Key Indicators: Monitoring and Assessing Service to Customer
Explore how Fill Rate and OTIF help measure reliability, analyze service gaps, and improve customer satisfaction.
Monitoring and Assessing Service to Customer
Companies rely on a range of metrics to evaluate how effectively they are serving their customers.
Two of the most essential and insightful metrics are Fill Rate and On Time In Full (OTIF).
Together, these indicators help organizations:
- Identify trends in supply chain reliability and responsiveness
- Conduct root cause analysis on service performance
- Implement targeted action plans to continuously improve customer service
🚚 What is Fill Rate?
Fill Rate measures an organization’s ability to meet customer demand from available stock or scheduled production.
In simple terms, it reflects how well your company fulfills orders on time and in the correct quantity.
Fill Rate is often also referred to as Service Level or Level of Service.
It may be calculated based on:
- % of orders picked complete upon receipt,
- % of line items picked complete, or
- % of total dollar demand fulfilled.
Although it’s a backward-looking metric, consistent monitoring reveals trends that can predict future risks or opportunities across commercial and operational functions.
⚙️How is Fill Rate Calculated?
1. Unit Fill Rate
SKU | Ordered Qty | Shipped Qty | Unit Fill Rate |
A | 100 | 75 | (75/100) × 100 = 75% |
B | 450 | 450 | (450/450) × 100 = 100% |
C | 230 | 210 | (210/230) × 100 = 91% |
D | 1,000 | 800 | (800/1,000) × 100 = 80% |
E | 350 | 350 | (350/350) × 100 = 100% |
Total | 2,130 | 1,885 | (1,885/2,130) × 100 = 88% |
2. Revenue Fill Rate
SKU | Ordered Qty | Unit Price | Ordered Revenue | Shipped Qty | Shipped Revenue | Revenue Fill Rate |
A | 100 | $3.00 | $300.00 | 75 | $225.00 | (225/300) × 100 = 75% |
B | 450 | $2.50 | $1,125.00 | 450 | $1,125.00 | (1,125/1,125) × 100 = 100% |
C | 230 | $6.75 | $1,552.50 | 210 | $1,417.50 | (1,417.5/1,552.5) × 100 = 91% |
D | 1,000 | $1.45 | $1,450.00 | 800 | $1,160.00 | (1,160/1,450) × 100 = 80% |
E | 350 | $5.00 | $1,750.00 | 350 | $1,750.00 | (1,750/1,750) × 100 = 100% |
Total | 2,130 | — | $6,177.50 | 1,885 | $5,677.50 | (5,677.5/6,177.5) × 100 = 92% |
📌 Note: The difference between Unit Fill Rate (88%) and Revenue Fill Rate (92%) is due to weighting. High-priced SKUs (C and E) with better service levels influence the overall Fill Rate more heavily.
⚙️What is On Time In Full (OTIF)?
Many companies are now evolving from traditional Fill Rate to the more robust On Time In Full (OTIF) metric.
OTIF measures how often shipments arrive on time and in full, based on customer expectations.
In other words, OTIF evaluates how reliable and precise your delivery performance truly is.
To use OTIF effectively, companies must clearly define:
- What counts as “on time” (e.g., by customer request date, manufacturer promise date, or delivery appointment)
- How “in full” is measured (at order, line, or case level)
Since there is no universal standard definition, organizations should ensure that:
- The definition is clearly documented and understood internally, and
- It is aligned with customer expectations, particularly in collaborative planning contexts.
Example of a Strong OTIF Definition
Case quantity that is delivered to the destination by the requested delivery date, calculated as a percentage of the ordered quantity.
1️⃣ Case quantity excludes any over-delivered or incorrect product.
2️⃣ Delivery means arrival at the destination facility, not unloading or check-in.
3️⃣ Requested delivery date refers to the original customer request date (with a one-day early allowance and retailer-caused delay adjustments).
(Adapted from Davies et al., 2019, McKinsey & Company)
⚙️How is OTIF Calculated?
SKU | Ordered Qty | Shipped Qty | Unit Fill Rate | In Full | Customer Req. Date | Actual Delivery | On Time | Case-Level OTIF % |
A | 100 | 100 | 100% | ✅ | Jan 10, 2022 | Jan 10, 2022 | ✅ | 100% |
B | 450 | 450 | 100% | ✅ | Feb 15, 2022 | Feb 14, 2022 | ✅ | 100% |
C | 230 | 210 | 91% | ❌ | Feb 15, 2022 | Feb 15, 2022 | ✅ | 91% |
D | 1,000 | 1,000 | 100% | ✅ | Apr 4, 2022 | Apr 6, 2022 | ❌ | 0% |
E | 350 | 350 | 100% | ✅ | Apr 30, 2022 | May 1, 2022* | ✅ | 100% |
Total | 2,130 | 2,110 | 99% |
Interpretation of Results
- ✅ SKU A → Delivered in full and on time
- ✅ SKU B → Delivered 1 day early (still on time per definition)
- ⚠️ SKU C → Delivered on time but not in full
- ❌ SKU D → Delivered in full but late
- ✅ SKU E → Delivered in full and on time (adjusted for retailer delay)
Line-Level OTIF Calculation
💡Why Fill Rate and OTIF Matter
Metric Result | Possible Root Causes | Business Impact |
Low Fill Rate / OTIF | Poor forecast, production delays, supplier issues | Lost sales, penalties, service failures |
High Fill Rate but Low OTIF | Good inventory, but poor logistics execution | Late deliveries, customer dissatisfaction |
Variable OTIF | Inconsistent scheduling, transport constraints | Unpredictable service, planning inefficiencies |
A Forecasting Performance Dashboard can visualize these indicators over time and across hierarchy levels.
This allows teams to:
- Identify trends and anomalies in forecast performance
- Conduct root cause analysis by product, customer, or region
- Collaborate with Sales, Marketing, and Operations to adjust plans
- Implement improvement initiatives and track impact
Continuous monitoring of Forecast Accuracy and Forecast Bias drives a culture of data-driven decision-making and forecast ownership across the organization.
✍️Key Takeaways
✅ Forecast Accuracy measures precision.
✅ Forecast Bias measures directionality of errors.
✅ Both are needed to truly understand and improve forecast performance.
✅ Tracking and analyzing them over time reveals opportunities to reduce costs, improve service, and align business functions.
📘 References
Davies, A., Lal, S., Perez, F., & Potdar, S. (2019). Defining “On-Time, In-Full” in the Consumer Sector.
McKinsey & Company.