Increased levels of customization and particularization of every capability have made their way into all forms of business and production. The supply chain has not been able to stay out of this domain of reorganization, and as a result, supply chain segmentation is a hot topic.
Our world is changing and becoming increasingly more volatile, uncertain, complex, and ambiguous (VUCA). What does this mean for top-performing supply chains? To maintain a sustainable competitive advantage over competitors, they need to excel in three qualities:
Allocation planning plays a key role in these three processes. This detailed guide discusses allocation planning, why it’s important in supply-constrained supply chains, and how it can help supply chains achieve agility, adaptability, and alignment in a challenging post-COVID world.
Almost every production company has a continuous improvement process: an army of people is constantly working on improving operational KPI’s, like, for instance, Overall Equipment Efficiency (OEE). However, despite all the effort, results may be stagnating. Does this sound familiar? Then you most likely have the wrong focus in steering operations. In this article, our manufacturing expert Martin Dieker shares what indicators make the difference in steering your operations.
A digital twin is a highly detailed digital replica of any system that uses comprehensive data to emulate the working of the system at all times. Therefore, a supply chain digital twin is a simulation model of a supply chain. You feed the model real-time data from all sources and systems of the organizations that can exactly work out the effects of macro and micro-changes on the system using advanced analytics and learning models.
Marcus Ketter, CFO of the MDAX-listed GEA group, has had a successful start to his year. Within two years of targeting working capital, he cut down the GEA group’s working capital to sales ratio by almost two-thirds. Reducing net working capital from 906m EUR to 367m EUR has given them the flexibility they needed to move forward with the trust of the financial markets. Being named CFO of the month by the Finance Magazin is only the beginning – eleven months more of similarly impressive work could bring higher accolades and even more.
Even though it's hard to pin down an exact percentage, research has shown that on average, about half of strategic initiatives fail to be executed successfully. For those conceptualizing strategies, this is, of course, a sobering statistic: this means half the strategic work you're doing is not leading to the desired results. In this article, we'll look at some of the reasons why strategic measures aren't executed, and help you ask the right questions to increase the impact of your strategies.
In our ongoing series, the AIO Data Science teams publish tutorials that go along with AIO on GitHub. Today, aioneer Maryam introduces read_and_write. This function is necessary because often, CSV files provided by clients contain bad_lines. These are lines with too many fields, like, for instance, too many commas. As a result, these CSV files cannot be read by Qlick, so they need to be cleaned. Doing this one by one would be very time-consuming. Secondly, sometimes it is necessary to combine data files if we receive data in several files or sheets. These need to be concatenated. It would be great to be able to do this in a simple function. In the tutorial, Maryam shows you how to do this!
At aioneers, we create a lot of dashboards and do lots of machine learning tasks. Some of those analyses are done regularly. To deliver these dashboards and machine learning, we need to do a lot of data transformation, like cleaning data and joining tables. To automate data transformation, we use Databricks clusters to run Python and, sometimes, R scripts. Databricks allows us to automatically run data transformation scripts on schedule, but it is missing one essential feature: email notification on how the data was loaded.
We live in a changing world, and our environment becomes increasingly Volatile, Uncertain, Complex and Ambiguous. Over the last few weeks, we dove into the VUCA framework and the megatrends that shape VUCA. In the final article of this series, we'll put together the learnings and focus on the companies thriving in a VUCA world: competitive project-driven companies that are lean, agile and digital.
In the fifth article of our series on VUCA, we’re diving into Ambiguity. Ambiguous things are open to more than one interpretation and do not have one obvious meaning. Therefore, within the VUCA framework, Ambiguity tells us it is not clear how to interpret events. We rarely, if at all, know what effect events will have on the future. The role they will play in further developments is fuzzy.