What can we do to increase the number of "perfect processes"? From the ordering process to delivery and receipt of payment, things can go wrong. With sufficient available data, we make predictions, correct deviations or at least plan for them. How could this look like for the complex area of logistics?
Relationships in a commercial enterprise often develop in an organic way and tell a whole story in the process. Without the possibility of objective evaluation, one often clings to existing structures - as often happens to us in our everyday lives. I think the question of why some companies are more successful than others can also be traced back to the fact that successful retailers constantly re-evaluate and continuously optimize their existing relationships: The right supplier, the right carrier and the optimal transport route are subject to constant change.
Processes in logistics challenge us through their complexity: Some goods are only important seasonally, others are perishable, short-term trends increase the demands on flexibility and cost efficiency. On the one hand, overstocks must be avoided or reduced and on the other hand sell-outs must be prevented.
At the same time, the question "What does the customer want?" always comes first, and different sales channels must be used simultaneously. Often companies still discover too few commonalities in the channels, which leads to the individual channels being treated separately. This means additional effort.
Let's imagine that a software makes the complete and objective analysis of all processes possible, and this is done by data extraction. Fast solutions and automation possibilities become "visible".
It does not matter whether a company works with many different databases and backends, and it does not have to be completely SAP-based, but all the databases involved have one thing in common: they set time stamps. Now all data points are recorded and, using Unique Identify, are combined and mapped to form an overall process.
The goals of the optimization in our case would, of course, be: punctual, complete delivery, fast order processing and, in addition, as few manual interventions as possible. Desired time parameters can also be defined in the software.
This is not just a possible analysis - the goal is to better understand the processes and their current problems. This shows us the possibilities for optimisation. For example, a first-time-right rate shows how many runs of the processes correspond to the "happy path". If it is only 44%, for example, we have to ask ourselves whether and how this can be increased.
By filtering the material groups, we can see which material causes the most delays. The same material leads to different delays in different production plants. The deviations from the "perfect process" can therefore depend on the production site.
Another filter visualizes the delivery times: The frequency of changes regarding quantity or mode of transport can be compared. A direct comparison of two distribution centres with opposing results can make a solution visible: What happens in the successful distribution centre compared to the one with the greatest difficulties?
If I can visualize the problems of a process, I can also deduce how to solve these problems and thus provide my employees with concrete and quick assistance at any time. This is especially important when interacting with my customers and in terms of a good, long-term relationship. Direct messages via bot to the employees, which transmit immediate information and contribute to quick decision making, optimize processes in a very concrete way, also with regard to the customer.
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Supply Chain Management
