[Book Club] Supply Chain Management For Dummies
Supply Chain Management For Dummies
Daniel Stanton
Three-Sentence Summary
There are three supply chain flows: material (product or service), money, and information. Managing supply chains means managing the flows of the three flows in a timely manner. When technology advances in any of the three flows, the managing methods advance while the principle remains.
Who Is This Book For?
For someone who has been involved in part of the supply chain (which is surprisingly broader than you might think) but never has a chance to have an overview of it. For someone who wants to specialize in this field but doesn’t have enough real-world experience. Or, for someone just wondering why Tim Cook succeeded in Apple.
Major Concepts
Supply chain management is again another type of complex system management. I come from the field of system engineering, and I have spent significant time searching, reading, and comparing complex system analysis methods. They are surprisingly similar in helicopter view. They have randomness playing a role; they evolve through time and environmental exchange; their parts or as a whole react with a chain of consequences; it is easy for the observer to be distracted and focus only on one of the subsystems; it is difficult to judge with certainty whether the result is caused by a specific intervention.
So now, let’s dive into the topic of supply chain with a (not so heavy) personal perspective.
SCOR Model
The supply Chain Operations Reference (SCOR) model is one of the most commonly used tools for describing, designing, and measuring the performance of supply chain processes.
The SCOR model illustrated above provides a comprehensive framework for analyzing supply chain processes. Within this framework, the yellow boxes represent core operational components essential for value creation and customer delivery. The Plan process serves as the central coordinating function, interfacing with all other operational elements. The model demonstrates a strategic progression through Source (procurement of materials), Make (product manufacturing), and Deliver (customer distribution). Additionally, the Return process, positioned beneath these primary functions, facilitates the management of reverse logistics when products require upstream movement within the supply chain. A reminder: some boxes have arrows, which are the indication of flows (materials, money, and information).
Remember, in the beginning, I mentioned the supply chain is much broader than you might think. Here is what I mean. You might be an engineer, sitting in the Make process and interacting mostly between Source and Deliver. We also need marketing and accounting to enable the supply chain to achieve its goal. An OEM (Original Equipment Manufacture) connects tier 1, 2, and 3 suppliers, retailers, and distributors. Seldom is someone outside a supply chain. Most likely, it is blind of us when we are right in the middle of it.
Seeing ERP system as a huge database of supply chain
There are lots of subsystems in a supply chain. In order to let the three flows run smoothly from point to point, those subsystems need to be planned, designed, and monitored. Naturally, it draws all brilliant businessmen to develop tools accordingly. (In fact, almost all of them evolve from an internal fast-growing spreadsheet that, at some point, no one is able to understand.)
Here I quote a few from the book:
TMS: transportation management system keeps track of shipments and carriers. It may contain features such as a routing guide that tells you which mode of transportation and which carrier you should use for a shipment
WMS/WES: warehouse management and execution system keeps track of all the stuff that’s stored in a warehouse or distribution center. It also helps pick each order and combine the individual order lines into shipments.
MRP: material requirements planning system finds out what part you need, and when and where you need them, so that you can manufacture your products.
MES: manufacturing execution system connects to PLCs and synchronizes the processes in a factory.
LMS: labor management system helps decide how many people you need on each shift to meet the demands on your warehouse. It also tracks the performance of your workers and identify those who deserve rewards and those who need more training.
CRM: customer relationship management system keeps track of your customers.
SRM: supplier relationship management system keeps track of your supplier information
Linking these tools into the SCOR model, we see they spread among the three processes: Source, Make, and Deliver.
ERP, an Enterprise Resources Planning system, merges all those tools (including the ones not mentioned here) into one massive system. One famous player is SAP. You might have heard someone works as an SAP engineer. Yes, as it is such a complex tool, the company that buys it will most likely hire a group of SAP engineers to configure it. It might last from months to years to set it up and let it be fully functional. Logically, not every company needs an ERP system, and not everyone needs all the functionalities in an ERP system.
I have another anecdote about the ERP system. Nike spent 400 million on building an ERP system in 1999. The project didn’t finish on time (7 years to put it online) and on budget (100 million overcost), see my previous post book-club-how-big-things-get-done.
Back to our topic. Essentially, the author's insight into the ERP system gave me a new perspective.
Supply chain software is really just a big database, storing transactions and tracking relationships among different types of data.
When you hear “big” “database”, what is your natural reaction?
How can I get what kind of information about it? Right?
Looking into the future
Supply chain modeling software uses sophisticated math and performs complex calculations to predict the behavior of actual supply chains. Where does the data come from? ERP systems. Specifically, cleaned data from any level of ERP systems (not necessarily the most complex one like SAP). Cleaned data means supply chain metrics, which involves SCOR model performance metrics, Operational, Financial, People, and Sustainability metrics. I will not take too much space here to list them.
Then, there are four levels of analysis based on the data.
Level 1: Descriptive analytics. Descriptive analytics involves structuring and filtering historical data to identify patterns and trends. Six Sigma uses a lot of descriptive analytics.
Level 2: Predictive analytics. Predictive analytics uses historical statistics to estimate future probabilities. In other words, predictive analytics uses what has happened in the past to make forecasts about the future. Predictive analytics are used heavily in demand planning.
Level 3: Prescriptive analytics. Prescriptive analytics compares forecasts with real-time data, and then uses artificial intelligence (AI) to provide people with recommendations and instructions about what they should do. Prescriptive analytics tools are sometimes called recommendation engines.
Level 4: Advanced analytics. Advanced analytics involves automating processes and taking humans out of the loop. Autonomous vehicles that make routing decisions and respond to traffic conditions are example of advanced analytics.
The first two are intuitive, almost well-deployed, and functional in an up-to-date company. The rest is difficult to grasp as B2B services are naturally mostly outside public view. I have put a few links here for you to explore new ways of supply chain management. One day, ERP will fade from the stage. However, one question will always remain to push humanity moving forward. Why do we (humans) exist when AI/machines can take over more and more tasks?
https://www.everstream.ai/risk-center/
https://www.resilinc.com/
https://www.accio.com/