This post concludes our ongoing series about the supply chain and big data. You can catch all of our posts on in our Big Data category to catch up on all we have written.
In recent years, organizations have turned to technology, global production, and lean manufacturing to improve efficiency and decrease costs; however, these strategies are producing diminishing returns. For example, many businesses have transferred production offshore, yet the appeal of that opportunity is shrinking as the differences in manufacturing costs between various countries such as the U.S. and China have narrowed. Concurrently, global supply chains have increased in complexity, many of which now span multiple continents and involve myriad external suppliers. As a result, corporations are relocating production nearer to home markets (nearshoring) and occasionally “reshoring” manufacturing back home despite high labor costs.
The blending of large, quick-moving and diverse streams of big data with advanced techniques and tools represents the next generation of supply chain innovation. When guided by a clear comprehension of market context, strategic priorities and competitive needs of the business, these methods provide new opportunities to improve customer responsiveness, lower costs, reduce inventory and enhance agility. Flash Global has the global expertise and optimized services and big data capabilities with superior technology for the greatest visibility to give your company the competitive edge in end to end service supply chain management.
Businesses can optimize logistics, distribution and production networks by utilizing robust data processing and analysis resources. Integrating supply chain and big data can lead to the discovery of new demand patterns, improvement of demand forecasts, and the development of new offerings by sharing data across the supply chain with partners. Moreover, it can expand throughput, increase asset uptime, employ preventive maintenance of installed products and production assets, and produce real-time supply planning by utilizing dynamic data feeds. These advancements offer three high-potential opportunities that businesses can exploit to generate improvements in revenue and profits, reduce costs, boost agility and decrease cash requirements.
Last-mile delivery represents one of the most difficult challenges in logistics management. Conventional routing programs will show drivers precisely how and where they should drive to maximize efficiency and reduce fuel costs. The most sophisticated programs can plan out a truck route on a daily basis using historical traffic patterns. However, even the most flexible programs produce considerable slack in scheduling and lack the capacity to dynamically calibrate and visualize routes.
Combine this with the challenge of aligning the shipments of multiple businesses, each with its own delivery system, and the difficulties increase. By using advanced analytical techniques and big data to address intricate supply chain hindrances, businesses can pinpoint opportunities for savings up to 15 percent of transportation expenses. Recent advancements in geoanalytical mapping methods, integrated with vast quantities of location data and inexpensive, quick, cloud-based computational power, give an organization the capability to dynamically analyze the data and produce hundreds of viable shipment route scenarios.
Forecasting demand in the global marketplace represents a time consuming and cumbersome operation. Currently, companies use inflexible systems that generate inaccurate estimates based on information from the sales force to forecast the future. Moreover, forecasting has become increasingly intricate in the face of higher volatility in demand and greater density in product portfolios.
Now, corporations can utilize the vast amount of fast-moving data from suppliers, customers and sensors to combine contextual factors including forecasts, weather, pricing positions, competitive behavior and to identify which factors correlate to demand and then adapt to the present reality. Advanced analysis can integrate data from multiple sources that speak different languages, such as pricing, enterprise resource planning and competitive-intelligence systems, giving managers a visual capability they currently lack.
Businesses have a greater awareness of what will sell tomorrow, how to ship to customers on demand and carry lower inventories to generate their products, thereby reducing costs and increasing operational performance. With advanced demand forecasting, businesses replace inventory with data to meet consumer demands with greater agility. Frequently, a company can reduce inventory by 20 percent through better forecasting while increasing fill rates contemporaneously by 3 to 7 percent. This can produce margins by as much as 2 percent.
Many distribution networks have transformed over the years into dense webs of factories, warehouses and distribution centers that sprawl across many regions. This leads to fixed networks that lack the capacity to adapt to changing flows of supplies to manufacturing facilities and finished products to market. However, current supply chain and big data capabilities can solve the complex optimization problems that older programs cannot. Managers have access to more variables and scenarios that can be integrated with analyses across multiple interconnected systems. Businesses that have incorporated advanced analytics and big data have frequently seen produce savings from between 10 to 20 percent of warehousing and freight costs. A company can also use insights from the diverse data streams to consolidate warehouses and reduce operating costs, thus lowering inventory levels and respond more easily to volatile demand.
Flash Global integrates seamlessly with client systems for the greatest agility and flexibility in today’s global marketplace. We offer proactive account management, expertise in 80 countries, more than 700 forward stocking locations, 15 global distributions centers, and five in-region command centers to provide your business with the capability to increase efficiency and reduce costs.