The specific signals an experienced supply chain analyst hiring panel grades on during the eight-second scan.

• Business scope

  'Demand planning analyst at a $1.4B CPG company; 38k SKUs across 8 brands' beats 'supply chain analyst.' Revenue + SKUs + brands.

• Forecast accuracy + bias

  Forecast accuracy (MAPE / WAPE) + bias. Universal demand-planning metrics.

• Inventory + service level

  Days of inventory on hand (DOH) + service level (fill rate + OTIF) + working capital.

• Planning system fluency

  SAP IBP, Kinaxis RapidResponse, Oracle Demantra, o9, Blue Yonder, Anaplan, Logility.

• Analytical stack

  SQL + Excel + Python + Tableau / Power BI. Modern supply chain is data-heavy.

• S&OP partnership

  Sales + Operations Planning cadence + cross-functional. Senior signal.

1. 1

   Open with scope + MAPE

   Revenue + brands + SKUs + MAPE vs network. Supply chain hiring opens here.

2. 2

   Quantify forecast + inventory trade-offs

   MAPE + DOH + service level + working capital. Trade-offs articulated.

3. 3

   Surface S&OP role

   Monthly cadence + executive review + scenario presentation.

4. 4

   Name planning system + analytical stack

   SAP IBP / Kinaxis / o9 + SQL + Python + Tableau. Specificity.

5. 5

   Close with certifications + education

   APICS + Anaplan + MBA where applicable.

Each follows the [verb] [object] [number] structure hiring managers grade against. Copy them as a starting point, swap in your own numbers, and read the annotation to understand why each one works.

• Forecast

  Forecast accuracy: lifted MAPE from 22% to 14.8% over 14 months via 3 changes — moved 38 top SKUs from monthly to weekly granularity, integrated promotional-lift modeling (XGBoost in Python on 4 years of sales + promo + price data), reconciled with Sales on top-14 customer-account assumptions.

  Why it works: MAPE before/after + 3 changes + tools + data scope.

• Inventory

  Inventory: DOH 84 → 62 days while holding service level 98.4%; freed $84M working capital; tightened safety-stock parameters on 14k slow-movers using statistical safety-stock + 1,400 top SKUs with seasonality models; rebalanced FCS across 4 DCs.

  Why it works: DOH + service level + working capital + 3 methods + DC scope.

• S&OP

  S&OP: led demand-review meeting for the $380M brand (monthly + executive S&OP quarterly); presented forecast + supply-vs-demand gap + scenario analyses on 4 stress scenarios (peak-season surge, supplier outage, capacity constraint, demand contraction); influenced 3 quarterly capacity plans.

  Why it works: Role + cadence + content + 4 scenarios + influence.

• Stack

  Stack: SAP IBP (demand + supply modules, 3 yrs); SQL (Snowflake, 14k lines authored across 280 production-grade queries); Python (XGBoost forecasting + Pandas + scikit-learn, 4 years); Tableau (8 published dashboards, 380 weekly viewers); Anaplan (S&OP scenario planning).

  Why it works: Tools + tenure + code volume + dashboard reach.

• Modeling

  Promotional planning: built the team's promotional-lift model (XGBoost on 4 years of sales + promo + price data); reduced post-promo forecast bias from -18% to -4% on 38 top SKUs; presented model to executive S&OP + adopted as standard for Q4 peak planning.

  Why it works: Model detail + bias reduction + SKU scope + adoption.

• Cross-functional

  Cross-functional: weekly with Sales Ops + Brand Managers on top-14 customer accounts; biweekly with Supply Planning on capacity + supplier coordination; quarterly with Finance on working-capital + forecast-revenue alignment.

  Why it works: Partners + cadence + scope.

• Scenario

  Scenario planning: built Anaplan model for peak-season surge analysis (4 demand scenarios × 3 capacity scenarios × 4 logistics-cost scenarios = 48 combinations); presented to executive S&OP; informed $12M peak-season capacity decision.

  Why it works: Model + combination count + audience + decision influence.

• Network

  Network: led MILP-based network-design study (Python with PuLP + Gurobi); evaluated consolidation from 6 DCs to 4 DCs; identified $14M annual savings + 2-day service degradation; informed 2-year network roadmap.

  Why it works: MILP + tooling + DC scope + savings + trade-off + roadmap.

• Supplier

  Supplier collaboration: led monthly collaborative-forecasting sessions with the top 4 suppliers (28% of total spend); supplier forecast-sharing reduced inbound emergency expediting from 38 events/year to 8 events.

  Why it works: Cadence + supplier scope + spend % + outcome.

• Mentorship

  Mentorship: mentored 2 junior analysts through their first S&OP cycle; built the team's onboarding playbook (a 60-page Notion doc covering SAP IBP + SQL + S&OP norms + Tableau templates).

  Why it works: Mentee count + scope + playbook authorship.

• Recognition

  Recognition: Supply Chain Excellence Award (annual, 1 of 14 across 380-person SC org) 2024 for the MAPE + DOH initiative; presented at company-wide town hall.

  Why it works: Award + cohort + initiative tie-in + audience.

• Career

  Career arc: started as Supply Chain Coordinator (1 year), promoted to Analyst (2 years), then Senior Analyst on the largest brand (current, 3 years); ladder driven by MAPE + S&OP impact + cross-functional reputation.

  Why it works: Ladder + tenure + criteria.

Same intent, two phrasings. Read why the right column lands on the keep-pile and the wrong column doesn't.

Patterns our writers see most often when reviewing supply chain analyst resumes — each one disqualifies candidates faster than weak experience does.

• Mistake

  Generic 'analytical skills.'

  Fix

  MAPE + DOH + service level + working capital. Supply chain hiring opens here.

• Mistake

  Forecast accuracy without context.

  Fix

  MAPE vs network avg + improvement arc + mechanism. Context.

• Mistake

  Inventory without trade-offs.

  Fix

  DOH + service level + working capital together. Trade-offs articulated.

• Mistake

  Planning system missing.

  Fix

  SAP IBP / Kinaxis / o9 / Anaplan + tenure + module detail.

• Mistake

  SQL + Python without depth.

  Fix

  Lines authored + query count + library + production-grade vs ad-hoc.

• Mistake

  S&OP absent.

  Fix

  Monthly S&OP cadence + executive review + scenario presentation. Senior signal.

• Mistake

  Two-page resume at entry level.

  Fix

  1 page if < 5 yrs.

• Mistake

  No certifications.

  Fix

  APICS CSCP + CPIM are universal. Anaplan + Kinaxis if applicable.

Strong verbs lead strong bullets. Replace generic openers (worked on, helped with, was responsible for) with the specific verb that matches what you actually did.

ATS pipelines weight your Skills section as a structured list. Include 15-25 of the items below if they match your experience — not soft skills.