Time is money, as the saying goes. But when you consider it, time is even more valuable than money. And in no other industry is this more true than logistics, especially in today’s on-demand business world. Whether your company sells meal kits, clothing, or electronics, how you allocate your time (and resources) has the power to make or break your bottom line.
The modern logistics market is more complex and demanding than ever before. Across the supply chain, businesses are grappling with heightened expectations, like minimizing inventory errors, predicting consumer buying behaviors, and providing quick and efficient delivery.
The solution: Predictive analytics. In the past, a predictive analytics strategy was once a nice-to-have game plan for forward-thinking businesses. But today, a predictive analytics strategy is a necessity. And as predictive analytics are introduced to logistics and supply chain management practices, companies are more strongly positioned to meet increasing demands.
According to the MHI Annual Industry Report, this shift towards anticipatory logistics is widely accepted among decision-makers, with 82% of supply chain and manufacturing executives planning to adopt predictive analytics by 2025.
Predictive analytics are driving forward momentum for businesses, helping mitigate costs, decrease risks, and satisfy growing consumer expectations. The innovative technology empowers supply chain professionals to optimize operations across the board, including warehousing, transportation, inventory management, predictive maintenance, demand forecasting, and more.
What Is Predictive Analytics?
Predictive models utilize historical and transactional data, artificial intelligence, and machine learning to identify behavior patterns, trends, and habits. When this data is digested and analyzed, decision-makers are empowered to anticipate future risks and opportunities. These highly reliable predictive solutions deliver actionable, valuable insights across different facets of the supply chain.
Businesses can apply rules and conditions to generate specific scenarios or data sets. For instance, companies can preempt consumer demand utilizing controllable factors, like sales price, and external factors, such as weather effects and work calendars.
So, how exactly are predictive analytics reshaping logistics management? Let’s delve into the transformative power of this technology.
Optimize Key Areas of Warehouse Operations
As predictive analytics gain considerable ground in supply chain management, they significantly impact the quality and performance of warehouse operations. Gone are the days when warehouses serve a single purpose: physical storage. They have evolved into a multidimensional hub, uniting crucial aspects of the supply chain. And, with the right warehousing partner, your business can tap into a deluge of priceless data.
Using machine learning applications, predictive analytics can project future events or trends, gauge their impact, and evaluate if they open the doorway to new opportunities or pose potential risks.
Predictive analytics can help businesses implement agile and strategic initiatives to accommodate market fluctuations. Furthermore, with predictive analytics, data can be computed and rationalized to improve warehouse and fulfillment operations — optimizing inventory, improving customer service, predicting demand, and managing data.
To paint a better picture, let’s look at the following scenario. A meat home delivery service experiences higher demand during months of the year when tailgating and backyard barbecues are in full swing. Proactively planning for these fluctuations using predictive analytics ensures the company maintains accurate inventory levels. Without this data, the business risks overstocking – think: extra, unnecessary expenses and the stench of spoiled meat. Or, they risk understocking inventory, forfeiting revenue, and driving customers to their competitors.
The takeaway? Data provides leaders with critical insights to ensure their business runs as smoothly and efficiently as possible. Let’s explore the essential areas of your warehouse operations that can be optimized with the help of predictive analytics.
1. Demand Forecasting
By combining real-time and historical data, predictive analytics can forecast future demand for your product based on consumer behavior patterns. Accurate forecasting is crucial for stock control and manufacturing surrounding holidays and seasonal demand. It also allows business leaders to prepare weeks (even months!) in advance, decreasing stagnant inventory and ensuring more on-time deliveries.
Leveraging predictive solutions to create supply and demand forecasts allows companies to address needs proactively — rather than reactively — and make informed operational decisions. This approach also provides leaders with the flexibility to rebalance assets across their logistic network to increase profit margins.
2. Inventory Management & Optimization
Keeping track of merchandise can be chaotic and disorganized without the proper systems. Predictive analytics enable companies to better grasp customer buying patterns and maintain adequate inventory levels.
In our current climate, when economic uncertainty, impatient customers, and procurement fragility are creating challenges across supply chains, identifying an optimal balance between supply, demand, and capacity is integral to both your bottom line and company reputation.
Leveraging automation, AI, and machine learning to generate greater visibility across the supply chain can allow your business to stay nimble and adapt to market fluctuations. Because let’s face it: stock-outs will disrupt the operational flow and aggravate customers. And in an era when customer loyalty, online reviews, and referrals can mean the difference between success and failure, businesses can no longer risk taking a gamble on inventory management.
Beyond bridging gaps and fortifying your inventory management strategy, predictive analytics can also help develop future initiatives. For instance, if you’re launching a new product line or considering bundling products for an upcoming sale, having access to purchasing trends can help your business cultivate an informed go-to-market strategy. That means less risk and more reward.
3. Process Automation
Repetitive tasks, manual data processing, and similar labor-intensive activities can be minimized (and, in some cases, eliminated) with predictive analytics. By automating analytics functions, many processes can be streamlined and improved.
As a result, businesses can look forward to decreased operational costs, better resource and space utilization, reduced storage costs, increased efficiency and productivity, enhanced data accuracy, improved order fulfillment accuracy, greater inventory control, and so on.
4. Customization of Data
With predictive analytics, businesses can pull specific data sets based on their needs and correlate different groups of data across locations, departments, or functional teams. The ability to access comprehensive insights allows leaders to make holistic, informed decisions surrounding operations, finances, and inventories. Through this lens, businesses can look ahead and craft long-term strategies to fuel upward mobility.
5. Customer Satisfaction
We know what you’re thinking: How can predictive analytics benefit customer service? By maximizing operational efficiency and keeping inventory stocked correctly, you can minimize delays and inaccuracies, delivering a better customer experience.
Furthermore, predictive analytics can help with workforce management in the customer service arena. Higher demand seasons call for more robust contact center staffing, and vice versa. Predictive analytics help ensure your customer service operations are staffed appropriately, with the right crew in place at the right times.
6. Last-Mile Delivery
Predictive analytics can significantly impact last-mile delivery. Transportation-related greenhouse gas (GHG) emissions, like carbon dioxide, account for an estimated 27% of all U.S. greenhouse gas emissions (the largest contributor in the U.S.). However, predictive analytics in route optimization, anticipatory shipping, and robotics can bolster sustainability efforts and produce tangible improvements, especially in last-mile delivery.
Innovative Technology to Improve Logistics Management
From real-time inventory insights to stock replenishment, market forecasting, and consumer demand, predictive analytics is transforming supply chain management.
The predictive analytics market share is expected to increase to $17 billion by 2026, accelerating at a CAGR of 21.36%. As we move forward, businesses will need to harness predictive analytics to maintain a competitive presence in the market and unlock crucial cost-saving benefits.
As a 3PL that invests heavily in innovation and technology, Smart Warehousing can help your business tap into new opportunities for growth and success. To learn how we can create a customized solution to fit your unique needs, contact our team today.