Optimizing Connected Logistics Operations with Data Analytics

connected logistics with data analytics

Logistics has been one of those industries where digitalization has been long overdue, although the linchpin holds several 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 solutions, 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. There lies the importance of data analytics.

Data analytics is not new to us anymore. It has been transforming diverse industries, including logistics worldwide, for quite some time. Logistics is a classic case in point when evaluating the impact of data analytics. It is complex and relies on an intricate but extensive network of industry players for its myriad functions.

The one thing that all of them need to work smoothly is transparency. Data analytics ensures complete transparency in this traditionally fragmented industry that is now dramatically navigating its course amidst the effects of the pandemic.

Experts unanimously agree data analytics is 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 analytics to be a core competency for their organizations. In comparison, 71% of 3PLs think process quality and performance can be significantly improved with the help of big data.

Interestingly, a whopping 91% of respondents in McKinsey’s Global Manufacturing & Supply Chain Pulse Survey1 believe forecasting in the years ahead needs to be different given the disruption the pandemic has caused.

Delivering value in connected logistics

AI and machine learning are already playing a significant role in shaping new initiatives for the logistics industry. With data analytics 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 analytics paves the path for productivity and performance, providing organizations with the much-needed anchor to support their objectives. To understand how we must first look into the many areas of data analytics. It is broadly divided into:

Descriptive Analytics is the most basic form of analytics 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 overperforming 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 machine learning 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 analytics.

It adopts a more refined approach to look for correlations in data that are usually beyond the scope of descriptive analysis. It helps organizations anticipate probable scenarios, plan for the future, and deal with contingencies.

Prescriptive analytics – This form of data 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 analytics, 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 analytics offers 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.

Optimized for more

Since data analytics gives you the edge to think and plan for the future, logistics companies have been leveraging it well to optimize their operations. Its role has been highly transformative in the field of logistics. It empowers you with powerful capabilities that include the following:

Elevate performance

Organizations use data insights to attain actionable results with appropriate resource consumption. Be it routes or resources, data analytics gives you the edge to plan and maintain docking schedules, monitor machine performance, and track the work activities of the workforce. The data is often shared among relevant stakeholders to improve the efficiency of the entire supply chain or network.

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 efficiencies

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. Traffic congestion is a major hurdle, and delivery points, particularly in rural areas, can be far apart.

Considering that last-mile delivery accounts for 30-35%2 of the total delivery cost, it is imperative that logistics companies work towards increasing their efficiency and cost-effectiveness. Data proves to be invaluable here in optimizing delivery strategies. 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 analytics 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 analytics in all its 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 analytics and insights to help you beat the competition and grow revenue. Our technology experts will empower you with advanced logistics solutions to streamline core business operations, reduce costs, improve supply chain visibility, and optimize routes.

We can partner with you to optimize logistics operations and deliver a flawless customer experience. Call us today to book a business consultation.

References
1. https://www.mckinsey.com/industries/travel-logistics-and-infrastructure/our-insights/a-fresh-approach-to-logistics-forecasting-in-2021
2. https://www2.deloitte.com/global/en/pages/consumer-business/articles/last-mile-delivery-landscape-transportation-sector.html

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