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The Philosophy Behind OTIF Calculation

On-time, in-full – or OTIF as it’s commonly referred to – was borne of the concept that retail stores need to be able to better manage their supply chain and manage inventories. By putting suppliers’ and shippers’ feet to the fire, retailers can be more responsive to customer demand by ensuring the right products in the right volume are on the shelves at the right time. 

WalMart may have created the OTIF delivery requirement, but many other big box stores have followed suit, seeing the value in having greater predictability and control over inventories. The intention makes financial sense, however, many supply chain participants aren’t entirely sure how to go about OTIF calculation. 

OTIF calculations are intended to measure how well a supplier is able to deliver on its timeframe commitment, how complete and accurate the order is, and the integrity of the products ordered. Retailers can impose fines on suppliers for poor OTIF performance and evaluate suppliers by their score, motivating suppliers to prioritize those processes that minimize their risk of missing OTIF commitments.

The problem with OTIF calculations, however, is that there is no standard definition for what exactly OTIF means. According to McKinsey, every supply chain stakeholder may have their own interpretation, saying, “Does ‘on-time’ mean on the date requested by the retailer, or the date promised by the manufacturer? Does it mean within the specific delivery slot allocated to the shipment, or any time inside a broader, agreed-upon time window? Should ‘in-full’ be measured at the level of complete orders, line-items or individual cases?”

Without a standard definition and expectations, it is difficult to perform accurate OTIF calculations. A McKinsey and Trading Partner Alliance (TPA) survey of 24 major U.S.-based retailers and manufacturers of consumer packaged goods found that 92% of respondents would prefer an industry standard for OTIF as it would reduce confusion and foster greater partner collaboration, all of which would likely help them keep the supply chain operating more efficiently and effectively.

With a common definition, retailers and suppliers are able to have conversations using the same language. This is an important contributor to transparency but also how issues are identified and resolved. Unless all supply chain stakeholders understand what is expected of them, it is difficult to calculate OTIF, particularly as retailers each have their own definitions that frequently change.

Beyond lacking a common definition of what on-time, in-full, the McKinsey survey found that 79% of respondents said they preferred using a single metric to measure both in-time and in-full versus measuring each component separately. Additionally, 79% of respondents said they prefer to define “in-full” at the “case” rather than the “order” or “line” level, and 67% of respondents said they prefer to define “on-time” as the requested delivery date or the “must arrive by” date rather than the scheduled-delivery appointment date or the manufacturer’s committed-delivery date.

Interestingly, nearly 80% of respondents indicated they wanted some kind of flexibility with the actual delivery window, with some preferring their deliveries are still considered “on-time” even if they are delivered up to two days early than the requested delivery date. While some retailers may be satisfied with such a broad delivery window, others may view it as unacceptable. Early deliveries can cause just as many or more issues as late ones. McKinsey says, “Unloading [early] deliveries can disrupt distribution-center operations, while holding trucks until their scheduled slot leaves assets standing idle, consuming industry capacity while incurring demurrage costs.”

It is easy to see why supply chain stakeholders would like to see a common OTIF calculation to simplify an already complex ecosystem.

Weather, Infrastructure and Social Issues Can Impact OTIF Calculations

Manufacturers, shippers and carriers have more to worry about than finding a standard OTIF definition. The supply chain is riddled with risks, many of which are difficult to predict ahead of time. Any one issue can instantly cause a chain reaction of delays that make meeting OTIF commitments all but impossible.

Related: Managing Risk with Supply Chain Risk Management Software

Some consider weather one of those uncontrollable variables that regularly threaten shipments. The weather may be unpredictable to an extent, but with the right data consolidated and analyzed using actionable, predictive intelligence, most weather events can be predicted with remarkable accuracy. Same goes for infrastructure and social issues.

The beauty of this type of advanced technology is that some providers offer solutions that can be customized per customer, giving companies the ability to adapt their OTIF definitions to their customers’ requirements. OTIF calculations, therefore, can be made with greater confidence and less confusion.

The important elements of OTIF that suppliers, carriers and shippers need to know as they relate to weather and other common risk factors are how likely they will be able to meet delivery windows and how well they can protect cargo.

Meeting Delivery Windows

Decision-makers require predictive data to help them understand their risk as it relates to the company’s specified risk tolerance. In order to meet delivery windows, they need OTIF calculations that indicate the probability of each shipment delivering early, late, or within a customer’s requested delivery date. 

Related: Predictive Analytics Tools Have Changed Logistics Forever

Beyond the probability, it is important to identify the risks that could cause any delays, measured with an actual risk score. The risk score provides that “common definition” so many survey respondents desire, customized to the risk tolerance agreed upon by leaders. With risk quantified for each shipment, it is much easier and faster to come to a decision about how to mitigate the highest-potential risks, and risk mitigation efforts can be executed days ahead of time.

Protecting Cargo

Even when a shipment arrives within the required timeframe, if the cargo is damaged, the company will get dinged for failing to meet the in-full requirement. Advanced technology is now being used to break down each shipment at the granular level. For instance, each shipment is assessed based on the type of cargo being transported and its environmental tolerance, the predicted weather and temperatures along the route, and the planned mode of transportation for that specific cargo.

This type of analysis is excellent for companies to protect each shipment, as well as to reduce costs. Seasonal lane calendars are too general and inflexible to temperature extremes. With predictive analytics, logistics leaders managing temperature-sensitive cargo, such as food and beverages, pharmaceuticals, etc., can see when they have opportunities to use weather extremes to their advantage. They can potentially reduce overspend on temperature-controlled freight when temperatures drop and take additional measures to protect freight when temperatures rise. 

Speeding Decisions

Understanding all of the variables and dependencies at this level helps companies become more agile to change, reduce costs, and have greater confidence in their decisions. The key to all of this data is having it presented in a way that makes it immediately actionable and in hand well enough ahead of time to modify plans and expectations.

As beneficial as predictive analytics are, prescriptive analytics also speed decisions. Today’s solutions are capable of alerting stakeholders of risks while also prescribing the best next action. The software analyzes all potential risks, options, and scenarios throughout the lifecycle of each shipment to determine which mitigation efforts have the greatest likelihood of success. For example, it may recommend a change in a shipment date, lane, or equipment type – days before pickup.

For companies that are serious about improving their competitive position and prioritize getting products to their destinations efficiently, reliably, and in the best condition, this type of advanced technology is a must. OTIF calculations may never be standardized, but with intelligent analytics, OTIF is attainable no matter how the retailer defines it.

Know your risks before you ship. Watch Riskpulse in action.