Dive deep into the supply chain with advanced analytics
As digitalization advances, companies are gaining more and more valuable insights into their supply chains – in the form of large amounts of data. However, how this information is used is crucial. Transparency of processes through good data is particularly relevant in dynamic systems such as supply chains. Detecting and correcting delays, bottlenecks or disruptions at an early stage – ideally before they actually affect the supply chain – saves time and money. This is where advanced analytics comes into play: it represents a forward-looking approach to data analysis that uses technologies such as AI (artificial intelligence) and machine learning to make data-based predictions and decisions. In this blog post, you will learn how companies can use advanced analytics as a comprehensive planning tool to optimize their supply chain management and prevent problems along the supply chain.
What are advanced analytics?
Advanced analytics enables companies to gain valuable insights into their operational processes by using historical data and statistical algorithms. Various analytical methods are combined to create the most comprehensive knowledge base possible:
Descriptive analysis forms the basis for all analytical procedures, as it focuses on the documentation, summarization and investigation of past events. Through the use of data mining and data aggregation methods, patterns, correlations and developments are identified. This provides companies with a detailed overview of their past performance, allows them to identify weaknesses and draw conclusions for future decisions. However, the analytical view remains focused on the past.
In predictive analysis, statistical algorithms access historical data to create well-founded forecasts. Various data processing techniques are used, such as data cleansing, data integration and scaling. Future events or trends can thus be predicted on the basis of accurate data. Companies use predictive analytics to minimize risks, identify opportunities, use resources more efficiently and make better decisions.
Prescriptive analytics goes one step further. It not only aims to predict future events, but also to provide specific recommendations for action. Advanced algorithms capture the status quo and historical data, analyze it and evaluate it. Well-founded simulations are used to identify the best options for action in complex scenarios and recommend appropriate measures. Companies use prescriptive analytics to increase efficiency and optimize strategic decision-making. For example, it can determine the best steps to avoid bottlenecks or waste, leading to higher profitability.
In addition, there is real-time data analysis, which analyzes data as it is generated, collected or updated. This process is particularly important in dynamic application areas such as supply chain management, because the more data that is processed and evaluated without delay, the more precisely supply chain processes can be monitored and controlled. Companies can immediately identify and quickly respond to problems such as delivery delays, bottlenecks or demand fluctuations. This helps to reduce costs because companies can proactively take action before problems escalate. Real-time data analysis is thus a valuable tool for increasing competitiveness in an often unpredictable supply chain landscape by increasing agility.
How advanced analytics is revolutionizing supply chain management
Advanced analytics has so far been the domain of highly qualified specialists. However, advanced analytics tools and user-friendly software platforms with intuitive data visualizations are now making it accessible to more and more users. The employees responsible in the company no longer need to understand in detail which variables influence each other, because the powerful analysis tools also solve complex tasks fully automatically. The time and expertise needed to set up and establish advanced analytics in companies has been significantly reduced as a result.
Our software-as-a-service solution S2data Platform, including the advanced analytics tool, offers precisely this combination of detailed, fully automated analysis and transport planning, easy integration into existing systems and excellent user-friendliness. For example, the software offers intelligent 3D loading space planning based on load weight, length and volume, taking into account aspects such as stock levels, production utilization and capacities. With the help of data from transport management, warehouse management and ERP systems, a detailed transport plan is generated that incorporates all factors relevant to planning along the supply chain and offers optimal transparency. This is how we are shaping the future of supply chain management. In the age of big data, the possibilities for data evaluation are becoming more and more extensive – and the insights correspondingly more precise. Our transport planning, including TCO (Total Cost of Ownership), directly highlights parameters in need of improvement, thus minimizing transport costs. Using the technical possibilities for more efficient transport planning not only reduces the workload, but also provides a clear competitive advantage.
Automatic reporting
In addition, our reporting tool enables the creation of reports that transparently show the efficiency of companies. Based on these reports, services can be adjusted as needed to better achieve strategic goals. This also applies to the topic of sustainability: thanks to the extensive data available, progress towards climate neutrality, for example, can be tracked and documented. Read on to learn more about our CO2 reporting options and AI-based transport optimization as a solution for meeting sustainability goals.
Efficient use of resources
Modern supply chain management using advanced analytics offers the advantage of being able to move from a reactive approach to problem solving to a proactive one. The advanced analytical methods detect disruptions early on, giving companies the chance to take action in good time. What’s more, the algorithms identify patterns and trends that would be difficult to discern manually. Detailed demand forecasts can help to avoid supply bottlenecks and optimally manage inventory levels. Particularly when managing limited resources, such as storage space, transport and production capacities, it pays to use advanced analytics to identify and directly exploit optimization potential. Managing inventory with foresight and switching to just-in-time warehousing, for example, helps to reduce stocks to the necessary minimum and avoid having to manage unnecessary quantities in storage.
The S2data software solution is able to precisely align the demands on stock levels and necessary resources. Personnel, warehouse, production and transport capacities are automatically aligned, enabling more efficient resource planning, warehouse management and a reduction in capital lockup through stored material. These process optimizations ensure that all resources are used optimally and unnecessary costs are avoided. This enables our customers to reduce their costs by a quarter. Read on to find out how improved transport management increases efficiency.
Optimized route and tariff planning
Route planning is another prime example of a logistical challenge where advanced analytics facilitates management. Variable transport costs, different delivery times or stopovers – a range of complex factors need to be taken into account, which is why manual planning is often a lengthy and complicated process. Algorithms calculate the optimal route, taking into account efficiency targets such as minimizing total mileage, the number of shipments, transport costs or CO2 emissions.
Our software tool uses artificial intelligence to optimize route planning, taking into account all available tariffs and transport planning parameters – and processes all information on loading, route, tariff and mode of transport in real time. The intelligent algorithms independently choose between full truck load (FTL) and less than truck load (LTL) shipments and always determine the most efficient transport solution. This way, our customers save costs and resources. At the same time, the workload for employees is reduced, as they no longer have to manually compare information. You can get an insight into working with our innovative route planning tool here.
Conclusion: Increasing competitiveness with advanced analytics
Advanced analytics has the potential to revolutionize supply chain management. With predictive and prescriptive analytics, future challenges can be identified and proactively solved at an early stage, minimizing risks and reducing costs. Real-time data analysis ensures that problems are immediately identified and resolved, increasing agility and competitiveness.
Fully automated and user-friendly software solutions enable companies to make decisions based on advanced analytics without the need for in-depth technical knowledge on the part of their employees. The time and expertise previously required to build and integrate intelligent analysis tools has been drastically reduced.
With the help of precise demand forecasts and optimized resource planning, companies are able to manage their inventories efficiently and avoid bottlenecks. In the areas of route planning and transport optimization, intelligent algorithms make a valuable contribution to reducing transport costs and CO2 emissions, which simultaneously leads to greater competitiveness and a smaller environmental footprint.
Overall, it is clear that the use of advanced analytics in supply chain management not only helps to increase efficiency and profitability, but also represents a sustainable and future-proof solution for companies that want to compete in an increasingly data-driven world. The possibilities created by the intelligent use of data not only offer companies operational advantages, but also the chance to continuously improve their business strategies and ensure long-term success.
Find out how much your company could save by switching to intelligent transportation management.
Further sources of information:
https://www.techtarget.com/searchbusinessanalytics/definition/predictive-analytics
https://www.technik-einkauf.de/einkauf/einkaufsfuehrer/advanced-analytics-keller-kalmbach-fundierte-zukunftsprognosen-fuer-mehr-versorgungssicherheit-813.html
Sources are in german
