Jim Hearson | Content Strategist | November 17, 2023
Supply chains have existed in some form for as long as the concept of production itself, but technology and globalization have made today’s supply chains more complicated. Now that even the smallest manufacturers can source raw materials and components worldwide for increasingly complex finished products, having a vague idea of where goods are in the supply chain and when they’ll arrive, based mostly on past experience, is no longer good enough.
Adding to the complexity are global events such as war, disease, financial crises, political turmoil, and labor shortages and strikes, all of which force manufacturers to pivot on a dime. And that’s without even considering the changing preferences and needs of end customers.
Poor supply chain management leads to higher costs, dissatisfied customers, and lower profits. That’s why rigorous supply chain planning is so crucial.
Supply chain planning is the process of mapping out the flow of goods from the sourcing of components and raw materials to the manufacture, distribution, and final sale of finished products. It entails anticipating demand and supply, factoring in data about a variety of internal and external factors to reduce costs, minimize disruptions, and ultimately delight customers.
On the surface, the meaning of supply chain planning seems clear: planning for supply to meet demand. While the idea is simple, the execution is not as manufacturers must grapple with unpredictable factors, including sudden spikes in demand when a product goes viral, strikes affecting the availability of production line workers, truck drivers, and other key personnel, and major events such as wars, pandemics, and natural disasters.
Supply chain planning can help improve operations by standardizing procedures, reducing waste, and preparing for variability. A well-run supply chain lowers manufacturing costs, improves the reliability of deliveries, and helps manufacturers respond to unplanned demand. The best supply chain planning practices help manufacturers identify, anticipate, and adjust to change, with built-in what-if scenarios layered on top of data on the supply and demand patterns they generally encounter under normal conditions.
How is it possible for manufacturers to plan for the unpredictable? To begin with, they need to understand the known factors by analyzing historical sales numbers and data on demand patterns. Then they can layer in data on economic, market, and customer buying trends as well as planned events to predict what “typical” demand should look like.
Next, manufacturers need to work out their existing supply. How much is on hand? Is there enough to meet the projected demand? Is there more than enough? Unsold inventory increases costs for manufacturers, who must pay not only for the resources and labor that went into making it but also the holding costs to keep it stored securely.
Once manufacturers know what they have, they can think about what they need to make to meet future demand. This will include getting a sufficient supply of raw materials and works-in-process and securing the resources required to produce finished products.
At this stage, while a manufacturer may be ready for an ideal-world scenario, it must extend its supply chain planning to the real world. This involves considering what-if scenarios and coming up with a plan for each. What if some components aren’t available because of a natural disaster, or a nationwide trucker strike strands vital materials or finished goods on loading docks? What if onward demand varies greatly from what the manufacturer forecast? This is where supply chain planning comes in.
Supply chain planning is a complex process, but it essentially involves five stages. Mastering each stage, in large part by analyzing the best data available from a variety of sources, gives manufacturers a much better chance of building resilience against variable market and other conditions.
Product planning is at the heart of any supply chain. Before they think about obtaining the resources required for production, manufacturers must plan what they’ll be producing. This includes determining whether to simply produce more of the products that are already successful, update products to maintain and improve their appeal, or introduce innovations that competitors don’t offer. Manufacturers must also establish revenue and profit goals for each product, determining whether to define success as turning a simple profit, turning a large profit (for example, as the result of a big investment in a product), or breaking even (for example, on a new product introduced to help boost sales for others in the catalog).
In the demand planning stage for a particular product, manufacturers account for a variety of factors, including previous sales, market sentiment, economic conditions, the availability of substitute products, market size, and the price elasticity of the product. Manufacturers use supply chain planning applications, the most advanced of which use AI and machine learning, to analyze data on such factors to generate precise demand forecasts so they don’t produce too much or too little.
Closely aligned with demand planning is supply planning, whereby manufacturers lay out what it will take to make enough—but not too much—of the product they forecast customers will buy at a given price point. Factors manufacturers must consider in their supply planning include the amount of inventory they already have on hand, their production capacity and that of their contract manufacturers and materials suppliers, the reliability of those partners, and external factors that could disrupt parts of the supply chain, such as adverse weather patterns, disease outbreaks, labor instability, and geopolitical turmoil.
This stage lays out precisely how a given set of products will be manufactured, including the numbers needed to meet demand, the labor, equipment, and other resources required, the facility or facilities that will manufacture the product, and the process and schedule for making the product. The goal is to run as lean as possible so raw materials and end products aren’t wasted, without sacrificing quality.
This ongoing executive-level process pulls together demand, supply, and financial planning to forecast the revenue and profitability of a given product line over the next several years. S&OP also revisits the demand planning stage by allowing sales, marketing, and other post-production departments to bring fresh data to the production side. This aligns operational teams so they can better meet organizational and financial goals.
The idiom “fail to plan, plan to fail” is particularly applicable to supply chains in this fast-paced world where processes are built to have razor-thin tolerances to maximize efficiency. Unanticipated snags at any stage in a supply chain can cause it to grind to a halt.
With rigorous, data-intensive planning, manufacturers can maximize the efficiency of their supply chain management and lower the costs involved in purchasing, production, inventory management, and logistics. They can also improve the flow of goods, anticipate potential supply disruptions, and formulate contingency plans. Happier customers and higher profits are the ultimate gains.
So far, we’ve covered the importance of supply chain planning and the nuts and bolts required, but those nuts and bolts are just pieces of scrap metal if you don’t have an idea of how to put them together. Here are the key elements.
The more high-quality data a manufacturer can gather and analyze, the more accurate its planning models and forecasts will be. That data includes historical sales numbers, current budget figures, existing inventory levels, numbers on manufacturing capacity and resources, and the data gathered through S&OP. It also includes data on market size and trends, customer sentiment and buying patterns, the state of the economy, and other factors. To gather external data, manufacturers might mine third-party aggregators, institutions, research journals, and respected industry publications. Software for scenario planning can make this process easier by pulling in data from external sources automatically. To gather internal data, manufacturers can manually sift through records or use supply chain planning software to automate the process. The final step is to aggregate both the external and internal data so planners can review the potential impact of various scenarios.
Originating in Japan after WWII, with Toyota as one of its main practitioners, this lean inventory strategy has spread worldwide. The theory is that by ordering raw materials and components just in time to be processed, manufacturers can minimize inventory stockpiles and the associated costs. However, part of supply chain planning involves considering the contingency if supplies are disrupted or demand exceeds forecasts, scenarios for which manufacturers tend to keep a certain amount of safety stock on hand.
Visibility within a supply chain involves being able to track each material, product, and service throughout the process. Manufacturers must ensure all parties remain aligned, ideally using a digital system that all parties can access and use to share updates. Cloud applications make it easier to provide visibility to all parties because anyone who is authorized to use them can access them anywhere. Manufacturers must also set quality expectations and make those visible to all parties in the supply chain, managing them from the beginning to avoid situations in which quality that passes for one party fails to meet expectations for the next party in the chain. Being able to see all the factors within the supply chain also helps manufacturers spot and rectify any inventory shortages or logistical issues.
Manufacturers require consistent processes across every step of their supply chains, from product planning to final delivery. Standardization involves more than automating the assembly line, although this is often a first step. Today, it often involves using the same software across factory locations, and making sure all suppliers have the same information, so all production lines follow a consistent, step-by-step process every time. These steps include ordering raw materials, issuing purchase orders, shipping and logistics, quality control, assembly, and sale. Standardized, automated processes allow for economies of scale and reduce the potential for human error, which in turn makes it easier to produce goods that meet quality control and regulatory standards. A lack of standardized processes creates information silos, hampering a manufacturer’s ability to see the whole supply chain and develop a supply plan that will accurately meet demand.
TaylorMade Golf moved to supply chain planning software in 2018. When the pandemic hit two years later, they were well-placed to deal with a shutdown in manufacturing and many logistical areas as well as a subsequent explosion in orders once more people took to golf as their socially distanced exercise of choice. TaylorMade could prioritize orders to meet the uptick in demand, even if inventory was relatively low, because their supply chain planning technology and workflows made the process that much smoother.
Another company that needed to move quickly due to the pandemic was Santa Cruz Nutritionals, which produces gummy vitamin supplements. Their old spreadsheet-based supply chain planning system left planners with far too much data to chew on when orders shot up during lockdowns. By moving to the cloud, Santa Cruz Nutritionals optimized supply chain planning with enhanced visibility into supply and demand data. They can now balance purchasing and manufacturing requirements by automating order recommendations in real time when certain triggers are hit.
Zebra Technologies also unified supply chain planning processes when they moved from multiple on-premises business systems to a single system in the cloud. The switch gave them the ability to analyze multiple sets of supply chain data alongside each other and use the results to drive efficiencies. For example, integrating their transportation management and planning systems allowed Zebra Technologies to use traffic forecasts while planning shipments—and save US$2 million in freight costs on one of its orders.
The benefits of strong supply chain planning are only magnified at larger organizations. GE Power used to have a massively unwieldy supply chain planning procedure that included multiple ERP systems with 15 forecasting tools, all operated by different divisions that relied on push-based planning. Unsurprisingly, forecast accuracy was only around 55%.
GE Power adopted a modern supply chain strategy, consolidating these disparate tools and systems using a single supply chain planning solution. They did away with different departments’ standalone practices and gained the ability to dive deeper into a wider range of data more quickly—reporting that used to take five days can now be completed in a matter of hours. They also built customer order data into the demand planning and forecasting process, allowing for a much more pull-based system that has helped increase forecast accuracy to around 70%.
Each manufacturer’s supply chain planning process will differ to some extent, based on the company’s unique situation and goals, but the following steps are essential.
Manufacturers must set supply chain goals that are SMART: specific, measurable, achievable, relevant, and time bound. Goals might include improving efficiency to cut waste, gaining visibility into subcontractors’ operations, or ensuring there’s always enough product to satisfy customer demand. Defining those goals with the SMART framework will help ensure they’re achieved because it provides each relevant supply chain player with action items, deadlines, and a way to measure success.
In evaluating current supply chain performance, another classic framework proves helpful: SWOT analysis. The tried-and-tested method involves identifying strengths, weaknesses, opportunities, and threats. Manufacturers can use this analysis to get an idea of how their supply chain is faring. Then they can identify improvements by doubling down on strengths, eliminating weaknesses, exploring new opportunities, or minimizing threats.
With goals established, manufacturers should consider how to achieve them and the tools they’ll use to do so.
With easy access to real-time data, manufacturers can see how their supply chain theory is working out in practice. For example, they might check that the flow of raw materials is arriving as and when required, monitor sales feedback, or ensure their cash earned versus cash invested continues to improve.
If feedback is showing that progress toward the objective is slowing or has stopped, manufacturers can use the available data to adjust their supply chain plan. If demand warrants more resources, for example, manufacturers could add flexibility into the plan by sourcing additional or alternative suppliers. Changes in component or staff availability or an issue with transportation might warrant adjustments to delivery schedules.
The best supply chain planning software provides manufacturers with the data required to make accurate and timely decisions relating to demand, supply, and production, enabling them to plan a supply chain that minimizes cost and effort. It also allows them to react to changing market conditions so they and their customers aren’t adversely affected.
Supply chain planning software should integrate easily with your other supply chain systems, such as procurement, order management, inventory, and logistics. For example, some manufacturers use blockchain technology to securely offer transparency to all members of the supply chain so they can track materials or components down to the serial number. Feeding this data back into the supply planning system can help inform decisions on how much to order next and from which supplier. A supply chain command center can manage all this information, integrating internal and external data to boost manufacturers’ decision-making capabilities.
No matter the size of the supply chain, making it simpler and faster is always a positive. Manufacturers can achieve this with Oracle Fusion Cloud Supply Chain Planning.
By moving supply chain functions to the cloud, manufacturers gain visibility into their processes from end to end. They have useful data about demand on hand for analysis to help them predict supply problems, and everyone involved in supply chain planning can provide real-time input to make changes if needed.
Oracle Supply Chain Planning allows manufacturers to automate tasks such as placing new orders and identifying alternative suppliers. With machine learning, it also analyzes predicted and completed sales and offers feedback on how to improve the planning process so that supply chains can get slicker and the cash-on-cash ratio can get better with each production run.
What are some challenges of supply chain planning?
Effective supply chain planning relies on accurate and timely data, which isn’t always readily available. Meanwhile, many external factors that influence supply and demand, such as pandemic outbreaks, natural disasters, trade wars, and labor strikes, are hard to predict even with the best data.
Which technologies are used for supply chain planning?
Supply chain planning is its own application module within most major supply chain management software suites, encompassing functions such as production scheduling, integrated business planning, collaboration, sales and operations planning, replenishment planning, and backlog management. The most advanced supply chain planning applications include built-in, AI-based analytics.
What metrics are used to measure supply chain planning performance?
Among the metrics used to measure supply chain planning performance are forecast accuracy, cash-on-cash cycle time (how long it takes from paying suppliers to receiving payment from customers), inventory supply and turnover, order fill rate, on-time shipping, and supply chain cost as a percentage of revenue.
How can manufacturers improve their supply chain planning process?
Having visibility into the entire supply chain process means that manufacturers can see what’s going right and what could be improved. This allows them to keep track of stock, find alternative suppliers, identify and eliminate bottlenecks, and much more—all in a timely manner, thanks to real-time data and tools imbued with artificial intelligence that can automate most of the process.
What is the difference between supply chain planning and logistics management?
Logistics management focuses on getting raw materials, components, and finished goods from A to B, whereas supply chain planning is concerned with getting the broader start-to-finish process right.
How can manufacturers optimize their supply chain planning process?
Manufacturers need to first set goals for what they want to achieve, then gather as much up-to-date data as they can from all relevant sources and regularly adjust their planning process based on the results achieved and new data that becomes available.
Supply chains are now at the core of any business decision. With increasing supply and demand variability, supply chain leaders need to make big decisions faster than ever before. To stay competitive, you need to quickly detect, decide, and execute on any business condition.