A Guide to World-Class Demand Planning
Published: March 14, 2023
Building a world-class demand planning process requires collection, collaboration, and disaggregation.
In an interview with Simon Joiner, Chakri Gottemukkala discussed the importance of the demand planning process, and how to ensure success at each phase of the process. He explained that there are different cycles within the overall demand planning process, and that there are some standard steps that happen in each cycle. In this article, we will go through the steps of the demand planning process, and provide insights on how to optimize each step for success.
Step 1: Collect Data
The first step of a world-class demand planning process is to automate the collection of data. This includes historical sales data, external drivers, and commercial actions. However, automated data collection has brought its own challenges, as a much of this data is spread across different spreadsheets and disconnected systems. A next-generation demand planning solution is invaluable at this stage, as it automates the collection of all this data into a combined data model. This, in turn, makes it easy for demand planners to access and use the data they need, resulting in more accurate demand forecasts.
“The challenge today in automating the collection of data for demand planners is that much of this data is in spreadsheets, disconnected, and coming from different systems. One of the key benefits of a world-class demand planning processing system is the automation of the collection of all of this data into a combined data model that then makes it completely easy for the demand planner to access and use.”
Chakri Gottemukkala —
Co-Founder and CEO of o9 Solutions, Inc.
Step 2: Perform a Post-Game Analysis
Once the data has been collected, the next step is postgame analysis, a critical step that is often overlooked. It is not enough to simply generate a demand forecast every week or month without sufficient time and rigor spent on analyzing what happened in the previous period. By carefully analyzing the forecast versus planned deviations and correlating with expected drivers, such as commercial or supply chain drivers, you can identify the drivers that transpired as expected, and those that did not. This is a crucial step as it leads to two important actions. Firstly, should any drivers be changed going forward? Secondly, do the forecasting models themselves need to be updated to improve accuracy? By taking the time to properly conduct postgame analysis, businesses can make informed decisions that will help drive future success.
“By analyzing the forecast versus planned deviations and correlating them with all the expected drivers, you can identify the drivers that caused the forecast and the market drivers, such as commercial or supply chain drivers. This is a crucial step because it leads to two key actions. First, should some drivers be changed going forward? If the drivers did not perform as expected, they should be changed to improve future forecasts. Second, should the forecasting models themselves be updated because their accuracy is not good enough?”
Step 3: Generate a Forecast
Once the postgame analysis has been completed, the system-generated forecast is the next step. This forecast is based on statistical and machine learning methods, which use both historical sales and drivers as inputs to generate accurate predictions for future periods. By applying specific rules and algorithms, the consensus forecast can be automatically disaggregated into the necessary components for supply chain decision-making.
“This is a statistical forecast, a machine learning-based forecast that takes into account the drivers and historical sales as inputs, and generates a forecast for future periods. There are rules and algorithms that can be applied to take the consensus forecast and automatically disaggregate it to what the supply chain needs to make supply chain decisions.”
Step 4: Review the Demand
The next critical step in the demand planning process is the demand review. During this step, the planning organization conducts a thorough review of the forecast, with a particular focus on identifying the big exceptions. This involves analyzing forecasts that have significantly changed beyond thresholds from the previous period, identifying what has gone up and what has gone down, and assessing the potential impact on the supply chain. It is essential to apply good reasoning to any big changes and provide clear explanations for those changes. Failure to do so may result in the supply chain second-guessing the forecast changes, leading to reduced confidence in the demand plan. The primary objective of the demand review is to identify and focus on the big exceptions, ensuring that any potential impacts on the supply chain are appropriately addressed.
“One of the critical steps in reviewing the forecast is to really narrow down on the exceptions. What forecasts have significantly changed beyond thresholds from last time? What has gone up, what has gone down? Because any big changes will drive a lot of impact to the supply chain, there has to be good reasoning applied to any big changes. In fact, explanations have to be given for those big changes; otherwise, the supply chain is going to second-guess and not accept the forecast changes.”
Step 5: Collaborate
To establish an agreed-upon demand, all stakeholders should come together to collaborate on creating a common level of demand forecast. Even though the level of detail required by the supply chain or sales team may differ, it is important to focus on identifying changes to the forecast and the reasoning behind them. Documenting the assumptions and reasons behind these changes is essential, as it helps establish the reason for the baseline forecast along with the reasoning for changes.
“The next step is to bring all stakeholders into a collaborative demand planning process where a common level of demand forecast is established. The common level could be different from the level of detail that the supply chain or sales team needs, but it is the one number where everyone agrees on what the market demand is. At that level, the focus should be on identifying changes and providing the reasoning behind those assumptions. Do we agree on this new forecast? Do we agree on the changes to the forecast? Have weather forecasts gone up or down? Documenting the assumptions and reasons behind the forecast changes is a critical step.”
Step 6: Perform a Risk and Opportunity Assessment
When forecasting demand, stakeholders may have different views on the risks or opportunities that could affect it. To address this, a collaborative and consensus-building process is used to establish the rationale for the baseline forecast, what is expected, and the reasoning behind any changes, as well as identifying any risks or opportunities. Based on this, demand scenarios are established for the supply chain to take into account.
“The forecast has been generated by the system, but there could be potential downside risks or potential upside opportunities to the forecast that different stakeholders have input on. These are used to construct what we call demand scenarios. In this collaboration and consensus process, you establish the reason for the baseline forecast, what we expect, and the reasoning for the changes, but also the risks and opportunities. You assess those and establish the forecast scenarios that we want the supply chain to consider.”
Step 7: Disaggregate
Consensus forecasts, while useful, may not provide the level of detail needed for effective supply chain planning. This is where the automated disaggregation step comes in. A next-generation demand planning solution will automatically break the consensus forecast down into a more detailed supply chain forecast that takes the specific capabilities and limitations of the supply chain into account, including production capacity, lead times, and transportation constraints. Once the demand plan has been approved by the supply chain, it determines the amount of risk that can be taken in terms of costs and inventory.
“Supply chain requires a forecast potentially at a more detailed level than what the consensus forecasts provide. Therefore, there is an automated disaggregation step that takes the consensus forecast and drives it into supply chain forecasts. Then, the demand plan, which is now approved by a supply chain that can support it, determines the amount of risk we can take in terms of costs and inventory. This is what we, as an organization, have now aligned to cross-functionally in terms of our sales expectations.”
The demand planning process is critical to the success of any organization. By following the steps outlined above and ensuring that each step is optimized for success, organizations can generate accurate demand forecasts that help the supply chain meet customer demand effectively.
- The demand planning process involves seven steps: collecting data, performing a post-game analysis, generating a forecast, reviewing the demand, collaborating, performing a risk and opportunity assessment, and disaggregating.
- Automating data collection is essential for accurate demand forecasting.
- Postgame analysis is a critical step that should not be overlooked.
- All stakeholders should be involved in the collaborative demand planning process to establish an agreed-upon demand forecast.
- Documenting assumptions and reasons behind forecast changes is essential.
- Consensus forecasts may not provide the level of detail needed for effective supply chain planning, therefore a next-generation demand planning solution may be required to automatically break the consensus forecast down into a more detailed supply chain forecast that takes the specific capabilities and limitations of the supply chain into account, including production capacity, lead times, and transportation constraints.