerce or omnichannel retail preferred.