“We are surrounded by data but starved for insights.” – Jay Baer

The most important asset for any industry today is data. Looking at the huge amounts of data getting generated, it is imperative to have a thorough process of data analysis that can lead to insightful business decisions. Especially when it comes to a volatile and happening industry like supply chain and logistics, data analytics is an indispensable ingredient in the success of the business. It is also referred to as ‘Supply Chain Analytics’.

The business world of supply chain and logistics is surrounded by multiple stakeholders like suppliers, manufacturers, retailers, distributors etc. Each group generates a large amount of data that can be leveraged for enhancing the efficacy of operations. Even futuristic trends and patterns can be extracted from these data bulks through proper data analytics, that can be helpful in generating further business plans.

This article focusses on the importance of data analytics in the supply chain and logistics industry, key benefits it tags along and the best practices, if followed, can bring about a successful output.

Supply Chain Analytics – An Overview

Supply chain analytics is a process of leveraging data analytics techniques and tools to enhance the supply chain and logistics operations and increase business efficiency. Since it is an exhaustive environment, the bulk of data must be analysed for perceiving trends and patterns, find out anomalies and create a futuristic solution.

Supply chain analytics can offer an effective supply chain management cycle, with lesser operational costs, enhanced planning and risk management, in-depth understanding of upcoming events. It focusses on connection to disparate sources to avail data, collaboration between the stakeholders and the digital systems, preventing any type of cyberattack or data anomalies, automatic assessment of data through AI models and scaling analytical competencies with further data.

Some of the supply chain analytical tools that are prevalent in the market are Tableau, Deloitte Lead Time Analytics, PeopleSoft Supply Chain Analytics etc.

A Good Read – 5 Key Data Management Approaches That Can Modernize the Logistics Industry

Key 7 Advantages Data Analytics Can Bring to Supply Chain & Logistics

Data analytics can serve to be a robust tool for monitoring and enhancing the supply chain and logistics operations, in a big way. Here are some of the evident advantages that are attached to data analytics in this industry segment:

• Managing Risks with Mitigation

Once you analyze data in detail, there is so much information that comes out and help in analyzing the risks. Stakeholders can come to know the reasons behind the risks and how best to mitigate them. There is transparency in the entire process and a sense of awareness that there is continuous monitoring happening in all supply chain processes now. Even the working taskforce can indulge in managing the risks with ease.

• Forecasting Demand with Precision

Demand forecasting is a major area of concern in this segment. With ample of historical data available for analysis, studying market patterns, trends, futuristic indicators become easy and more accurate. This can directly help in smoothening and finetuning the internal processes like inventory management, stock management etc.

• Real-time Visibility into Operations

Once detailed analytics is performed on the data bulks, it offers a real-time view of the entire supply chain operations. This helps in identifying and resolving issues earlier and saves the organizations from facing any hurdle. The real-time vision also helps decision makers in taking the best of decisions for the betterment of the segment.

• Developing Sustainability Ideas

Since organizations can be totally involved in tracking and analyzing the environmental influence of water utilization, carbon emission etc., it turns out easy for them to create and implement sustainability initiatives that can help in lessening expenditure and increasing brand awareness.

• Optimization of Inventory

Analytics of information can be of great help in finding out the exact inventory level that must be maintained for the stock level to be balanced between supply and demand. This helps in ensuring immediate availability of items when required and at the same time, least wastage of the same. It helps big time in reducing inventory costs and wastage of resources.

• Management of Transportation

Supply chain and logistics need to monitor their transportation schedules very diligently. Analytics can help them in optimizing their routes, correcting actions whenever required, changing carriers if needed and thereby maintain efficiency levels.

• Easy Dealing with Suppliers

Since data analytics can offer insight into important parameters such as pricing, delivery deadlines, quality of work etc., stakeholders can select the suppliers wisely based on the information gathered.

Know More About Data Analytics – An Exhaustive Guide on Data Analytics

Best Practices for Implementing Data Analytics in the Industry

However much we ensure, there are certain challenges that could come up as a hurdle – poor data quality, security risks in accessing private information, compliance with regulatory standards, unforeseen consequences, poor decision with data bias, human error, over dependency on data.

Following the below guidelines could prove helpful in overcoming or avoiding these challenges.

• Defining clear goals as to why data analytics is being used in the supply chain process
• Searching for disparate data sources that will be instrumental in the analytical techniques
• Preparing the data for analytics – undergoing data cleaning, transformation, integration from different sources for better precision and transparency
• Choosing the ideal tool for analytics that can understand organizational objectives and help fulfil them
• Build analytics models, predicting models, prescriptive models and descriptive models that can do deeper into data formats and come up with intuitive insights that can help better decision making
• Keep testing the models that are created to ensure that they deliver results as expected and fulfil the criteria that is needed for an expected output
• Whatever insights are observed, must be applied to daily supply chain and logistics operations so that betterment of processes can be witnessed

On a Concluding Note

The extent to which data is spread out in the supply chain and logistics industry is amazing. To tame that data and make optimal use of it, a comprehensive process is needed and that is what data analytics does best. Yes, it does have its own set of challenges but then we have a solution to each problem. It is just a matter of time!                                                                

As a competent data analytics services company, we @ Ridgeant empower every domain via the power of data-driven transformation, where perceptions ignite innovation and data-driven development goes for a transformation. We choose the best technologies and platforms for your data analytics needs, leveraging smarter BI tools to convert raw data into actionable insights.

Our experience and exposure to the supply chain & logistics industry is far and wide, in which our data and AI-driven solutions have showcased positive outcomes in supply chain optimization for our global clientele. Starting from optimizing routes to tracking real-time information, our solutions encompass all functionalities that form the core of supply chain operations.

Associate with us and get your data analytics revolutionized to suit your requirements.