Top 5 Supply Chain Management Software Requirements

Businesses from the logistics, manufacturing, and retail sectors can hardly stay afloat with the ever-changing supply chain management software requirements. Just having SCM software is not enough to meet high industry standards. As IT solutions become outdated on average every 2-5 years, a company’s software needs to be regularly upgraded to keep bringing real value to a business.

Exoft is a leading logistics software development agency. We offer businesses holistic, end-to-end transportation solutions. Over the last decade, we've helped logistics companies pursue ambitious business goals. We develop innovative custom logistics software that simplifies supply chain management by automating and streamlining processes.

Today, we’ll discuss the best innovative SCM software features you can implement in your existing system to meet the latest requirements and enhance its effectiveness.

Top Features and Requirements for Supply Chain Management Software

The effectiveness of software solutions is pivotal for successful supply chain management. When top-notch technologies such as Artificial Intelligence (AI), Internet of Things (IoT), and Big Data take center stage, it is crucial to strike a balance between implementing advanced features and automating fundamental processes.

In this section, we will explore the best supply chain management software features you can implement to master dynamic industry requirements, cost-effectiveness, and customer satisfaction. The table below provides an overview of five key features, accompanied by examples of their implementation solutions.

We will delve into each feature, exploring their significance, implementation solutions, and how they contribute to optimizing supply chain processes. From predictive analytics reshaping strategic planning to real-time replanning automating inventory management, these features collectively enhance transparency, efficiency, and adaptability throughout the supply chain. Let’s explore how each feature contributes to the evolution of supply chain management in detail.

Predictive analytics

The AI-powered analytical functionality allows supply chain managers to get accurate predictions of market trends, customer demands, and other essential internal and external factors. As a result, advanced forecasting features enable better strategic planning and facilitate more informed decision-making at every stage of the supply chain (see the chart below).

But not only that. Adding predictive analytics to a supply chain management system can also make you completely rethink how your business generally operates. For instance, Amazon and other market leaders are actively working on so-called “predictory shipping.” It will allow companies to start a delivery process before a customer even orders a product. Let’s look at some implementation solutions for predictive analytics.

Demand forecasting

Predictive analytics allows businesses to forecast future sales and customer behavior. Using sophisticated machine learning algorithms, you can analyze historical data and market trends. Dynamic forecasting models can adjust predictions in real time based on factors like promotions, seasonality, and unexpected events, modifying forecast confidence levels.

Inventory optimization

You can use predictive analytics for dynamic inventory optimization by continuously monitoring demand patterns, supplier performance, and market trends. It empowers supply chain managers to determine optimal stock levels to meet demand. This way, you reduce excess inventory costs, minimize stockouts, and enhance overall supply chain efficiency.

Risk assessment

Integrating risk management parameters into predictive analytics models, you can identify potential disruptions and assess their financial impact on the supply chain. Machine learning algorithms and scenario analysis enhance risk mitigation strategies. It allows supply chain managers to address challenges proactively and maintain operational resilience.

Predictive maintenance

Advanced analytical software can predict equipment failures to prevent downtime. Machine learning algorithms and IoT sensors gather machine metrics, analyze data, and forecast potential failures. It enables precise repair scheduling and minimizes disruptions. An optimized maintenance schedule extends the lifespan of critical supply chain materials and assets.

Real-time replanning

Fast and error-free inventory management is one of the greatest challenges retail and logistics businesses face. A real-time replanning feature has the potential to resolve it once and for all by automating the entire process. This approach, also known as “zero touch order processing,” is mainly aimed at eliminating required manual intervention from the moment of order intake to the moment of order fulfillment.

In particular, real-time replanning functionality allows for constantly monitoring inventory levels, ad hoc planning of replenishment and production schedules, instantaneous order confirmation, and delivery setup. In addition, the advanced version of this feature lets customers reroute the shipment or change the delivery time via a mobile application.

Automated order processing systems

End-to-end automated order processing systems can help you eliminate manual intervention throughout the order fulfillment process. Barcode scanning, RFID technology, and automated data capture streamline order processing. AI integration further enhances the system with real-time data analysis. It allows for automatic adjustments to production schedules, inventory levels, and order fulfillment processes for increased efficiency.

IoT-enabled inventory management

Implementing IoT devices across the supply chain enhances real-time visibility into inventory levels. IoT-enabled inventory management facilitates continuous real-time monitoring of product movements and conditions. It provides automatic and accurate tracking through RFID technology and sensors, supporting dynamic replenishment processes.

Dynamic routing and delivery management

Dynamic routing utilizes intelligent algorithms that adapt in real time based on traffic, weather conditions, and order priorities. This approach significantly reduces delivery times and enhances overall operational efficiency. It allows for a more adaptable and customer-centric supply chain management strategy.

Blockchain for supply chain transparency and traceability

The use of blockchain technology in real-time replanning ensures a secure and immutable record of transactions in the supply. Blockchain facilitates efficient order processing, minimizes manual intervention, and provides a decentralized and transparent ledger. It reduces disputes and delays in the delivery process.

Machine learning-driven predictive replanning

Utilizing machine learning for predictive replanning involves continuously analyzing real-time data to predict potential disruptions or delays in the supply chain. This solution enhances adaptability by automatically adjusting production schedules and inventory levels. It enables proactive decision-making and improves overall supply chain responsiveness.

Simulation models

The delivery of goods has always been associated with many risks, especially when entering new markets or offering unconventional services. Simulation functionality added to management software (either SCM or ERP) can significantly mitigate most of them by digitally representing the real-world systems with all the products, customers, vehicles, warehouses, etc.

Today, most simulation models are built with machine learning technology in the core. Hence, besides identifying high and low-impact events, they can analyze a vast amount of data and improve the accuracy of predictions over time. In addition, a simulation model may be connected to an actual supply chain with the help of IoT technology, making them a digital copy of the latter. Such digital twins take visibility to a new level and help the company’s management optimize the processes.

Machine learning-enhanced risk analysis

Simulation models use machine learning algorithms to analyze historical data, identifying potential risks and disruptions in the supply chain. The models are further strengthened by integrating external data sources like weather forecasts and geopolitical events. It enhances the accuracy in predicting potential disruptions. To ensure adaptability to real-world conditions, the models are continuously updated with real-time data from IoT devices.

Digital twins with IoT integration

To create digital twins in the supply chain, IoT devices are integrated to replicate real-world systems. These digital twins improve visibility and optimization by connecting directly to the live supply chain. IoT sensors capture real-time data on product movements, environmental conditions, and equipment performance, enhancing the accuracy of these digital twins. Implementing machine learning algorithms within these digital twins allows for process optimization, prediction of bottlenecks, and simulation of various scenarios.

Scenario-planning and optimization tools

Scenario-planning and optimization tools manage uncertainties dynamically and streamline operations. They provide insights into potential outcomes by creating and evaluating various scenarios. It enables proactive risk mitigation and strategic decision-making. Integration of algorithms ensures real-time adaptability, optimizing inventory, production, and distribution strategies. It reduces costs and minimizes inefficiencies.

Continuous learning and improvement simulation models

Incorporating mechanisms for continuous learning within simulation models enables them to adapt and refine their predictive capabilities over time. These models undergo iterative improvements by integrating feedback loops that capture insights from real-world supply chain performance. It ensures a more accurate reflection of dynamic operational conditions. This approach enhances the reliability of simulations and contributes to a more responsive and effective supply chain management strategy.

Full-view tools

Nowadays, supply chains become more complex and their management requires greater visibility. This means that the top company’s officers need to have an opportunity to take a bird’s eye view of all the processes in real time. On the other hand, logistics managers of the lower level of seniority should be able to monitor even the most minor operation and track products in transit up to their final destination.

To reach such a level of transparency throughout the supply chain, companies must supplement their logistics management software with advanced functionality based on AI and IoT technologies. Its implementation will likely require significant investments at the beginning since you’ll need to upgrade not only your software but also the hardware. However, a business will also get many benefits which include saving costs, greater performance, improved automation, and ultimately — enhanced customer satisfaction.

AI-powered supply chain dashboards

With AI-driven dashboards, you gain real-time, holistic perspectives across the entire supply chain, from raw material sourcing to product delivery. These dashboards use machine learning algorithms to analyze data from diverse sources, offering executives actionable insights. You can customize the dashboards to manage different access levels, ensuring the delivery of relevant and strategic information for each role.

IoT-enabled supply chain monitoring

Integrating IoT devices throughout the supply chain enables real-time monitoring of product status, equipment conditions, and inventory levels. You can get detailed insights into their location, condition, and estimated arrival time by employing sensors and RFID technology. AI algorithms analyze the vast array of data IoT devices collect, generating timely alerts and recommendations that optimize various aspects of supply chain processes. It ensures higher visibility and control within the supply chain ecosystem.

Cloud-based supply chain platforms

Shifting towards cloud-based supply chain platforms provides scalability, accessibility, and real-time data synchronization. With cloud computing resources, these platforms efficiently process and analyze large volumes of data. It facilitates swifter decision-making and amplifies the visibility of supply chain activities. Stakeholders can monitor and manage operations, adjusting permissions to different organizational roles.

Mobile-friendly supply chain management platforms

Mobile-friendly supply chain platforms offer on-the-go access to vital information through intuitive interfaces. Responsive design enables efficient monitoring and real-time decision-making, ensuring a consistent user experience across devices. Benefits include enhanced data accessibility, improved agility, and streamlined operations.

Collaboration features

Even the most basic supply chains usually involve several companies as well as many people who perform different tasks. Naturally, to complete all deliveries successfully, everyone participating in the process needs to stay constantly connected and informed on the key events. That’s why modern supply chain management systems have to contain collaboration tools for internal team and external partners.

The list of exact features aimed at the enhancement of collaboration will depend on the specifics of your business processes. For example, this may be something simple like communication and task assignment platform (see the chart below).

Alternatively, you may consider upgrading your supply chain software with more advanced functionality that includes status reporting, document management, inventory alerts, self-service portals for customers and partners, enhanced traceability, etc.

Unified communication platforms

Integrating communication tools into the SCM system fosters real-time collaboration among internal teams and external partners. Essential features such as chat, video conferencing, and document sharing, enhance communication efficiency and information sharing. It promotes effective and cohesive interactions throughout the ecosystem.

Document management and workflow automation

Document management systems ensure secure storage, sharing, and version control of essential files. Workflow automation streamlines approval processes, minimizes manual errors and improves collaboration efficiency. Additionally, the e-signature feature expedites approval workflows, ensuring the integrity of contractual agreements.

Advanced collaboration analytics

This solution employs sophisticated algorithms to analyze data from various collaboration tools, offering granular insights into team interactions and communication patterns. By identifying bottlenecks and areas for improvement, these analytics enable organizations to optimize workflows, enhance productivity, and foster a more agile work environment.

Cross-platform integration

Integrating supply chain management platforms with other enterprise systems and tools helps to enhance collaboration. It facilitates seamless communication, data exchange, and mapping among internal teams, external partners, and suppliers. This way, you eliminate silos and enhance the sharing of information across various enterprise systems.

Challenges in SCM Software Implementation

For businesses, implementing supply chain management (SCM) software comes with its hurdles. This section explores key challenges logistics companies encounter while integrating SCM software into their operations.

Ensuring User Adoption and Training

When implementing SCM software, you need to take care of widespread user adoption and effective training. Overcoming resistance to change is crucial for maximizing the software's benefits. Establish adequate training programs to empower users with the skills and confidence to utilize the software seamlessly. It will foster a smooth transition and minimize disruptions to daily operations.

Data Migration and Integration Complexity

Migrating existing data and seamlessly integrating the new SCM software with other systems is complex. Accurately transferring historical data and real-time synchronization with other enterprise applications requires meticulous planning and execution. This will help you maintain data integrity and prevent information silos. Ultimately, it will enable a cohesive flow of information across the entire supply chain network.

Balancing Customization with Standardization

While customization allows tailoring the system to specific needs, its excessiveness can lead to increased complexity, longer implementation times, and challenges in future upgrades. Striking the right balance ensures that the SCM software aligns with unique business processes while still leveraging standardized features. It will facilitate scalability, maintenance, and compatibility with industry best practices.

Managing Costs and ROI Expectations

Managing costs and ROI expectations is an enduring challenge in SCM software implementation. You need to carefully manage upfront costs, including software licenses, implementation services, and potential disruptions. Conducting a thorough cost-benefit analysis and strategic financial planning will help you to establish realistic expectations for achieving ROI. This way, you align budgetary constraints with the long-term strategic benefits of the SCM software.

Keeping Up with Technological Advancements

Staying up-to-date with emerging technologies, industry standards, and software updates ensures the longevity and relevance of the implemented system. Establish mechanisms for continuous improvement. Regularly updating your SCM software, you will leverage new features, enhance security, and adapt to evolving industry requirements. Maintain a proactive approach to technological innovation and incorporate advancements strategically.

Wrapping-up

The disruptive technologies such as artificial intelligence and the Internet of Things have a great impact on the way the supply chain management evolves. Hence, to remain relevant and effective, SCM systems should be constantly upgraded with new functionality. Otherwise, a business will be able to meet neither market requirements nor ever-growing customer expectations.

Exoft leads the way in logistics software development , enabling logistics companies to accomplish ambitious business objectives with innovative SCM features. We customize our logistics software solutions to each project's unique requirements and complexity to simplify operations and streamline supply chain management.

Reach out to us to discuss the requirements for your SCM software.