The emergence of Internet of Things (IoT)-enabled devices and solutions, such as artificial intelligence, virtual reality and augmented reality, is transforming the very nature of manufacturing and the overall supply chain. By integrating IoT-connected sensors at every step of the supply pipeline, an organization can cultivate brand new data points and gain comprehensive visibility across the entire supply chain. This modernization of the supply chain is the next frontier for organizations, enabling companies to reduce inefficiencies, cut costs and ultimately promote better customer experiences using the power of data. So, how can supply chain organizations keep up?
For manufacturers, logistics providers and all other companies involved in the supply chain looking to drive modernization within their organizations, success will stem from the ability to understand, adapt and leverage data methodologies underlying emerging technologies like IoT devices. Although the future of a completely connected ecosystem is still far away, organizations must ensure that their data strategies in the present day can support these new and emerging technology trends, which will in turn create better experiences for the end user. In the face of growing customer expectations and digital transformation efforts within the industry, today’s modern supply chain organization must anticipate and prepare for the next wave of technology innovation in order to stay above the competition.
The Importance of an End-to-End Data Strategy
In an ideal world, supply chain organizations have end-to-end visibility of all operations along the pipeline, enabling a streamlined flow of data and goods from the factory to shipping warehouses to customers’ doorsteps. In reality, supply chain data visibility remains in the dark, with data gaps in production and logistics causing unanticipated freight delays, mismatches in inventory and sometimes, disgruntled customers.
Supply chain modernization seeks to solve these gaps in visibility by promoting a more agile and adaptable approach to data management, enabling organizations to seamlessly communicate information from one end of the supply chain to the other. This “end-to-end” data strategy also promotes a singular view of the customer, providing a baseline that helps organizations craft ultimate customer experiences. This is supported by a recent survey revealing that 48 percent of leaders from the manufacturing sector within the supply chain verticals cited heterogeneous data integration and master data management as the greatest challenge to achieving a single customer view.
Online retail giant Amazon is one example of a modern end-to-end supply chain in action. The degree of optimization adopted by Amazon exemplifies the rapid pace of supply chain needs — many popular products can move from warehouse to doorstep in the course of one business day. Amazon’s supply chain first and foremost emphasizes customer-centric ideals, enabling incredibly quick turnarounds on delivery. Their strategy also demonstrates the power of an end-to-end data strategy, as customers can simply interact with a mobile app, press a few buttons and receive a package in the course of a day, sometimes within a matter of hours.
What exactly supports the widespread success of Amazon? We believe the answer is in the power of data, and how Amazon supports the transformation of data points into actionable insights and agile supply chain processing. Their usage of data integration, beginning with orders within their mobile app and website, in combination with their willingness to demo and implement cutting edge technologies (delivery drones, anyone?) places Amazon at the forefront of e-commerce and supply chain organizations. To keep up with the pace of this retail giant, companies should adopt modern data strategies to ensure that they can also leverage the supply chain technologies of the future.
Supporting Future Technologies Using Present Data
With many manufacturing, logistics and other supply chain organizations relying on IT hardware and software to facilitate operations, enabling integration across these data points is crucial to promoting end-to-end visibility into the pipeline. To support this visibility and modernize the supply chain, enterprises must implement an agile, adaptable and secure data strategy that can handle high volumes of data in a way that promotes the extraction of relevant real-time insights. Here are a few steps that organizations can take immediate action on and use to revamp their IT data strategies:
* Implement application programming interfaces (APIs) to promote real-time data integration
* Leverage data analytics to transform data into actionable insights
* Promote an ecosystem of data sharing among partners, third parties and other organizations to gain an outside-in view of customers and operations
Ultimately, a comprehensive data strategy will provide organizations with the tools needed to promote business efficiencies as well as emphasize customer experiences.
Some supply chain organizations are already taking the steps to modernize their operations and gain a competitive edge over other enterprises. For example, global trucking company Navistar recently implemented a mobile app to collect relevant information from drivers on the road, such as the services they require and where to find these services. The app also integrates a social function that drivers can use to rate various truck stops for cleanliness, services provided, fuel costs and repair quality. The company’s use of mobile app technology improves the employee experience while simultaneously promoting greater efficiency in shipping operations.
Although modernization is by no means a requirement in the industry, supply chain organizations should consider the various benefits and efficiencies created by keeping data and data visibility top of mind. Only by continuing the path toward innovation will companies be able to rise above the competition and continue providing end users with ultimate customer experiences.