A modern WMS can process big data in real-time and generate insightful reports that fulfillment providers can use to make better decisions and sustain operational efficiency. In fulfillment operations, big data encompasses information from sensors, transactions, and customer interactions.
Go beyond a traditional WMS with Logiwa IO. A fulfillment management system (FMS), it uses AI-powered data analytics and machine learning for reporting that helps drive operational scalability.
Let’s explore how to use warehouse management systems to leverage big data in decision-making and promote operational scalability.
- How WMS use big data to enable data-driven decision-making
- Enhance operational scalability with warehouse software
- Invest in advanced tracking and visibility
- Explore AI and machine learning
- Transform your fulfillment strategy with data-driven insights
- FAQs on WMS analytics, reporting, and fulfillment optimization
How WMS use big data to enable data-driven decision-making
In today’s fiercely competitive ecommerce landscape, data analytics drives warehouse and fulfillment success. Companies that transform their operational data into actionable insights gain a decisive market advantage, particularly in optimizing the end-to-end customer fulfillment experience. This direct link between data utilization and customer satisfaction has made sophisticated analytics capabilities non-negotiable for modern warehousing operations.
Thus, any insight or decision that elevates the delivery experience for the end customer is a big plus. Here’s how WMS leverage big data to inform decision-making, leading to positive outcomes for fulfillment providers.
Predictive analytics for demand forecasting
Overstocking and understocking are common problems that 3PLs and ecommerce stores face. Stockouts are particularly damaging to a brand’s reputation as it may be easy to miss delivery promises and upset customers. Such setbacks were inevitable when businesses relied on spreadsheet-based analytical methods to forecast demand.
However, companies use AI-driven analytics in warehouse management to perform more accurate demand forecasting. Predictive analytics uses machine learning algorithms to examine historical data pulled from a company’s WMS and leverages the derived insights to forecast customer demand. It also correlates historical data to the existing and expected market trends to predict demand. All these efforts facilitate proactive inventory management and resource allocation.
Real-time monitoring and decision making
Ecommerce customers expect prompt status updates from their fulfillment provider. If an issue hinders order delivery, they want ecommerce stores to notify them promptly and offer solutions. Fulfillment companies keep up with such high standards by implementing real-time inventory tracking to monitor operations as they unfold.
Logiwa’s WMS analytics empower 3PLs to optimize critical operations through real-time data, including:
- Inventory management
- Directed putaway
- Order fulfillment and tracking
- Resource allocation
- Equipment usage
- Shipping status
With real-time tracking and unfettered access to crucial operational data, 3PL providers can identify and quickly address issues to avoid extended disruptions.
Logiwa IO’s AI-Driven Analytics
Using Logiwa’s AI-driven analytics to predict potential operational drawbacks gives warehouse managers ample time to tailor short- and long-term solutions. Besides AI-driven analytics, other critical AI integrations of Logiwa IO that use big data include directed putaway and optimized picking.
Enhance operational scalability with warehouse software
Logiwa IO provides fulfillment partners with a reliable and secure platform to advance operational scalability with big data by supporting the following crucial functions.
Resource optimization
Effective labor and resource management is fundamental in scaling operations. Given that labor accounts for 60-65% of total warehouse fulfillment costs, managers must optimize its distribution to maximize utility. Besides labor, fulfillment operators should check equipment and space utilization to ensure proper use.
Process automation
A great use for big data is selecting which fulfillment processes to automate. Before a customer receives their order, it goes through several stages, such as picking and packing. With all orders following the same process, there are many repetitive tasks involved, which are great candidates for automation.
Reviewing WMS task data shows which process workers spend the most time completing every day. Assessing relevant task data metrics like warehouse throughput pinpoints the processes where automation would have the most effect. Such data-driven insights can help automate repetitive tasks that may drain the most labor and resources.
Common repetitive warehouse tasks primed for automation include:
- Picking, packing, and shipping
- Order processing
- Inventory putaway
- Inventory replenishment
- Order tracking
- Aspects of customer service
Logiwa IO’s AI-powered job optimization
Logiwa IO uses AI to improve picking and packing operations by addressing criteria such as order volumes, picking locations, and cart dimensions. AI job optimization helps warehouse managers maximize their staff’s productivity by assessing picking routes, SKU quantities and sizes, inventory spots, and storage rules.
AI job optimization enhances operational scalability by setting the foundation for high-volume fulfillment operations.
Invest in advanced tracking and visibility
Advanced tracking solutions for fulfillment enable providers to leverage big data for:
End-to-end supply chain visibility
Integrating data from different functions into one solution breaks down operational silos, giving every stakeholder crystal-clear visibility into supply chain operations. This transparency enables warehouse managers to understand the ripple effects of their decisions across the entire network, leading to smarter, more informed choices that optimize the whole system rather than just individual components.
Asset tracking and management
Tracking warehouse assets can help fulfillment providers verify resources are used productively. Advanced tracking systems offer features such as traffic analytics, warehouse pallet tracking, geofencing, forklift movement tracking, and real-time reports and alerts. These features empower warehouse managers to improve asset utilization and maintenance.
Logiwa IO’s real-time analytics
Logiwa IO provides real-time dashboards and customizable reports, empowering businesses to check, evaluate, and get key insights from KPIs and make decisions based on the data. Its powerful 3PL analytics feature empowers 3PL managers to optimize operations and derive data-driven insights that can inform proactive decisions.
Explore AI and machine learning
Logiwa AI and machine learning tools can improve predictive capabilities and automate decisions that may have a lot of different components. Integrating machine learning in fulfillment operations can help improve processes over time because machine learning can self-learn from existing data and use historical data to make accurate predictions.
Leading-edge AI warehouse technologies reshaping operations today include:
- Smart picking solutions powered by robotics, voice-directed systems, and light-guided technology
- Intelligent inventory management platforms that optimize stock levels in real-time
- Advanced storage and retrieval systems that maximize space utilization
- Streamlined systems for document insertion
- Automated Guided Vehicles (AGVs) performing towing, forklift operations, and unit load transport
- Autonomous Mobile Robots (AMRs) revolutionizing picking assistance, inventory movement, and sortation tasks
Transform your fulfillment strategy with data-driven insights
Fulfillment partners and 3PLs can leverage big data to analyze patterns and trends of their customers and their industry. Harnessing big data provides actionable insights into key decisions such as:
- Level of stock inventory to carry to fulfill existing and projected demand
- How to best optimize inventory management to enhance efficiency
- How to implement cross-selling strategies to sell slow-moving inventory
These actions drive efficiency, scalability, and advanced tracking capabilities, helping companies to significantly enhance their current and future fulfillment operations.
Schedule a call with one of Logiwa’s fulfillment specialists to discover how Logiwa IO can help you to fulfill brilliantly.
