Supply Chain Analytics
What is Supply Chain Analytics?
The economies are constantly changing, stock markets rise and fall, the flow of goods keeps on changing, and there are always new trade regulations in the market. In all these chaotic changes, SC Analytics comes to the help. Supply chain analytics is a process of gathering data of different parts of the supply chain, organizing it, and analyzing it for understanding the future needs of your business. By implementing supply chain analytics strategy, businesses can gather and analyze all the historical and recent data of their business which helps them better predict future demands of their business. When you understand and work for the future demands of your business, there are more chances of your business growth at a faster pace.
How to Analyze a Supply Chain?
Supply chain data analytics is the gathering and analysis of all the data produced by the various arms of the supply chain. It helps you dig deeper into the supply chain data to examine the efficiency gaps and improve the operational, financial, and managerial aspects of the supply chain. It helps businesses to capture and study a huge amount of data. The whole data is collected and visually displayed in the form of charts or graphs. The managers then use this data to plan and make decisions for the future of the business. But it is not this simple. Supply chain managers need to find very relevant data and sort it concisely. They can’t just gather and provide too much information to already overwhelming stakeholders.
Importance of Supply Chain Analytics:
A supply chain is a network of companies that produce, distribute, and sell products. Supply chain management aims to bring together the various players involved in a supply chain in order to deliver these products to customers as efficiently and effectively as possible. This means that supply chain managers must monitor their supply chains closely in order to identify any potential problems or inefficiencies. A supply chain analytics strategy is the way that your organization collects and analyzes data in order to make better decisions about the supply chain and improve the overall performance of your business. SC Analytics can be used to identify and solve problems across the entire supply chain, from procurement to transportation, inventory management, and customer service.
Supply Chain Predictive Analytics:
Predictive analytics is a type of supply chain analytics that involves the prediction of future business trends such as market demand, sales, exchange rates, and other important metrics of your business. For this type of analysis, the application of statistic modeling and analysis of historical data is used.
Using these two strategies, the future trends are understood and formulated for the better growth of your business. Mathematical models are formulated and tested until they are capable of reliably forecasting the future. Predictive analysis isn’t the 100 percent true prediction of the future but it only tells you the probability that what’s likely to happen with your business based on the trends revealed by analyzing historical data.
Building a Supply Chain Analytics Strategy:
The first step in building a supply chain analytics strategy is to identify your objectives. What is the purpose of collecting supply chain data and analyzing it? What are you hoping to achieve? This will help you to focus your efforts and identify the data that is most relevant. In addition, organizations should consider the following when building the strategy:
DATA SOURCES:
Where are your data sources coming from? How can you ensure that the data is accurate and reliable?
DATA TYPES:
What types of data are important to your supply chain?
DATA AVAILABILITY:
Is the data available in a timely manner? Can it be accessed by all members of the supply chain team?
DATA OWNERSHIP:
Who is responsible for collecting and analyzing data? Who owns this data?
DATA SECURITY AND PRIVACY:
How is the data being secured? Are there any impactful compliance requirements?
DATA ANALYSIS CAPABILITIES:
What tools are you using to analyze supply chain data? What types of reports and visualizations are you creating?
3 Tips to Improve Your Supply Chain Analytics Strategy:
The following are 3 tips to improve your SC Analytics strategy:
NO.1 – START SMALL:
It is important to prioritize projects that will have the greatest impact on the organization. Building a big data analytics project can be costly, time-consuming, and complex. Start small with a few projects that have a clear objective and that can be completed relatively quickly. This will help you to gain experience and show value quickly.
NO.2 – FOCUS ON DATA THAT MATTERS:
In order to be effective, supply chain analytics must be actionable. This means that the data must be accurate and must have a legitimate impact on the supply chain. While all data has value, only data that is truly relevant should be collected and analyzed.
NO.3 – BUILD A CULTURE OF COLLABORATION:
Supply chain analytics can provide value to organizations of all sizes and in a variety of supply chain environments. However, the best results are achieved when organizations create a collaborative culture where data is accessible to all members of the supply chain team.
Transforming The Supply Chain With Data Analytics and Intelligence
The process of collecting data, analyzing it, and using it to make decisions that improve performance is known as supply chain analytics. The increased variety and volume of data available today provides an opportunity for businesses to identify inefficiencies in their supply chains and take action to address them. In order to turn data into analytics and intelligence, organizations must build a data-driven culture that embraces collaboration, uses the right tool like SCOR Model, and is compliant with privacy regulations. With the right approach and the right technologies, businesses can use data analytics and intelligence to transform their supply chains.
Supply Chain Analytics Examples:
Several examples are demonstrating the use of SC Analytics to achieve organizational goals. For your better understanding, here is a brief explanation of three such examples:
No-1: Capacity Planning:
Capacity planning is made to match the manufacturing capacity to sales demand. Different analytical tools are used to make a mathematical model for your business. Then the whole data is analyzed to predict the future capacity of the sales.
No-2: Stimulation and Scenario Analysis:
Stimulation and Scenario analysis is an example of supply chain analytics which is used for strategic planning for determining the potential business scenarios. It will help to shape the company’s future and help your company standstill during numerous crises.
No-3: Sales & Operations Planning:
Sales and operation planning is used to look at the financial bottom line to determine the most profitable production. It is used to determine the sales scenario and maximize future productions.
Supply Chain Analytics Success Stories:
DHL:
DHL is a multinational logistics company that offers supply chain management services and software. In 2018, DHL hired doctorate in logistics and supply chain management qualified professionals and partnered with blockchain company Riddle & Code to improve its supply chain and customer experience through blockchain technology. With this partnership, DHL will be able to track individual shipments in real time.
Swedish Railway:
In 2018, the Swedish Railway partnered with SAP to improve its ability to manage its global supply chain. The partnership has allowed the railway to optimize its procurement, logistics, and asset management.
E.ON:
E.ON is a global electricity and gas company. In 2018, the company partnered with SAP to better manage its global supply chain. Using data collected through its IoT platform, E.ON is able to improve energy management and customer service.
Data Analytics in Transforming Supply Chains:
SC analytics is a powerful tool that can be used to identify inefficiencies in the supply chain and take action to address them. Building a analytics strategy requires organizations to consider the types of data they collect, the tools they use to analyze the data, and how they use the insights gained from the data to improve their supply chain. There are several ways to use supply chain analytics to improve supply chain operations and customer satisfaction. The best approach will depend on the organization’s objectives, data sources, and the volume and types of data.
FINAL THOUGHTS:
Supply chain analytics is the process of collecting data, analyzing it, and using it to make decisions that improve performance. The increased variety and volume of data available today provides an opportunity for businesses to identify inefficiencies in their supply chains and take action to address them. Supply Chain data analytics is very important part of your business supply chain. It can effectively help you achieve your data organizational and future business goals.
Original Article – https://aims.education/supply-chain-analytics-2/
