Digitalization was supposed to make our lives easier; instead, it has made our supply chains more complex. In this environment, steering by “gut feel” is a recipe for disaster. You need precision, and in my experience, there is no tool more vital—or more misunderstood—than the On-Time In-Full (OTIF) metric.
On the surface, OTIF looks deceptively simple, like a two-piece puzzle – measure the timeliness of the delivery and the completeness of the goods within the shipment. But once you dive into the operational weeds of delivery windows, promise-date definitions, and the “case vs. item” debate, the picture gets cloudy fast. Moreover, I’ve seen many OTIF programs sink because the data was fragmented or the metric parameters weren’t aligned with actual business goals. In this article, I’m sharing eight hard-won insights to help you master measuring OTIF for your unique business. By the time we’re done, you’ll have the practical roadmap you need to turn OTIF from a confusing acronym into your supply chain’s greatest strength. Let’s get started.
- 1. Inventory Availability vs. OTIF: Why You Need Both.
- 2. Measuring Delivery: By Delivery Window or By No-Later-Than.
- 3. How Big Should the Delivery Window Be?
- 4. Measuring On-Time Dates Correctly: Delivered, Promised.
- 5. Is It Better to Measure Based on the Shipment’s Case Count or By the Purchase Order’s Product Item Count?
- 6. Consequences of Setting OTIF Standard Too High Or Too Low
- 7. How Poor Data Quality Affects Both OTIF Measurements and the Ability to Take Corrective Action.
- 8. Do We Need an Universal Standard for OTIF Or Just Make It Understandable?
First, What is OTIF?
On-Time In-Full (OTIF) is a supply chain metric that measures the percentage of orders delivered to customers on time and in the correct quantity. It’s a critical indicator of a company’s ability to meet customer expectations and maintain a competitive edge. By tracking OTIF, businesses can identify areas for improvement in their supply chain operations, from order fulfillment to inventory management and shipment delivery. Below is a good working definition of OTIF.
“… measures a supplier’s ability to fulfill its delivery promises, meaning a customer receives exactly what was ordered, in the amount requested, at the correct location, and within the agreed upon timeframe.”
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Without a doubt, On-Time In-Full (OTIF) is an essential barometer of supply chain excellence. Moreover, OTIF reflects how well logistics companies, retailers, and suppliers align their operations with customer expectations. For a more detailed discussion on the mechanics of OTIF, see my article, What is OTIF, How to Calculate, and Why is It Important?
Achieving Supply Chain Excellence with OTIF Metrics: Essential Insights You Need to Know
To achieve supply chain excellence with OTIF metrics, it’s essential to understand the nuances of this metric and its relationship with different supply chain systems and their data interfaces. See below, where I share my insights on how best to set key operational parameters for effectively measuring OTIF in your supply chain.
1. Inventory Availability vs. OTIF: Why You Need Both.
OTIF and inventory availability on the surface have similar objectives, but they track different things. Think of inventory availability as just checking if items are in stock. Versus OTIF goes much further – it measures if those items actually reached your customer when and how they wanted them. Indeed, a warehouse full of products won’t help your OTIF score if trucks arrive late or ship wrong quantities. At the same time, it is best to measure both as OTIF gets tricky when you deal with back orders or partial shipments. The bottom line – it is essential to measure both inventory availability and On-Time In-Full (OTIF) performance, as each metric tracks a distinct aspect of operations.
“… it is essential to measure both inventory availability and On-Time In-Full (OTIF) performance, as each metric tracks a distinct aspect of operations.”
2. Measuring Delivery: By Delivery Window or By No-Later-Than.
When establishing your OTIF measurement standards, it is important to identify whether your business should measure On-Time Delivery by a delivery window or by a no-later-than (NLT) date and time. While your average consumer might love getting a package sooner than expected, businesses often don’t. In fact for many commercial operations, an early delivery is just as bad as a late delivery. For example, think about a busy warehouse – an early truck means finding unexpected storage space, scrambling for equipment, or juggling dock schedules. That’s why when setting up your OTIF system, you need to decide upfront whether to measure OTIF by delivery windows or by NLT date/time.
“… you need to decide upfront whether to measure OTIF by delivery windows or by NLT date/time”
3. How Big Should the Delivery Window Be?
Determining the optimal delivery window is a delicate balancing act between operational flexibility and customer expectations. For example, a broad 4-hour delivery window eases pressure on transport providers, but more than likely will trigger inefficiencies in warehouse scheduling. Moreover, residential consumers can quickly become frustrated with large delivery windows as they wait for a package to arrive. Conversely, narrower windows demand high levels of resource coordination and precise execution for both the carrier and the commercial receiving operations. Ultimately, delivery window specifications need to reflect on the capabilities of the supplier and the needs of the customer, ensuring a harmonious supply chain operation.
“… delivery window specifications need to reflect on the capabilities of the supplier and the needs of the customer …”
4. Measuring On-Time Dates Correctly: Delivered, Promised.
To accurately measure OTIF, it’s essential to compare the actual delivered date with the promised date. Surprisingly, it is a formidable challenge to measure delivered and promised dates correctly. In many instances, carriers or the receiving operation do not accurately document actual delivery date and time. Worse, it is quite common that neither party has the same understanding of the shipment’s promised date. In fact, this is a major reason why many supply chains do not measure effectively either On-Time Delivery (OTD), nor OTIF.
Without a doubt, many times shippers and receivers do not explicitly agree on what measures to use when determining a successful delivery. For example, Let’s look at a truck delivering to a warehouse. Does delivery mean: when the truck enters the yard, or when the trailer is dropped, or when the trailer is unloaded? Even more challenging, how do you account for delivery schedule changes by either the supplier or the receiver?
For a more detailed discussion on measuring on-time deliveries, see my article, Measuring Ecommerce On-Time Delivery: Instructive Advice To Best Avoid Pointless Mistakes.
“… carriers or the receiving operation do not accurately document actual delivery date and time. Worse, … neither party has the same understanding of the shipment’s promised date.”
5. Is It Better to Measure Based on the Shipment’s Case Count or By the Purchase Order’s Product Item Count?
To achieve a true measure of supply chain performance, shippers should ideally track OTIF against the original purchase order (PO) and its promised date. This prevents “split shipments” from masking delays. When it comes to measuring “In-Full” there are several factors to consider.
Measuring “In-Full”: Factors to Consider
- Case Count: Best for uniform products; it streamlines data processing and protects sensitive product details during transit.
- Product Item Count: Offers granular visibility, identifying specific friction points in the supply chain to drive targeted improvements.
- Operational Variables: Data availability, customer preferences, and potential order modifications (such as quantity changes) must be aligned to ensure “in-full” metrics remain consistent and accurate.
“… shippers should ideally track OTIF against the original purchase order (PO) and its promised date. ”
6. Consequences of Setting OTIF Standard Too High Or Too Low
Setting the OTIF standard too high can lead to unrealistic expectations and unnecessary costs, resulting in constant delivery failures. On the other hand, setting it too low can result in subpar performance and decreased customer satisfaction. So, the standard should be challenging yet achievable. Moreover, a metric should not be set in stone. Most importantly, the metric should be geared toward continuous improvement without compromising service quality. Lastly, when shippers set their OTIF goals, they must balance it against customer needs, the competition, and costs to achieve the metric standard.
7. How Poor Data Quality Affects Both OTIF Measurements and the Ability to Take Corrective Action.
The first challenge is that most supply chain operations need to get OTIF-related data from multiple systems to measure OTIF. This type of data integration is difficult. For example, these systems can include order fulfillment, shipping, TMS, carrier, WMS, and ERP to name a few. At its core, OTIF data encompasses a diverse range of systems, various data formats, and numerous communication protocols within supply chains.
Moreover, even if shipping data is available, it is often fragmented, duplicated, ambiguous, and riddled with inaccuracies, making it nearly impossible to measure OTIF accurately or diagnose supply chain deficiencies. For example, data deficiencies can include a missed delivery status or a lack of exception statuses, detailing why a shipment was delayed. Moreover, routinely shippers have broken linkages between purchase orders and their associated tracking numbers. Lastly, in the case of order fulfillment, OTIF may be accurate, but difficult to improve due to data quality. For example, stock outs continue to occur due to outdated supplier lead times. Or shipping departments, working with faulty data, cannot detect that a shipment order is incomplete.
For more information on the impact of poor data quality on OTIF measurement and taking corrective action, see my article, Poor Shipping Data – Here Are The 4 Reasons Impeding High Tech Visibility And Actionable Analytics.
“… even if shipping data is available, it is often fragmented, duplicated, ambiguous, and riddled with inaccuracies, making it nearly impossible to measure OTIF accurately or diagnose supply chain deficiencies.”
8. Do We Need an Universal Standard for OTIF Or Just Make It Understandable?
While a universal standard for OTIF would foster industry-wide consistency, this may not be the best approach. Indeed with the wide variety of supply chain operations across different sectors, a one-size-fits-all approach may be impractical as well as not meet operational needs. As stated previously, what is most important is to ensure that the OTIF metric is clear and understandable within your specific operation. Ultimately, a successful OTIF program must be strategically balanced to meet customer expectations, remain competitive within your cost structure, and align with your organization’s logistical capabilities. For a more detailed discussion on the merits of standardizing OTIF measurements, see McKinsey’s article, Defining ‘on-time, in-full’ in the consumer sector.
“… a successful OTIF program must be strategically balanced to meet customer expectations, remain competitive within your cost structure, and align with your organization’s logistical capabilities.”
More References.
- Measuring OTD: Measuring Ecommerce On-Time Delivery: Instructive Advice To Best Avoid Pointless Mistakes
- OTIF Explained: Celonis’ article, OTIF explained: The what, why and how of optimizing for on-time in-full delivery
- Measuring OTIF: Measuring The OTIF Metric: The Best Ways To Focus On Uplifting Supply Chain Excellence
Need help with an innovative solution to make your supply chain analytics actionable? I’m Randy McClure, and I’ve spent many years solving data analytics and visibility problems. As a supply chain tech advisor, I’ve implemented hundreds of successful projects across all transportation modes, working with the data of thousands of shippers, carriers, and 3rd party logistics (3PL) providers. I specialize in launching new analytics-based strategies, proof-of-concepts and operational pilot projects using emerging technologies and methodologies. If you’re ready to supercharge your analytics or if you are a solution provider, let’s talk. To reach me, click here to access my contact form or you can find me on LinkedIn.
For more from SC Tech Insights, see the latest articles on Data Analytics, Shipping, and Supply Chain.
Greetings! As a supply chain tech advisor with 30+ years of hands-on experience, I take great pleasure in providing actionable insights and solutions to industry leaders. My focus is on supply chains leveraging emerging LogTech. I zero in on tech opportunities and those critical issues that are solvable, but not well addressed, offering industry executives clear paths to resolution. I have a wide range of experience to include successfully leading the development of 100s of innovative software solutions across supply chains and delivering business intelligence (BI) solutions to 1,000s of shippers. Click here for more info.