OTIF – Measure to improve service

Introduction

The OTIF (On-Time In-Full) is an important indicator used to measure the service level of numerous companies, in different industries and at different levels of the supply chain. As the name implies, it measures the accuracy of fulfilling customer orders in two dimensions: on-time delivery and the quantity requested in the order. There are some references, as placed in this Beatris Huber's post about performance in the delivery process, which considers that the full must consider the “perfect order”, that is, not only the correct quantity, but also in perfect condition, with complete documentation, etc.

Currently, many companies define their goals and place great importance and expectations on this indicator, since the quality of service is a relevant form of differentiation in the market. However, it is very common to have doubts in the selection of the calculation method, which can be quite different and make the indicator more “basic” or “acid”, in the sense of presenting high or low values ​​depending on the calculation method and any tolerances . This post addresses the different existing forms of calculation and some aspects considered when choosing the method.

Calculation Methods

The OTIF is, in general, a binary indicator, that is, it assumes a value of 0 or 1. For each order, it is evaluated whether the time portion (on time) and quantity (full) was met, and if so, the order receives OTIF 1. If one of the installments has not been reached, the indicator assumes a value of 0. However, the complexity in the calculation begins with defining which aspects will be considered to define whether each one of these parcels has been met.

No article "Defining 'on-time, in-full' in the consumer sector" from McKinsey & Company, some existing forms of calculation are discussed, as shown in Figure 1. When thinking about the dimension of time (on-time), it is possible to consider some different references to the delivery date. There are cases in which the calculation of the indicator's time portion considers the original date, that is, the one defined at the time of placing the order. This date may be related to an SLA, previously agreed with the customer, or may have been defined at the time of placing the order by the commercial team. Another way of calculating the deadline can consider the scheduling for the delivery of the order, that is, the date that the supplier and the customer defined as the deadline, which can be different from the previous date due to delivery windows, holidays, etc. Finally, there is another reference, the agreed date, which would be the date on which the supplier and customer defined as the date with the highest probability that delivery will actually occur. The need to change the “original” and “scheduled” date to an “agreed” date can come from the customer or the supplier and have numerous reasons, such as problems in order production, lack of storage space, delays in shipment, etc.

In the quantity dimension (in-full), there are also different forms of calculation. A Order Fill, binary form that only considers 1 if the order delivered the complete quantity for the entire order; O Line Fill, binary form that considers each order line, that is, each SKU, as an item to be evaluated as 0 or 1; and the non-binary form Case Fill, which considers the percentage of the total volume that was fulfilled for a given order.

Depending on the references used to calculate the OTIF, the stipulated value for the indicator can vary dramatically. We can have a “more acidic” or more severe indicator, which considers the original date and order fill, or a “more basic” or softer indicator, which considers the agreed date and the case fill. In the case of research conducted by McKinsey and the Trading Partner Allaince (TPA), which analyzed 24 large retailers and consumer goods industries, most use the most “acid” way to calculate the on-time, which would be the original date, together with the most “basic” way to calculate the in-full, which would be the Case Fill (Figure 1). There is also the possibility of considering tolerances on the selected value, that is, the on-time consider the original date, but with a delay tolerance of up to 1 day, for example.

Figure 1 – 79% of respondents use the form Case Fill for the calculation of in-full, while 67% use the Original Date for the on-time. Source: McKinsey & Company.

How to Define the Proper Calculation Forms

O ILOS Customer Service Overview presents a survey carried out with the main retail players and the industry's main logistics performance indicators in three major segments: hygiene/cleaning, perishables and non-perishables. For the three sectors analyzed, the highest degree of dissatisfaction is related to consistency in the delivery time and the order cycle, with availability appearing in third place (Figure 2). This shows how indicators that measure deadlines and quantities, such as OTIF, are fundamental for companies to measure the quality of their service and manage to improve their logistics performance. But, for that, it is essential that the indicator is being measured properly, to correctly reflect the degree of satisfaction in the customers' view.

Figure 2 – Degree of Dissatisfaction with Market Practices (Rio de Janeiro and São Paulo). Source: ILOS Overview of Customer Service (2015).

To define this most appropriate form of calculation, it is necessary to consider aspects of the segment in which the company operates and the expectations of customers regarding the service offered. There are sectors, for example, in which the order backlog is relatively small (few orders), but voluminous (large volume of items per order), and in these cases consider the Order Fill can be very clustered and greatly harm the indicator, and perhaps the Case Fill be more suitable. On the other hand, if the customer has very high expectations regarding the perfect order quantity, consider the indicator Order Fill may be more suitable.

With regard to deadlines, the original date may be the closest to the customer's expectations regarding the quality of the service offered. However, the customer often has a series of uncertainties in his operation and needs to reschedule the delivery of an order with his supplier. In these cases, in which changes happen very frequently at the request of the customer, it seems to make sense to consider the agreed date, since the request came from the customer and this new deadline should not penalize the indicator.

In addition to the metric used to calculate the on time and full, it is possible to consider some tolerances of deadlines and quantities, that is, “the original date + 1 day”, or “the total quantity per order ± 5%”. As long as these tolerances do not affect the customer's perception of service, they can be used to better align the service promise with the company's operational capabilities.

Conclusion

In short, the calculation method can consider different aspects, but the key point is to have the metric aligned with customer expectations. It is necessary that the indicator represents the level of customer satisfaction regarding the service and the calculation method needs to be clear to them as well. In addition, it is indicated that the indicator is managed so that, regardless of the absolute value it assumes, there is monitoring and improvement actions so that customer satisfaction with the service provided grows, allowing the company to obtain an important competitive advantage in its sector.

O 28th International Supply Chain Forum, which will take place between October 18 and 20, 2022, in person and online, will feature an Intelligence in Operations trail, bringing Brazilian and international cases to discuss the best practices and solutions currently adopted by large companies. For decision makers in supply chain and logistics, it's an excellent opportunity, it's worth participating!

References:

- ILOS Reports

– FourKites – Maximizing On-Time In-Full (OTIF) In The Supply Chain

– McKinsey & Company – Defining 'on-time, in-full' in the consumer sector