Decision automation is becoming increasingly popular across many sectors, and supply chain logistics is no exception. In the coming five years, decision automation will have a major impact on how supply chain operations are planned and managed.
One of the most immediate and observable effects of decision automation in supply chain logistics will be increased efficiency. Advancements in technologies such as predictive calculations, machine learning, natural language processing and computer vision all allow for much greater speed, accuracy and performance levels when it comes to task completion and escalation. This means that complex tasks previously requiring human input can now be done much faster, allowing organizations to optimize their production and delivery times while reducing costs associated with manual labour.
Decision automation, however, can be applied across all areas of the supply chain, regardless of how simple or complex. By combining process automation with financial calculations, data analytics, and machine learning, businesses can achieve greater efficiency, accuracy, and profitability while improving risk management. Here are some examples of how decision automation can be applied to simpler areas of supply chain management.
- Procurement and Sourcing: By automating the process of selecting the best suppliers and negotiating contracts, businesses can save time and money. Procurement automation software uses algorithms to analyze procurement data and make recommendations on the best suppliers and products to purchase.
- Inventory Management: Inventory management is another area of supply chain management that can benefit from decision automation. With automated inventory management systems in place, businesses can keep track of inventory levels and easily identify when they need to restock.
- Order Fulfillment: Automating the order fulfillment process enables businesses to manage their inventory levels more effectively, reducing costs and eliminating human error. By automating this process, businesses can ensure that customer orders are fulfilled accurately and in a timely manner.
These are ideal for starting your move into Decision Automation, to gain experience for your team and get early wins. Businesses that have more experience with Decision Automation or have deeper complexity can get more granular.
- Logistics and Transportation: Decision automation is particularly beneficial for complex areas of supply chain management such as finance, logistics, and transportation. With increasing demands for rapid delivery times and reliable service, automation can help businesses effectively optimize routes, reduce delivery times, optimize vendor financing relationships, and manage inventory levels in transit.
- Demand Planning: Demand planning is another complex area of supply chain management that can benefit from automation. By analyzing historical sales data and other relevant factors, businesses can accurately forecast demand and adjust inventory levels accordingly.
- Risk Management: With a wide range of potential risks associated with supply chain management, risk management is an increasingly important area of focus for businesses. By using decision automation to predict and respond to risks, businesses can reduce the likelihood of costly disruptions and ensure continuity in their operations.
In addition, decision automation can also help create better visibility across entire supply chains by providing detailed insights into current operations. This level of intelligence gathering allows organizations to gain a clear picture of all relevant processes within their supply chain – from forecasting demand to managing competing priorities – so they can quickly identify potential problems before they become costly mistakes.
It's this kind of Decision modelling that is a key component of decision automation. It involves analyzing data to identify patterns and trends that can be used to inform decisions. This process helps SMEs understand the implications of different scenarios and make informed choices about how best to proceed. Additionally, decision modelling allows SMEs to identify areas of waste or inefficiency that can be addressed with automation solutions.
Decision automation can be used in a variety of ways to save money for SMEs. For example, automated systems can be used to manage inventory levels, track customer orders, process payments, and generate reports. Automation also makes it easier for SMEs to keep up with changing market conditions by providing real-time data about sales trends and customer preferences. This information can then be used to make informed decisions about pricing strategies or product offerings.
In addition to cost savings, decision automation can also provide other benefits for SMEs. Automated systems can help reduce human error by ensuring accuracy in data entry and processing. This helps to minimize costly mistakes that could lead to lost revenue or dissatisfied customers. Automation also allows businesses to respond quickly to changes in the market or customer needs without having to manually adjust their processes which, in turn, can help businesses stay compliant with regulations by ensuring that all necessary paperwork is completed accurately and on time.
In the coming years, automated financing is expected to have a major impact on supply chain logistics. Automated financing can streamline the entire process of acquiring goods and services, making it simpler, faster and more cost-effective than ever before. By automating processes such as invoice processing, payments and reconciliation, companies can save time and money and also expected to make a huge impact on the way that data is collected and utilized within the supply chain. By using predictive analytics, machine learning and AI-powered systems, companies can derive valuable insights from their data to make better decisions faster. This can help organizations gain a competitive edge by being able to anticipate customer needs before their competitors.
This level of intelligence gathering allows organizations to gain a clear picture of all relevant processes within their supply chain – from forecasting demand to managing competing priorities
Credit decision engines are also beneficial for SMEs looking to automate their lending processes. These engines use algorithms to analyze data and provide recommendations on loan applications quickly and accurately. This helps reduce the amount of time spent reviewing applications manually while ensuring that only qualified applicants receive loans.
Finally, decision automation can provide more accurate data on customer preferences which could help improve customer satisfaction rates. By harnessing predictive analytics, companies can make better decisions regarding order quantity, delivery times and customer service quality which should result in an overall improvement in customer experience.
In conclusion, the use of decision automation in supply chain logistics is set to have a major impact over the next five years as businesses continue to adopt these technologies and reap the rewards of improved efficiency, visibility and customer satisfaction.