Surprisingly, supply chain planning is becoming a more interesting topic in this era of digital transformation and AI. Indeed, supply chain professionals now can use a wide range of software planning tools to tackle ever increasing complex logistics problems. However, these tools don’t necessarily make supply chain planning easier to grasp or implement. In fact, there are many aspects of supply chain planning such as analyzing demand, managing risks, and designing networks, to name a few. Simultaneously, supply chains are becoming more complex, with vast amounts of data to analyze, shorter planning cycles, higher customer demands for faster service, and increasingly fierce competition.

Indeed, the ever-increasing complexity of supply chains demands superior planning knowledge and rapid decision-making for survival. In this article, I’ll explain the differences between strategic, tactical, and operational supply chain planning. Also from a data analytics perspective, I’ll look at the six types of supply chain planning: demand planning, supply planning, production planning, integrated business planning, risk mitigation, and strategic network design. Finally, I’ll highlight how advanced technologies are increasingly merging supply chain planning with operational decision-making, thereby compressing and improving decision cycles.

“The line between disorder and order lies in logistics…”

Sun Tzu

What Is Supply Chain Planning and The Different Levels Of Planning?

First, supply chain planning is an ongoing process that occurs at all levels of a supply chain organization. To break it down, below is a definition of supply chain planning and an explanation of the three different levels of planning that occur within a supply chain operation.

What Is Supply Chain Planning (SCP)? 

“It is a method of forecasting product supply needs based on expected customer demand. The process starts with raw materials and ends with delivery to the customer. SCP optimizes the way companies prepare to meet and exceed expectations.”

Levels Of Supply Chain Planning. 

Supply chain planning is a continuous process that happens at the strategic, tactical, and operations levels. 

• Strategic Planning. This is the highest level of planning with a planning horizon of 3 to 10 years. Here executives are making decisions on things like business acquisitions, need for a new distribution center, and planning for a major increase of revenue.
• Tactical Planning. Planning at the tactical level usually spans 6 months to a year. Additionally, drivers of this type of planning are things like a new semi-annual forecast, new policy to reduce inventory, or selecting a major supplier and so on. 
• Operational Planning. These are the day-to-day and weekly activities to meet short-term operational goals. In particular, operational planning is focused on making adjustments and taking specific actions to assure operational activities stay on track and create the greatest value.

See anyLogistix’s article, SUPPLY CHAIN PLANNING AND MODELING FOR DECISION-SUPPORT for a more detailed discussion of the different levels of supply chain planning. 

“If you don’t know where you are going, any path will get you there”

Lewis Carroll, Alice in Wonderland

Six Types of Supply Chain Planning Within Logistics.

There are six major types of supply chain planning. These include planning for demand, supply, production, integrated business planning (sales & operations), risk mitigation, and strategic network design. Let’s first start with demand planning.

1. Customer Demand Planning: Powered By Predictive Analytics And Modelling.

Demand planning consists of analyzing data and data modeling using predictive analytics so that companies can better understand customer needs and forecast demand more accurately. With the right tools and analysis, companies can gain insights into customer behavior, seasonal trends, and other factors that impact demand. Hence, the end result of demand planning is that planners have quantified the expected demand of each product and service. Specifically, key data sets include:

Key Demand Planning Data Sets

a. Historical Sales Data.

Predictive Analytics Types: The Best Opportunities For Supply Chains

Planners collect this data from past transactions. For example, point-of-sales (POC) systems. Also, using predictive analysis, planners can model this data using time-series analysis or regression models to identify trends and seasonality in customer demand. 

b. Internal Trends Data.

Here analysts look internally within their organization. For example, a new product launches or changes in sales channels. So once they collect the data, they can model using statistical techniques such as regression analysis to identify the impact of internal trends on customer demand.

c. External Trends.

Here planners look at external factors that can change demand. For example, this can be such things as economic indicators or industry trends. This data can come from various sources to include government reports, industry publications, and market research firms. Then they can use data model techniques such as time-series analysis or econometric modeling to predict changes in customer demand based on external factors.

d. Events and Promotions.

A variety of product-related events and sales promotions can have a significant impact on customer demand. So planners need to incorporate this data into their predictive modeling to create demand forecast.

See GMDH’s 4 Crucial Elements of Demand Planning for 2023 for more information of demand planning analytics.

“All models are wrong; however, some are useful.”

George Box

2. Supply Planning Analytics: Predict Supplies Needed And Plan Supply Strategy.

Supply planning involves predicting the supplies needed to fulfill customer expectations. Specifically, supply includes the sourcing of raw materials, components, and other goods needed for production. Additionally, there are retailers and Ecommerce operators with no production processing. In this case, their supply planning is focused on their suppliers such as manufacturers and wholesalers. 

So for supply planning, planners need to have a good understanding of inventory levels, production capacity, and supplier lead times. Indeed by accurately predicting supply needs, companies can avoid stockouts, excess inventory, and other supply chain disruptions. To detail, see below for the key data sets and analytics that you need for supply planning.

Key Demand Supply Planning Data Sets

a. Supply Requirements Analysis.

Supply requirements analysis is essential for businesses to accurately determine the amount of materials and resources needed to meet demand. So by utilizing historical data, and forecasting models, supply requirements analysis allows organizations to optimize their procurement processes. Hence, businesses avoid both shortages and excess inventory. Also, this analysis ensures that the right quantities of supplies are ordered at the right time. As a result, this leads to cost efficiencies and increased customer satisfaction.

b. Analytics To Determine Sourcing Strategy.

The Strategic Sourcing Process Using Data Analysis In 7 Steps: The Best Way For Unsurpassed Supplier Results

Implementing a data-driven sourcing strategy is crucial for optimizing supply chains. Indeed by leveraging analytics, companies can identify the most reliable suppliers and negotiate competitive pricing agreements while minimizing risk exposure. Also, advanced analytical tools enable organizations to evaluate factors such as lead times, supplier performance, cost structures, and market conditions to develop a strategic sourcing plan.  For more details, see my article, The Strategic Sourcing Process And Data Analysis.

“Planning is everything. The plan is nothing.”

DWIGHT D. EISENHOWER

c. Analytics To Determine Inventory Management Strategy.

An effective inventory management strategy is essential for maintaining optimal stock levels and satisfying customer demand. Additionally, supply planning analytics provides valuable insights into inventory trends such seasonality, product life cycles, and regional market demand. Further, these insights help companies to forecast future inventory needs more accurately. Hence, this reduces stockouts and excess stock holding costs. For more details, see my article, Better Warehouse And Inventory Analysis.

Better Warehouse And Inventory Analysis Is The Way For Unsurpassed Results, Reduced Wastage

“Without data you’re just another person with an opinion.”

Deming

3. Production Planning: Determine Operational Resources Needed.

Production planning is the process of determining the operational resources needed to meet customer demand. Specifically, this includes capacity planning, scheduling production, and allocating resources such as labor, materials, equipment and facilities. Also, most production operations are either batch, job, or continuous flow operations. As a result of this process, analysts develop a production plan. Of course, supply chain operations and manufacturing are usually separate organizations. So typically, a supply chain operation does not create production plans. On the other hand, a scaled down production plan is sometimes needed for kitting or large value added operations within a supply chain.. 

Also, supply chain operations do need to have contingency plans to mitigate anything that can slow or stop production processing. Additionally with the right data analytics tools and software, businesses can create a production plan that reduces waste and only produces what is required. For more details on production planning, see ERPNext’s What is production planning and how to do it? A comprehensive guide.

“Everyone has the heart of a champion on game day. It’s the heart you have during the weeks, months, and years of preparation that actually makes a difference.”

John Raymond

4. Integrated Business Planning (IBP): Synchronize Planning As Well As Finalize Both Metrics And Budget.

Integrated Business Planning (IBP) is an important part of supply chain planning. Also, IBP is much like a Sales and Operations Plan (S&OP). The primary difference is that the IBP is more focused at the organization’s executive level and is more long term. Indeed, both of these collaborative types of planning involve both finalizing and synchronizing planning, metrics, and budgets across all business functions and departments. Further, this cross-functional process aligns sales forecasts with production plans to balance supply and demand. As a result, sales, production, inventory, and new product development plans as well as a financial plan are finalized.

Traditionally, medium and large businesses have used Enterprise Resource Planning (ERP) systems like  SAP to facilitate coordination as well as data modeling and “what if” analysis. Also, by breaking down silos and improving communication across the organization, businesses can achieve a comprehensive view of future supply chain operation. Hence, this allows for better decision-making when finalizing supply chain plans. Indeed, the goal of both IBP and S&OP planning is that through collaboration the company can perform better predictive analysis to grow the business and manage risk.

“If you want to kill any idea, get a committee working on it.”

Charles Kettering

5. Risk And Event Supply Chain Planning: How To Mitigate Unplanned Or Superordinary Events.

Risk Mitigation For Supply Chains: How To Best Identify, Make Assessment, Overcome

Risk and event supply chain planning involves developing strategies to mitigate unplanned or extraordinary events. This can include natural disasters, supply chain disruptions, or changes in customer demand. So by proactively identifying potential risks and developing contingency plans, businesses can reduce the impact of these events on their supply chain operations. 

Further, it is critical for planners to analyze every link in the supply chain to identify bottlenecks, breakdowns, and delays. Also if businesses are making changes to the supply chain such as a new supplier or major software update, they need to be prepared for unintended consequences. Lastly to mitigate these risks, planners need to be proactive and add redundancy into the supply chain and have contingency plans in place. Also for more on managing supply chain risks, see my article, Risk Mitigation For Supply Chains: How To Best Identify, Make Assessment, Overcome.

“Everybody has a plan until they get punched in the mouth.”

Mike Tyson

6. Strategic Network Design: Supply Chain Planning To Optimize Operations

Indeed, strategic network design is an important component of supply chain planning. This involves optimizing the supply chain network to maximize efficiency and minimize costs. So by leveraging data analytics tools, companies can analyze their supply chain operations and identify opportunities for improvement. This may include consolidating suppliers, changing transportation methods, or optimizing inventory levels. See below, for explanation of when network design is needed, what data planners need to collect, and data analytics required.

a. When Is Strategic Network Design Needed?

In smaller companies, strategic network design is usually done on an ad hoc basis. In contrast, network design for a large national or multinational company is critical and a continuous process. Specifically, below are types of events that would trigger a network design project.

Types of Events that Trigger a Network Design Project

• A major business expansion, such as an acquisition
• A change in business strategy, such as targeting new market opportunities
• The change of the business with the passage of time
• Responding to competitive pressures

b. Data Needed for Network Design Planning.

Network design projects require a significant amount of data. So, typical data required includes operational and historical data. To detail, below are the types of data needed for supply chain network design analysis.

Key Demand Network Design Data Sets

A Data Centric Business: The Best Way To Agility, One Truth, Simplicity, Technology Innovation

• Products and customer information
• Product flows and volumes including seasonality
• Customer order files
• Inbound and outbound shipments
• Intra-network facility shipments and routings
• Transportation routing, modes, rates, service levels, policies, and costs
• Facility information including assets, operations, capacities, and costs
• Inventory policies, levels, and requirements
• Customer service requirements
• Policies (sourcing, transportation, inventory, and customer service)
• P&L for supply chain operations

c. Network Design Analytics.

Lastly, as network analysis is very data intensive and is usually project based, this type of work is many times done by supply chain consultants that have experience in your industry. Whereas if you are a large company and have the expertise, you also can rely on network analysis software to assist you in what changes to make to your supply chain network. Also for more references, see TompkinsInc’s What Is Supply Chain Network Design And Why It Is Important?

“It’s critical that we drive digitization of supply chains, because without it, there will be no transparency; and without transparency, there will be no accountability.”

Christian Lanng

Data Analysis Examples To Best Overcome The Challenge Of Supply Chains

Conclusion and More References.

So, in this article I have described six distinct types of logistics planning that supply chain planners have traditionally used for strategic and tactical decision-making. Specifically, these supply chain planning types include developing strategies for demand, supply, production, business integration, risk, and optimizing logistics networks.

Further, information technology is changing the nature of supply chain planning. Indeed, advanced analytics is providing many opportunities to digitalize supply chain planning by both streamlining and providing better analytical tools for planners. Moreover, technology is compressing planning cycles and even merging strategic, tactical, and operational decision-making. In fact, a digital supply chain can enable decision-makers to have direct access to planning tools and the best information to make rapid decisions. So with this in mind, see references below for valuable insights on how information technology and data analytics is impacting both supply chain planning and decision-making.

More References: Analytics, Operational Planning Examples, Rapid Man-Machine Decision-Making

• Types of Data Analytics Empowering Supply Chains. Analytics today can answer these questions: What happened? Why did it happen? What is likely to happen? What action should we take? What do we do now? What question should I have asked? For details, see my article, A Data Analytics Perspective To Better Empower Supply Chain Managers.
• Rapid Man-Machine Planning and Decision-Making. Within a digital supply chain, decision-makers have the potential to obtain real-time data on a given situation, analyze the information immediately, make a decision, and initiate action. This rapid decision-making capability is akin to the military decision-making concept called the OODA (Observer-Orient-Decide-Action ) Loop made famous by the fighter jet pilot Colonel Boyd. For more information see, Unvarnished Facts’ article, The Forgotten OODA Loop: It’s An Amazing Military Decision Framework And Awesome Gift To Business.
• Data Analytics Examples at the Operational Level. For more information on the types of data analytics that supply chain managers need at the operational level, see my article, Data Analysis Examples To Best Overcome The Challenge Of Supply Chains. In this article, I introduce Ralph, a savvy supply chain manager who demonstrates the power of supply chain analytics. Additionally, more data analytics topics discussed include sourcing, warehousing, inventory management, order fulfillment, customer service, and customer delivery analysis.

Additionally, for more discussion on supply chain planning in general, see GEP’s Supply Chain Planning: What, Why, And How, Netsuite’s Supply Chain Planning, and G2’s Supply Chain Planning.