Supply chain analytics (SCA) is booming! It is time to enter this career vertical or business by learning what supply chain analytics is in this article and a few reliable learning resources.
Data analytics is making data-driven decisions by utilizing data generated from business processes and visualizing them in mathematical charts and graphs. When you do this to manage the supply chain from producer to retail shops and everything in between, you are actually utilizing supply chain data analytics.
According to Markets and Markets, the global revenue earned from supply chain management (SCM) was $28.9 billion in 2022 and should grow to $45.2 billion by 2027. This massive growth in SCM will require various critical components of this profession or business. Supply chain analytics is one of the critical components of SCM.
Hence, if you want to become a supply chain professional, and learn more about supply chain analytics to effectively manage supply chains, read on.
Types of Supply Chain Analytics
There are various types of supply chain analytics in use. The variant depends from business to business. Several organizations create their own kind that is more relevant to their supply chain management than the existing types. However, the following are the popular types you must know about:
Descriptive Supply Chain Data Analytics
Descriptive SCA is everything about collecting data about the supply chain from several touches points, as mentioned below:
Sales and operations from external and internal sources
Supply chain data about the related product and service from the market for other organizations
Responsiveness and efficiency of competitors
After collecting the data, you must create an online database that can be accessed by the SCMs and SCAs of your business. It works like a single source of truth for everything related to supply chain data. Database updation is also the scope of this SCA process.
Predictive Supply Chain Data Analytics
Predictive SCA is all about forecasting the supply and demand side of supply chain management. By analyzing the data collected in the previous SCA type, here you create insights for the entire supply chain-linked workforce, either internal or external.
For example, by analyzing the historical and present trends for smartphone adoption, you create a predictive trend for adopting the same product five years later. Accordingly, you plan procurement of chips, motherboards, fabrication components, and packaging materials.
The forecast helps the business to stock an ample amount of certain products to attain enough profit targeted for the financial year. Provided that there will be a sudden rise in smartphone sales, your business will be able to cater to the customers while your competitors are busy producing devices.
Prescriptive Supply Chain Data Analytics
Prescriptive SCA is more about collaborating with external and internal supply chain stakeholders to mitigate supply chain disruptions. For example, vaccines for a fast-spreading disease may not be available on the onset of the symptoms around the globe.
Also, there are only a few countries in this world that can invest heavily in faster vaccine research, clinical trials, and taking the final vaccine to the production level.
But, during the COVID-19 pandemic, the vaccine inventors, manufacturers, and distributors worked in collaboration to distribute the end product quickly to various parts of the world to slow down the progression of the virus in a healthy population.
Cognitive Supply Chain Data Analytics
Cognitive SCA empowers a business or company to answer complex supply chain and logistics problems in simple language that the top-level business stakeholders and investors can understand. The development and availability of artificial intelligence (AI) and machine learning (ML) made it easier to develop software that can analyze data generated in Descriptive SCA to answer complex questions.
How Supply Chain Analytics Works
Supply chain data analytics work by converging various data from different supply chain touch points in one database. It does not only work as a data aggregation protocol. It will also define the mathematical and statistical tools, equations, charts, and graphs you need to analyze data for functional insights.
To achieve this, businesses use various supply chain data collection tools and apps. Vendors, transporters, warehouse employees, and sales representatives constantly interact with these apps to feed data.
The fast growth of the internet of things (IoT), especially in retail, also helps you collect data from the endpoints of the supply chain. As a result, you can generate all the possible data you need to create insights for the supply chain managers, procurement managers, finance officers, and so on.
Businesses do not just implement any supply chain data analytics. They first run a trial SCA process for a small product lineup. Data scientists who can analyze data and also know various nuances of the trade step in to create patterns and forecasts from the collected data. The data include cash flow statements, inventory statuses, inventory in transit, inventory in retail shops, waste, customer service feedback on ordering, complaints about shipping delays, and many other components.
Business managers apply the findings to the product lineup and test if it is decreasing the overhead cost and increasing the profit margin. After several trials, the data scientists hand off the project findings to data engineers, who will apply the data analytics formula for all other products and services of the business.
Benefits of Supply Chain Analytics
Find below the benefits of SCA for any business:
Primarily, you can reduce the cost and wastage involved in product sales. When you are able to achieve this, you automatically increase the profit margin.
SCA empowers you to predict the upcoming trend of products in the market. Accordingly, you push the product down the line of supply chain and marketing to the shelves of the retail stores. When there is a genuine demand, you sell aggressively and earn profits while your competitors wait to stock their shelves.
SCA is highly functional in predicting and eliminating risks from the entire supply chain pipeline.
You can also use SCA to appropriately manage basic supply chain tasks like fulfilling customer needs timely, responding to vendor requests, and monitoring the warehouse status.
Challenges in Supply Chain Analytics
These are the challenges that you might experience in this discipline:
Generating the data you need for functional supply chain analysis is a big challenge. You rely on external and internal employees for accurate data entry when they perform a task. If the data is forged, the data-driven insight will not work.
Setting up an SCA process involves one-time costs that many small and medium businesses try to avoid to minimize capital expenditure.
The shortage of experienced SCA professionals is also a challenge.
Use Cases of Supply Chain Analytics
Find below how you can utilize SCA in your business:
You can gather valuable insights from supply chain data to appropriately manage your sales and operations process.
It also becomes easy to discover when to raise the price, reduce the price, offer discounts, etc., during a product lifecycle by analyzing SCA data.
You can create data analytics dashboards for your C-level stakeholders.
Accounting supplier and vendor performance dynamically is a big challenge. But when you collect and analyze vendor inputs and create patterns, it becomes easy to understand how your suppliers are performing.
SCA helps you to sign better vendor and distributor contracts by analyzing the market.
Learning Resources on SCA
Find below some books that you should read to learn more about the discipline:
Supply Chain Analytics: Concepts, Techniques, and Applications
Supply Chain Analytics is an innovative new textbook with core concepts from this sector. The book is written by an experienced practitioner and professor in SCM. It brings a business-focused overview of the applications of supply chain data analytics. The book also discusses how machine learning (ML) can be applied in the supply chain.
The content is easily understandable yet rigorous. SCM and supply chain data analyst students can learn the relevant techniques and concepts needed for data analytics. Consequently, the trainee SCM professionals learn decision-making for modern supply chains.
The book also discusses a powerful and popular programming app that helps SCMs in generating related data visualizations and patterns from raw supply chain data. This paperback is suitable for use as a textbook on upper-level graduate, undergraduate, MBA, and other postgraduate courses on SCM. Because the book covers all of the major workflows, processes, supply, and demand management, inventory control, warehouse management, shipping route optimization, transportation, and so on.
All the chapters come with real-world examples created from a range of business verticals. These examples are used as practical lab courses.
Supply Chain Analytics (Mastering Business Analytics)
If you are a student of supply chain management and analytics or a working professional in the said discipline, then you can learn a lot about real-world SCM and data analytics from this book. It exposes you to both technical and managerial skills needed to effectively manage supply chains of any business like retail, digital, food, consumer goods, automobiles, electronics, and more.
The author is a veteran professor in this domain, distinguished the entire supply chain into the following core processes:
Supply chain strategy
And the workforce or people
Accordingly, the author explained slime technical analytics tools that you can apply to the above core processes of your supply chain. It ensures continuous improvement of the SCM process in any business.
Also, you can find the following in detail:
Solved real-world examples to learn how all the techniques work
Techniques to apply the strategies
Mathematical equations and charts to visualize data analytics
Supply Chain Analytics and Modelling
The supply chain of any business generates terabytes of raw data at every touchpoint. However, it is complicated for the trainee SCMs, management students, and business undergraduates to derive valuable insights from such raw data. Here Supply Chain Analytics and Modelling book can help those who are willing to learn how to make sense of supply chain data.
The book presents many business models that experienced SCMs use to make use of supply chain data. Thus, the readers can understand the techniques to utilize supply chain data using these data analytics models. It is a popular way to teach SCM students hands-on supply chain data analytics with real-world business data.
The book touches upon in deep on the following topics of SCM and data analytics:
Supply chain planning
Single objective optimization
Supply chain demand forecasting
Simulating end-to-end supply chain process
Vehicle management, scheduling, and routing models
Case studies of specific business cases
Case studies on supply chain data analysis using software packages
Supply Chain Planning and Analytics
Supply chain planning involves decision-making from dynamically generated demand. For example, the demand for a certain product may sharply rise in the market when you did not stock the product knowing that it is not popular. Now, how you manage immediate procurement, packaging, shipping, and restocking retail shelves is a big challenge for supply chain managers.
Supply Chain Planning and Analytics teaches you exactly the above strategic planning process by analyzing historical and other market data. The book emphasizes the following three supply chain planning-related processes:
Supply chain demand planning
Sales and operations planning
Supply and inventory planning
When you plan well by analyzing supply chain data and including the above strategic processes, businesses ensure a balance between responsiveness and efficiency. Using various texts, concepts,m analytical tools, and case studies, the book teaches trainee SCMs and business graduates supply chain analytics and strategic planning.
The supply chain has always been a complex part of any business because it involves multiple organizations and businesses dealing in different industries. The goals and objectives of these related entities are always different. But being a supply chain manager, you must find a common thread in all the individual parties involved in your business’s supply chain.
Your best bet is equipping your business with a robust supply chain analytics tool or professional who can help you make data-driven decisions. Eventually, you will be able to cut down on procurement, shipping, and stocking costs, take high-quality goods to the public, and earn better profit margins.
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