Analysis of the operational shipping data with transportation logistics KPIs. The target is the optimization of the operational processes and quality assurance. Have a look at how to improve on your long-term logistics planning with operational transportation logistics KPIs.
Wouldn‘t it make sense to monitor the delivery rate every day and to trigger detailed data in case of problems?
Why not compare relevant KPIs between depots and highlight the strengths and weaknesses of the different processes of your subsidiaries?
Do you have access to the data that you require for calculations and supplier negotiations?
Can you rely on a dashboard that displays the current situation in a matter of seconds?
"Is the prompt understanding of key operational logistics indicators also a problem for you? In the following Case Study we discuss possible solutions."
Maximilian Kleine-Brockhoff (Sales Director)
KRATZER AUTOMATION
Joshua R. manages a freight carrier company with two subsidiaries and 80 vehicles. He is driven by high expenses and knows that it is imperative to control and monitor the cost situation for the survival of the company.
An external consultant suggests that he should make his costs more transparent by producing more detailed operational statistics (indicators).
Too many misinterpretations and possible errors during the data collection process prevents him from creating meaningful key indicators.
The average time spent for the collection of information is too high. Until now the manager has used operational numbers/indicators that his assistants have collected.
The prepared indicators are only available some weeks later. All the numbers have had to be put together from different sources. This is not acceptable for Joshua as he has to react very rapidly.
Also after such a long time it is sometimes impossible to search or to retrace some details.
Joshua wishes he could have access to all indicators the following day at the latest.
Apart from experiencing possible typing errors another potential danger occurs during the manual merging of charts (e.g. use of formulas, recopy data etc.).
The consequences are inevitable, inconsistent data sets and wrong results, an absolute no-go for BI applications!
Excel sheets that are generated manually in order to calculate KPIs is no longer a viable option for him. Joshua searches for a practical tool dedicated to analysis that calculates the KPIs, that has predefined KPIs already setup, that is easy-to use and that is available and conveniently accessible on a tablet and smartphone.
Joshua’s first step is an analysis of different BI providers. He realizes very rapidly that these providers do not succeed in solving the issue of the complexity of collection data.
Joshua’s dispatcher has the ultimate tip: a large part of the operational data is already being collected in their existing transport management system, cadis.
On further enquiry Joshua hears about the new cadis BI module that only requires activation.
Joshua can rely 100% on his data. In the past, the compilation of data was a difficult task (manual work) and now the data is already instantly available.
There are no manual intermediate steps anymore. Any new data from third party systems e.g. fuel consumption and driving style is now linked with the new analysis system through interfaces if required. By doing this has rapid access to all route data.
Joshua enjoys the rapid data availability. He can monitor the operational process at any time with live updates.
This provides more opportunities than he could imagine at the beginning.
After a few days of operation he has already detected the causes around the low delivery rate. The problems are always associated with temporary drivers. After having consulted his dispatchers Joshua decides that the occasional drivers have to be made responsible for processing less stops from now on. By controlling the work practices of the temporary drivers Joshua saves time and improves efficiency.
Joshua uses cadis for both his depots to plan and monitor his transport loads. By doing so he can start to immediately analyze the operational data he has available already. First he compares the transportation logistics KPIs of both depots. He notices significant differences in the numbers of failed collections between the two depots (collection rate). One depot shows a rate of failed collections that is 20% higher. When looking at the detailed data within the analysis tool the status “Closed” appears very often against the problem depot.
The drivers are visiting the site but they are not seeing anyone. After having spoken with the dispatchers of both depots it becomes apparent that the opening times of the collection locations are unknown to the drivers and that they are not stored in cadis.
After updating the missing data the drivers and dispatchers are now able to see the time slots and the collection rate has improved significantly.
Joshua immediately enjoys the web-based interface of the BI module. It is easy-to-use with different screen sizes and is also available on a tablet. By using the predefined basis indicators, starting to use the solution is made easy and provides the user with an initial overview in a short space of time.
Samuel T. - CEO: “I have found at last the transparency that I required for the management of my company. With practical transportation logistics KPIs the plan vs. the actual activity can be monitored and detected immediately and I can take countermeasures. After a short period of time we already have noticed a remarkable improvement e.g. in matters of trip efficiency and delivery rate.”
