What types of intelligence reports are supply chain managers looking for?

Supply chain intelligence has given the power to supply chain managers to manage and analyze all the data they get from within the chain. The question is: How is this an asset to the company? In this article, you will see how intelligent data analytics gather data from various points and have massively improved the way managers make decisions for the company. Let us dive right in.

What is Supply Chain Intelligence?

Supply chain intelligence refers to the technology and software that shifts the manual work within the supply chain to a more automated, data-driven process. This might range from fleet intelligence to technical data intelligence and many other factors as well. Supply chain intelligence is an umbrella term that covers all the factors that make up an intelligent supply chain.

A proper intelligent supply chain is where the management is data-driven, encompasses analytics, insights to work on the processes and their decisions. Machine learning optimizes the way a company deals with data and artificial intelligence-driven supply chain management ensures the most efficient and effective ways of using that data to benefit the company. Supply chain intelligence is undoubtedly an irreplaceable asset in the current world and is one of the key factors that help a company get ahead of its competition.

The factors of Supply Chain Intelligence

Amongst all the measures that can be taken to automate and enhance the supply chain, some factors soar over the others as benefits take place in specific situations where the system can thrive. Some of these are mentioned below:
Implementation of Internet-of-Things (IoT)IoT systems and devices are essential when it comes to factoring in intelligent asset management within the business. The system works in a way that goods are equipped with devices that can monitor their movement at any point of the supply chain. What this means is that IoT devices are able to provide the data that is required for AI, Machine learning, and other functions to do their jobs. This way, data inflow is seamless and can be gathered at the least amount of time in order to generate reports and make predictive and efficient decisions for the company. This can work parallel to many important features such as fleet intelligence, instant alerts automation, etc as these are the segments of the business that collect data from within the field and the data is then used to make technical decisions within the company. Therefore this is particularly where this implementation of supply chain intelligence will shine.

Usage of Algorithms and Big Data

With data flowing in from the IoT devices equipped in multiple regions, they can be immediately put into algorithms that can utilize them to their full potential. Big data can massively improve the predictive analysis taken from the integrated AI and Machine learning systems, because more data means more information to work on and more possibilities to consider. Algorithms can be fixed and also flexible due to adaptive machine learning that changes the algorithm according to the situation. And in order to utilize this, the system needs copious amounts of data, that big data is set to deliver.

AI and Machine Learning

Artificial Intelligence (AI) and Machine learning are two terms that are visible in almost every tech that is needed to shift to an intelligent supply management system. These two are automated software features that take the data from IoT, run them through algorithms, and are able to make decisions based on them by themselves. These decisions are generally more time-efficient and are a great alternative to manual, repetitive tasks that usually do not require comprehensive decision-making. The entire process is software-based and strictly calculative alongside being modeled to the company’s preferences. For example, AI is able to take information from the routes that vehicles take in a delivery management system, and is able to produce reports of how much time has been saved or could have been saved, fuel-efficient routes, stoppage points, etc. Machine learning can then analyze this data and reports that can be used to make better decisions in the future. These two technological advances are able to provide a massive boost in a company’s data analytics and ease up multiple tasks for the managers.

All of these factors provide the managers with invaluable insight into what the company needs and where it is headed. This insight is in the form of analytics and reports using the data derived from all the automated aspects of an intelligent supply chain. What this also brings to the company is automation. Intelligence management is almost synonymous with automation and is the key factor to increasing speed and workflow within the company.

Meeting the demands of Supply Chain Managers

Supply chain managers these days make decisions based on data and analytics that they get from points within the supply chain. Data analytics contain reports that are made using the activities that take place during all the internal processes, and it is a tremendous asset to the management. These reports help them get an instant overview of the business, as well as get a deep insight into what is taking place at what point. Such versatility cannot be offered without the tech that is being integrated in order to switch to intelligent management.

Data-driven intelligence brings out volumes of info that the company might not be seeing in general circumstances. For example, when it comes to fleet management, data intelligence would refer to utilizing the geological and technical data that is received from the field and running that data through AI that comes up with the most efficient solution to any issues that have occurred or might occur. Here, the driving force is the data that the software receives. This data helps track and keep location logs for the entire fleet. Not only that, but it also enables automatic alerts for pre-set events that might occur en route. Without the data-driven fleet intelligence at work, decision-making would not be nearly as efficient.

Reports generated from warehouse intelligence increases fulfillment efficiency. It helps you handle stock quicker and minimizes the decision-making time that is usually taken between order and delivery. It also enhances the fulfillment process, as the data gathered from our mobile app allows quick and informative driver updates from any point in between the route. This is another feature that goes both ways, for the management and the customers. Getting relevant updates from the driver such as pickup time, route delays, estimated delivery time massively improves customer satisfaction.

Moreover, getting updates on the location and status of your sales representatives is a generally tough task. But with a simple mobile device, the presence of sales representatives can be updated and logged at all times, with their current status as well. This increases efficiency, as monitoring the representatives becomes a lot easier.

The same things go for almost all the other sectors at play within the chain. This shows us just how much efficient decision-making today depends on data-driven analytics and how much there is to work on. Any business that wants to take a step up in decision making, needs to set up data analytics and carefully analyze them before taking any measures. In this age, this is considered to be the peak of smart management as all decisions are taken using information that has been taken from within the system itself, and made sure to be efficient.

If you are looking to integrate data analytics in your supply chain, look nowhere else. Nuport offers the integration of data-driven intelligence in various aspects of your company that will bring just the shift that you might be looking for. Intelligent fleet tracking software, route optimization, smart delivery orchestration system, etc., make sure all the data is immediately run through analytics and reaches your report files in no time. Schedule a demo today!