Logistics has been one of those industries that was long overdue for digitalization, although this is one where the anchor holds multiple value chains together. Thankfully, it’s now a game for new technologies and leveraging structured and unstructured data like no other.
The future of the global supply chain market lies in IoT, integrated services, data, and mobility. Connected logistics devices generate a massive amount of data. The ultimate goal of any organization dealing with a pool of connected devices and sensors is to leverage this data by learning the trends and patterns. And therein data engineering services comes into the picture - to streamline the intricate and myriad interconnected network of industry players in the logistics value chain.
The one thing that all of them need to work smoothly is transparency. Data engineering services ensure complete transparency in this traditionally fragmented industry that is now dramatically navigating its course amidst the effects of the pandemic.
Experts unanimously agree data engineering services are here to stay, considering 98% of 3PLs and 93% of shippers believe in having data-driven decision-making capabilities to manage supply chain activities. 86% of 3PLs and 81% of shippers want services to be a core competency for their organizations. In comparison, 71% of 3PLs think that big data can significantly enhance performance and process quality.
Interestingly, a whopping 91% of respondents in McKinsey’s Global Manufacturing & Supply Chain Pulse Survey believe forecasting in the years ahead needs to be different given the disruption the pandemic has caused.
Delivering Value in Connected Logistics
Artificial Intelligence (AI) and Machine Learning (ML) are now actively shaping a number of new initiatives for the logistics industry. With data engineering services at the helm, organizations are now bringing their predictive and prescriptive learnings to the fore while harvesting descriptive data to get a competitive edge. So let’s dive deeper to understand the changing dynamics from an analytics perspective and see how it’s optimizing operations globally.
The Route to the Future
Data engineering services pave the path for productivity and performance, providing organizations the much-needed anchor to support their objectives. To understand how, we must first look into the many areas of data engineering services. It is broadly divided into:
Descriptive Analytics – is the most basic form of engineering that offers information about the events that occurred in your organization in the form of sales reports, annual reports, insights into marketing campaigns, etc. It summarizes the past events to tell you what has happened so far.
It looks for trends at all levels – micro, macro, and aggregated – to identify underperforming or over performing areas and offer organizations a context for future actions. It helps you keep track of your operations regularly through dashboards and databases. Areas covered may include shipments, geographical locations, transport channels, and campaigns.
Predictive Analytics – This data helps forecast trends as it predicts what could happen in your organization. Based on ML algorithms and AI processes, it enables you to prepare for the future with initiatives that can have a meaningful impact.
It uses data from descriptive analytics and advanced statistical processing to spot trends and assess performance based on key metrics such as fill rates and operating costs. Questions like which would be the fastest route or whether you need to adjust your pricing as per market trends can be answered well using predictive engineering.
Moreover, it provides better clarity when searching for correlation in data - something that descriptive analytics is unable to do. Additionally, it enables organizations to predict probable scenarios so that they can be better prepared to deal with any emergency.
Prescriptive Analytics – This form of engineering takes predictive analytics a step further by informing you about what could happen in your organization and the ways and means by which you could ensure that whatever happens, happens for the better. It offers recommendations to help you optimize your processes and marketing campaigns for excellent outcomes.
While there is plenty of overlap in the above-mentioned forms of data engineering services, the fact remains that each one plays a significant role in organizational success. Not all data needs to be complex. Sometimes, our queries can be simple, but having relevant data to seek answers to those questions makes all the difference. Data engineering services offer insights and alternate path analysis to enable you to come up with new ways to operate to optimize an outcome.
More than different types, they seem more like a natural progression. While descriptive analytics offers basic information, predictive and prescriptive analytics help you realize your goals and improve business outcomes. All three types build on one another, yielding insights that can help organizations re-engineer their supply-demand network. They help optimize operations to enhance workflows and improve capabilities.
Benefits of Data Engineering Services
Since data engineering services give you the edge to think and plan for the future, logistics companies have been leveraging them well to optimize their operations. Their impact has been significant in the realm of logistics. They offer the following benefits:
Boost Performance: Organizational data insights provide ways to pursue actionable results with the right-level resource consumption. Be it route planning or allocation of resources, the data engineering services enable you to edge in the way of planning and maintaining schedules, monitoring the performance of machinery, following the work activities of the labor force, etc. Data is often shared among the stakeholders to improve overall supply chain or networks' efficiency.
Enhance Transparency: On-time deliveries don’t just happen. They must be planned and scheduled through follow-ups and constant communication for status updates. Internet of Things (IoT) and embedded sensors enable shippers to inform concerned parties, including customers, immediately about a delay. This instills faith and facilitates a better customer rapport.
Consumers value transparency in supply chain operations. Transparency is a prerequisite, with 77% of consumers now wanting to buy from companies that share their values. The rationale is to minimize waiting time and eliminate uncertainty from the supply chain.
Improve Last-mile Efficiency: Last-mile delivery has been a major pain point for the logistics sector. The anxiety begins when the product enters the ‘out for delivery’ phase. It is given that traffic congestion can be a major headache, and when it comes to rural areas, delivery points can be far apart, further adding to the hurdle.
Moreover, last-mile delivery makes up for 30-35% of the overall cost of delivery, so it is crucial for logistics companies to ensure that they are cost-effective and efficient. This is where data engineering services play an important role - in optimizing strategies for delivery and planning for contingencies. For instance, GPS tracking data from previous deliveries will help you determine areas that experience higher order volumes and plan accordingly to overcome last-mile obstacles.
You can make adjustments in real-time to offer customers personalized services, such as providing the right seasonal products according to geographical locations.
Optimize Routes: Real-time GPS data also ensures you are cued into weather conditions, vehicle conditions, fleet and personnel schedules, and the fastest route for delivery. This allows you to boost the speed of delivery while offering real-time visibility to customers about their orders.
Final Thoughts
It is evident industries worldwide are now relying on high-quality data to level their playing fields. The power of data engineering services cannot be undermined when it comes to building forecasting models to meet the diverse requirements of your business.
Data-driven insights can help your forecasts evolve into tangible plans with discussions and decisions. No matter how many tools emerge on the logistics landscape, data engineering services in all their forms – descriptive, predictive, and prescriptive – will continue to drive strategic planning.
Optimize Logistics Operations with Trigent
Build operational efficiencies and drive revenue with Trigent. We offer data engineering services and insights to help you beat the competition and grow revenue. Our technology experts will empower you with advanced logistics services to streamline core business operations, reduce costs, improve supply chain visibility, and optimize routes.
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