As a forwarder how do you measure the risk of your operations departments? If you are like most we work with, your measures are based on milestones and KPIs. For example, how long before arrival are we clearing customs or how many jobs have been delivered and not invoiced.
Whilst this is important information, allowing you to better prioritise work and catch potentially problematic jobs early; it only tells half of the risk story. We also need to know how stable our system is.
As we know, forwarding operations are consistently impacted by external factors meaning due date measures do not correlate perfectly to operational risk. Simply being on time does not guarantee a stable system and being late does not necessarily make for an unstable system. These are the two elements of Risk which together tell the full picture and allow for better management.
What does ‘stability’ mean?
Why should you care about stability?
– Stability is an early warning radar. In many cases it predicts a slip in due date performance, allowing you to take corrective action before a problem happens.
– Indicates processes and people which have been by impacted high levels of interruptions or variation, allowing you to focus process improvements.
– Impacts your response time to customers and thus your service level reputation.
– Impacts your ability to detect problems and thus the time you have to fix them.
What does it look like to be late but stable?
Jobs are beyond KPIs/have deadlines missed yet operationally you are in control and responsive.
Let’s say you are a Customs Broker and a shipment arrives tomorrow. You usually like to have these cleared 4 days prior to ETA. However, the customer is having some trouble getting the required information through to you. You have spoken to the customer each day since it became late and are working through the problem. The job is late by your KPIs but it is also stable as you have a fast response time and good customer service, it is simply outside of your sphere of control.
What does it look like to be on time but un-stable?
Jobs are currently on time but your response time is low/falling.
Again let’s take the example of a Customs Broker. All of your jobs are currently being cleared 4 days out from ETA. However from the time a job arrives on your desk until the time you look at it has increased from half a day to two days. In this situation you are on time but quickly becoming unstable, making you less able to detect problems and respond when needed.
How do we get the best of both worlds?
A tale of two teams
Below is a graph, each line representing one of two very similar team. Let’s call them team Green and team Yellow. Their response time is recorded over several days, measured as a percentage of an acceptable time window. Response is defined as a person completing a task as far as reasonably possible at that time. For example if they found a customer had not provided all information they would need to inform the customer and get an estimated timeframe for receiving the info. Once progression is fully in the customers hands they can reschedule the task and count it as responded to.
Both teams are currently ‘on-time’ per KPIs but their stability is far from the same. As you can see, team Green clears the majority of their work within 60% of the allotted time, whereas team Yellow has a surge at the end. This indicates team Green is calm, responsive, and can reliably take on more work. Team Yellow on the other hand is slow to respond, increasing the chances of service failure and poor customer service.
Before you jump to too many conclusions, this doesn’t mean that team Yellow are incompetent. It means they are either overloaded or are subject to excessive or unforeseen variation. Once this is clear you can track down the causes and systematically improve the system stability.