There are many words used for digital process optimisation: process analysis based on big data, data mining or process mining. They all more or less mean the same thing: obtaining an in-depth view of current individual processes. While statistical information is analysed in data mining, i.e. with reference to data that exists at the time of the analysis, process mining goes one step further. This most powerful tool allows businesses to see the gaps between ideal processes and actual processes. Data mining sees the relationships among the different layers of data and uses advance techniques to find patterns in order to improve the processes.
Some warehouses are outsourced nowadays to a third-party logistics (3PL) service provider for efficiency reasons. This enables the ordering party to save money and the companies offering warehousing enjoy improved utilisation rates. The sector calls this “complete handling of an all-round logistics process”. Those who can suggest innovations here, which can also be used beyond national boundaries, have a clear advantage.
Huge amounts of data accrue, particularly in the world of logistics. The trick then involves bringing together this data and enhancing it. “In order to optimise matters in warehousing, for example, it’s necessary to manage a warehouse efficiently while saving costs and resources – or reorganising it accordingly,” is the approach adopted at Rhenus Warehousing Solutions. However, the process mining concept is the greatest opportunity and the IT-based tools can create a degree of transparency for all the processes, which has never been possible in the past.
One trend has caught on, not just in production, but also in warehousing during the last few years: in addition to a much greater emphasis on the individualised production of all kinds of items, distribution has become increasingly customer-focussed. What formerly hardly seemed to make economic sense, is now technically possible with the help of modern IT platforms and can also be implemented in a cost-effective manner.
“Particularly because things are becoming smart now and objects have network access through the Internet of Things, it’s possible to clearly identify them. That’s exactly where process optimisation programmes kick in,” Henny Zhang, Business Intelligence Specialist at Rhenus Warehousing Solutions, emphasises and adds, “We’re not only able to see which processes are running at the time and how they are connected to each other. We also get an in-depth view of the complete process flow. So, we can easily allocate where our bottleneck or waste is and respond in time, thus almost obtaining a view of the future.”
This is a crucial advantage, particularly for warehousing. If warehouses in the past were geared towards large quantities or stockpiling, it is now essential to be able to directly respond to strong fluctuations in demand at a time when online orders are increasing. It is irrelevant whether the products are clothes, technology or food. The customer requires next- or even same-day delivery, without any delays or reasons for complaints due to the wrong item being delivered. In that sense, logistics has become an important part of customer satisfaction.
The old saying “Quality needs time” has become obsolete. Final customers do not want to wait. On the contrary, they expect quality – now, always and everywhere. At the same time, the new power exerted by customers can be particularly felt in the e-commerce sector through online assessments. “More effective, more flexible” is the slogan that has to be handled by outsourced warehouse operators for the benefit of the ordering party and particularly for the benefit of customers. The question is: are these kinds of warehouse data universally relevant or are they linked to individual sites?
“That’s already a challenge at a warehouse that has, for example, 53,000 square metres with a wide variety of goods on four floors,” says Marta Kunikowska, who works for Rhenus in Poland. Even small optimisation measures for the specific warehouse positions of items or improved routes and even the size of the warehouse stocks or more flexible times for deliveries and pick-ups can have an enormous effect. “We also have to be prepared for unexpected demand at any time. And that’s not only relevant for warehousing, but also when deploying personnel. It’s an enormous help if we obtain a reliable forecast so that we’re able to plan the manual work in advance.”
Other regions where the logistics specialist is operating – in France or the Netherlands – believe that scalability provides a great advantage. “That is to say, one solution, which has been found at one of the Group’s business sites, can generally be implemented at other locations across the Rhenus network,” says Audrey Chaudron, European Special Project Manager at Rhenus Warehousing Solutions in France, for example. And Henny Zhang adds, “This kind of live tracking is enormously helpful for our work. We can then provide the same service quality at all our worldwide locations, for example – with ideal flexibility levels.”
Optimising processes, however, goes beyond live tracking. The forecasts about future developments, some of which fluctuate a great deal, are even more exciting. As a result, a logistics specialist like Rhenus Warehousing Solutions is able to respond both in terms of goods and personnel at an early stage. “Where are the bottlenecks in the processes and where are there still weak points in the chain?” Big data can provide an enormous benefit here too, if the analysis of current processes can access “old data” – i.e. combine data mining and process mining.
“We enter our history data into the system – sometimes with unexpected results,” says big data specialist, Zhang, whose team introduced this tool at the logistics specialist in the Netherlands as early as 2019. “When analysing the previous data and comparing it with the current processes, we achieved approximately 90 percent agreement with our own forecasts. That was to be expected. However, we were amazed by the information that came to light regarding process optimisation with ten percent of the forecasts achieved by means of data analysis.”
Bringing together skills, expertise and technologies is the key to success – not just in warehouse management. That is why Rhenus has established a four-stage process optimisation protocol. The first stage involves what is known as process monitoring, i.e. scrutinising the individual processes. This stage alone can already reveal a great deal about efficiency or optimisation opportunities. Benchmarks are set on this basis during the second stage, i.e. a standard to compare services, and this is important when setting key performance indicators (KPIs).
The third stage then involves analysing the data “in an advanced form”. These advanced analytics provide some idea of the future and are therefore important for predicting success models. The fourth stage finally involves artificial intelligence, i.e. big data applications for automating business processes. Zhang is absolutely convinced, “This is the combination that finally gives us the framework for successful digital transformation.”
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