In an interview with SVP of Industry Strategy for Descartes, Brian Hodgson indicates that data will create major waves in the supply chain industry in 2020.
“With the expansion of networks and associated data, there is a huge growth in harmonizing data and providing it as a service to downstream applications,” he says. “This may include data on truck locations/routes and data to identify warehouses and their congestion.”
Mass adoption of DaaS in the supply chain would promote increased connectivity and the harmonization of information and improve any business’s bottom line. This article examines 3 ways that impact will be felt in the new year.
Data Enables Predictive Planning
In the supply chain business, much of your worries surround planning and ironing out logistics. The use of harmonized data can aid you in foreseeing your future needs based on trends and behaviors.
Typically using Enterprise Resource Planning (ERP) or other automated data tracking systems, managers are used to trying to stay ahead of the curve to ensure they have the inventory and resources available to meet consumer expectations.
By examining data from both internal and external sources, you’ll be better positioned to forecast you need well in advance and make informed decisions. Data retrieved in this way can assist you with anything from risk management to inventory planning, offering the information in real-time.
For instance, IBM utilized data analytics in their work alongside bakeries across the United States, assisting them in predicting inventory needs. Their DaaS system, Watson Analytics, tracked sales over time, the popularity of individual items, and the influence of social media advertising on the sales of baked goods.
Their analytics found that sales reached their height in the summertime, yielding a particularly considerable spike compared to other seasons.
With this seasonality in mind, bakeries concerned about keeping up their inventory to meet demand without overstocking goods that may expire are able to gain insight into their performance over time. This DaaS solution is able to inform them of how much inventory they’ll be expected to use by season.
DaaS can provide information regarding customer behavior over time. That enables you to stock inventory accordingly, making decisions based on accurate predictions of your needs.
Data Makes Invisible Problems Evident
Increased access to interconnected internal and external data points is critical to boosting your ability to trace products and shipments up and downstream.
Sustainability in the supply chain, namely transportation, has become a hot topic in recent years. DaaS allows you to automatically manage and update recalls or necessary product adjustments efficiently, without having to allocate resources to traceability.
The ability to discover issues ahead of time enables you to address problems before they move through the supply chain.
Traceability became demystified for dairy production in a Gujarat village using two IoT sensors that produced data reports regarding the quality of fodder and the vitals of the cows.
The devices were programmed to flag certain data points and results that would indicate problems with the fodder or animals. In the end, the sensors detected upstream issues with the quality of the fodder and the veterinary health of the cows.
Downstream, there were irregularities with inventory and reliable distribution, which makes the availability of products fluctuate more than the ideal.
Using this information, the village was able to act. They began to locate the problems with the fodder, regulating temperatures during transportation, accurately determining when cows were ready to give milk.
Each of these factors was made possible by the real-time data, updated throughout the product’s journey through the supply chain. It brought immediate attention to invisible problems and allowed the village to take smart, efficient action to fix them.
Your business can also improve the traceability of its supply chain by leveraging a network of sensors.
DaaS Systems Encourages Collaborative Networks
Data analytics works best when the interconnectivity of data exists throughout the supply chain.
The more information that infors your reporting and actions, the more accurate your decisions will be. However, most companies don’t have the resources to collect all the data necessary for this endeavor, especially when it comes to gathering data external to their operations.
This problem can be solved through a shift in your competitive mindset. It’s no longer the most beneficial course of action to silo your information. You’ll gain more from data sharing and collaborating with other companies.
This concept significantly deviates from more traditional supply chain processes, which were relatively linear. Goods traveled from suppliers to consumers without changing hands too many times.
With respect to data, it’s going to become less and less sensible to handle supply chain operations this way. Because of the value shift from optimizing your ability to produce goods in isolation to being able to leverage information to maximize your services, collaboration is necessary.
This creates a much less linear flow of goods from suppliers to customers. Instead, what results is a complex network of suppliers, manufacturers, distributors, and consumers sprinkled throughout the supply chain. This way, traditional competitive rules don’t apply.
While data analytics poses a massive benefit to all businesses connected to the supply chain, it’ll take a collective effort to make the impact that experts are anticipating.
Data & Reporting Streamlines Supply Chain Processes
With data analytics and DaaS systems come increased efficiency at all points of the supply chain. Those examining internal and external data are best equipped to locate problems up and downstream. That way, issues can be addressed at an accelerated pace.
Data and reporting also help users determine inventory requirements and other standards needed to best align their service with customer expectations.
Lastly, before data can be leveraged for growth, companies need to refine their outlook on external collaboration. In most cases, businesses will be able to get the most out of analytics by promoting synergy and data sharing with other supply chain companies. That way, everyone has access to more information, promising more accurate results.