Measuring customer service in manufacturing industries can be a complex task. If you are lucky and can ship from finished goods, the frequently used customer service measure of OTIF (On Time In Full) is easy to understand and measure.

However, if you must manufacture or assemble the product before you can ship it, the gap between the receipt of the customer order and shipment opens a window in which things may change.

You may wish to give careful thought to how you now measure OTIF, so as not to create an inaccurate measure. The sections below discuss the different dates that may need to be considered when determining the inputs into the OTIF measure.

OTIF Metrics

Customer performance metrics worth monitoring:

  1. The customer requests a delivery date e.g. ex-factory. (1st requested)
  2. The factory provides a promised delivery date (1st promise date).
  3. The customer requests an earlier or later delivery date (current request).
  4. The factory is able to adjust their delivery date to meet the new requested delivery date and informs the customer (last promise).
    1. The new promised delivery date may not meet the customers request, but the company cannot improve it further.
  5. The factory informs the customer that for unavoidable reasons that the promised delivery date is being changed (last Promise).
  6.  A count is kept of the number of times the customer changes their delivery requested date (customer change count), as well as the number of times the factory changes the promised delivery date (factory change count).
  7.  Items 3, 4 and 5 above can repeat a number of times.
  8. All the while, the factory has an expected ex-factory date associated with the works order. The works order expected completion data changes, potentially daily, as a result of fluctuations in activities in the factory.
    1. The factory does not inform the customer of the expected ex-factory date calculated by the scheduling solution, unless it impacts the promise last made and causes a delivery delay which the factory cannot prevent.
    2. The factory uses the calculated delivery date to determine what actions are required to ensure that the order is delivered as promised.
    3. If the works order will complete much earlier than delivery is currently promised for the factory could negotiate earlier delivery to the customer.

Measurements are:

  1. Delivery % against the last date promised (OTIF).
  2. Delivery % against the last received customer request.
  3. Delivery % against standard lead times.
  4. We can measure the number of days between the last date requested and the date delivered.
    1. We can use this to better understand customer expectations of delivery lead times vs what the factory delivers.
  5. We can count the number of times the factory or customer changes their delivery or expected delivery date.
    1. We can use this to try and understand what causes this volatility.
  6. The number of days from order receipt to delivery by product class, to understand what actual factory lead times are.
  7. We can measure the response times between customer requests and factory responses concerning date changes, to understand how responsive the factory is to customer requests.
  8. The company can experiment with different measures to better understand how dynamic the sales order and manufacturing promise environment is.

Gaming the system

You can expect the system to change as a result of the introduction of measures. Some of the changes may be unexpected and / or undesirable e.g. the factory starts building stocks or providing longer lead times to create internal time buffers.

You will need to constantly review the changes in the system and adjust the measures or consequences of trying to improve measures to obtain a fair reflection of the environment.