How Predictive Analytics Is Benefitting Supply Chain and Logistics Industry

Predictive analytics is being applied toward all facets of business operations and processes to help anticipate events, avoid risks, and create solutions. By forecasting future supply chain and logistical events, companies can gain a competitive advantage and prevent monetary loss due to inaccurate stocking, and mismanagement of goods, deliveries, and time.

According to Forbes, efficiency in the supply chain is crucial. “Inventory management, picking, packing, and shipping are all time and resource-intensive processes which can have a dramatic impact on a business’s bottom line.”

Utilizing predictive analytics to optimize supply chain and logistics is already benefiting major companies like Apple, Amazon, and Whole Foods. Other businesses are taking a page from their example and using predictive analytics across both small and large-scale operations to improve their forecasting abilities and responsiveness via real-time analytics.

Anticipating Events with Predictive Analytics

Predictive analysis is used to make forecasts by reading algorithms based on both current and historical data. Organizations can modify how and where they use resources to better prepare for future events. It creates a framework for connecting the dots between trends, patterns, and associations in data to help businesses respond proactively to future developments.

Predictive analytics uses a mixture of analytics methodologies, combined with automated tools and technologies, to find patterns within data, and goes one step further to anticipate the likelihood of specific future events.

Predictive analytics encompasses the following:

• Predictive Modeling
• Text Analytics
• Real-Time Scoring
• Ad-Hoc Statistical Analysis
• Data Mining

Through intelligent application of these predictive analytics models, companies can prevent unnecessary expenses and errors related to their supply chain and logistics processes.

How Predictive Analytics Helps Supply Chain and Logistics

Predictive analytics is improving supply chain and logistics industry by being able to accurately collect and analyze data that helps in management decisions. It can also help address issues like damaged inventory, stock errors, and supply and demand miscalculations. Predictive capabilities allow organizations to accurately address customer service and traffic patterns, labor unrest, and weather events that affect shipping and port behavior.

Organizations can use predictive insights for supply chain and logistics in the following ways:

• Transportation Management Systems: Supply chains depend on fixed lead time and uncertainty for factors such as ocean shipping, can be addressed by predicting future disruptions.
• Third Party Logistics: Predictive analytics can create more value by developing partnerships with technology providers to apply Big Data to their services.
• Industrial Procurement: Retailers and distributors can prepare months in advance to help their suppliers plan to inventory and shipments based on customer demand and buying behavior.
• Customer Visibility: Organizations can obtain market insights about customers, suppliers, and trading partners, as well as seasonal buying patterns and consumer forecasts to make quicker more intelligent decisions.
• Product and Content Placement: Organizations can better prepare for short-term behavioral changes that affect supply chain and logistics such as news, weather, shortages, and manufacturing promotions. By utilizing predictive analytic models to detect unexpected conditions, they can better adjust site merchandising in response to specific time-sensitive
• Improved Personalization for B2B: Predictive analytic models can be used to ensure that the correct seasonal products are delivered to customers based on geographical region. A model can detect changes that may necessitate a modification in merchandising per geographic location.
• Predict supply and demand: Predictive analytics ensures that there are less waste and on-time deliveries during pinnacle demand times.
• Predictive Maintenance: This is extensively used in supply chain logistics in a technology-focused way, particularly in operations that focus on picking and packing, and across fleets of transport ships and trucks. 

How Major Companies Utilize Predictive Analytics

Large companies are taking advantage of predictive analytics to improve their supply chain and logistics down to the smallest detail. They are setting the bar for the way that companies are using predictive analytics, and creating improvements that drive business growth.

• Apple and the Supply Chain Model: They’re using forecasting capabilities to establish real-time visibility into demand patterns, and anticipate online orders for products like Apple Watch, iPhone, and prevent delayed shipments.
• Amazon and Whole Foods: Amazon acquired Whole Foods to gain access to physical stores and their shoppers and the corresponding data. They’re using predictive analytics to optimize supply chain analytics in anticipatory shipping and stocking using real-time data. They’re making a more effortless experience for shoppers and suppliers while helping to reduce food waste in the United States.
• As is evident in companies like Apple and Amazon, predictive analytics can provide more certainty regarding shipment ETA’s, reduction of network latency, protection of profit margins, and shortened cycle times. 

Accurate Forecasting Capabilities

Predictive analytics is giving organizations the capability to improve key performance drivers in supply chain and logistics. Everything from delivery management, costs of goods, order lifecycle, movement of goods, shipping and warehousing costs, inventory management, and customer service can be forecasted through predictive analytic models.

Research Optimus (ROP) is a leading global research and analytics firm providing predictive analytics solutions to help organizations strengthen their Supply Chain and Logistics management processes, and become more resilient. ROP’s customized forecasting capabilities enable companies to accurately predict behaviors, trends, and events that impact their profit and core performance.

– Research Optimus