Today’s supply chains have faced a perfect storm of disruptions over the past three years from a global pandemic to the blockage of the Suez Canal, from port congestion to the invasion of Ukraine—to mention only a few. This new level of disruption and urgency requires managers to build robust and agile supply chain planning processes in order to appropriately respond to the massive fluctuations in supply and demand.
The results from a recent survey of supply chain leaders that we conducted underline that good planning processes enable businesses to navigate major business challenges more effectively.1 Typically, such a process would include providing sound transparency around demand and supply and any arising demand-supply issues, modeling relevant scenarios, and agile, fact-based decision making using the evaluated scenarios.
Over the years the sales and operations planning (S&OP) process has become a cornerstone of the modern planning landscape. The classic S&OP cycle is typically structured around four key meetings:
Any advanced S&OP process leverages scenario planning. Scenario planning enables decision makers to explore different alternatives to the baseline assumption. It does this by testing and evaluating the impact of specific choices (for example, applying demand shaping, pre-producing inventory, or leveraging a contract manufacturer) on key performance indicators (KPIs). It can help companies answer pressing questions such as: How do we fulfill this order if we do not get sufficient raw material (on time)? How can we increase supply volume to take advantage of the massive price increases? Or, how do we re-allocate the inventory meant for orders that have now been cut in half?
In our recently published survey, 37% reported the implementation of scenario planning as a key action to increase their supply chain resilience.2 While this figure shows an emerging awareness of the importance of scenarios, most companies still need to develop and implement operational processes and tools to really enable scenario planning. According to the survey, 64% of supply chain leaders are planning to develop their existing planning systems to focus on end-to-end integrated solutions, following an overall trend to shift supply chain IT efforts from visibility to scenario planning in response to the increasing uncertainty.
Indeed, providers of modern supply chain planning IT systems are responding to the increasing complexity in the supply chain by promising to revolutionize S&OP processes through autonomous evaluation of S&OP scenarios and trade-offs. But is a more capable advanced planning system (APS) the solution?
We believe there is a much bigger step change required than just implementing new systems. Companies need to transform their traditional ways of thinking about and conducting their sales and operations planning. Instead of just seeking to gain visibility into demand and supply and focusing on just one solution to demand-supply imbalances, companies need to holistically evaluate many alternatives. This is best done by leveraging a structured five-step framework, which we describe below. The key is to think in mitigation scenarios: Once an issue is identified, it is essential to create different options of how to respond and to evaluate these holistically from a business perspective.
Five steps for success
Even though the S&OP process is seen as common practice, its execution ranges from a pure update/information sharing between involved business functions to cross-functional integrated business decision-making. Although every organization has its own approach, successful preparation of the operational/executive S&OP meetings often follows a clear sequence of steps leading up to the decisions (see Figure 1):
[FIGURE 1] Sequence of steps to successfully evaluate S&OP scenarios
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In the end, a good S&OP process is characterized by making the right, meaningful decisions to steer the business. While these decisions can be prepared (semi-)manually, introducing a system support comes with advantages. Modern IT systems can handle a much larger number of different scenarios and calculate the consequences of them with high speed and accuracy, which allows for a wider range of decision alternatives to be tested in the S&OP process. But even though IT systems can help evaluate scenarios, supply chain planners still need to identify the relevant scenarios to be tested in the first place. With or without IT systems as enablers, the following steps can be implemented by any business to upgrade its S&OP process.
Step 1: Identify issues
During the demand and supply reviews and the demand-supply matching, demand and supply plans are being created and reconciled. Here, imbalances become evident (see Figure 2) with either planned capacities not being fully utilized or demand exceeding current supply capacities. Planners (or the planning system) typically are able to balance out minor gaps based on pre-defined rules, such as pre-producing up to a given number of weeks in advance or building up/reducing inventories within given thresholds. However, a number of imbalances will remain, which cannot be sorted out automatically or at working level and require a sound analysis and cross-functional decision making in the S&OP meeting. For example, an underutilized production plant could be better leveraged and sufficient raw materials could be available to produce more of product A, but the market appears to be saturated for this product at the current price point. To reach a feasible S&OP plan, promotional activities for product A and/or increasing material supply for product B would need to be investigated. If a company is using a tool to support its planning process, identifying the right issues to be escalated should be a rather routine activity at this point: The mismatches between demand and supply are (typically) automatically flagged based on the rule sets provided.
[FIGURE 2] Example of and S&OP issue tree
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Step 2: Define mitigation scenarios
To solve the identified issues, it is important to come up with potential solutions to close the gap between supply and demand: Can overtime be used in the preferred production plant? Is there an alternative plant that the volumes can be shifted to? Can the demands of a specific customer group be prioritized in production while delaying order fulfillment for some other customer groups? Can finished goods from other markets be rerouted? Can sales shape the remaining demand towards specific product groups?
Typically, there are too many scenarios to carefully consider, as it takes a great deal of time and effort to define and evaluate each scenario (unless supported by an autonomous planning system). Therefore, managers need to select the most feasible options for further analysis: What are the scenarios that have worked well in the past and could work particularly well in the current situation? Based on our observation, most companies rely on the expertise and experience of their planners to make these decisions. Only a very few companies track the success of an implemented decision through measuring business impact, and thus have solid data that they can use to create a shortlist of options.
So how to best create scenarios? We will focus here on supply-demand matching scenarios, considering an already agreed-upon consensus demand. Assuming demand exceeds currently planned supply, supply scenarios could be, for example, using additional labor (for instance by adding shifts), leveraging a contract manufacturer, pre-producing volumes and using inventories, or simply following the as-is scenario of currently planned supply, which would result in demands that couldn’t be met. These potential choices come at a cost and have a certain lead time until full operationalization—which should be taken into consideration.
The shortlist of scenarios should be selected based on the overall objective of the company. For example, do we want to optimize for service, for cost, for inventory, or for sustainability? To avoid “boiling the ocean,” one needs to align the parameters for evaluating the different scenarios upfront, closely linking them to the local incentive system. Misalignment can lead to execution not following the agreed plan. For example, a company may decide to select an option based on equipment utilization in order to optimize for capacity, in spite of the fact that the overarching target is to reduce inventories.
Step 3: Feed scenarios into the system
Many advanced planning systems offer the capability to evaluate the consequences of the selected scenarios. To have a truly automated scenario planning process, it is crucial that the solution uses a cost structure model based on up-to-date information. There can be a lot of fluctuation in data such as local materials cost, the conversion cost for internal production, contract manufacturer capacities, or freight rates. The system needs to reflect the correct levels to ensure an accurate evaluation of the scenarios. Finally, the number of scenarios must be limited so that they are easy to manage (both from an evaluation perspective and from an interpretation perspective after the evaluation has been done). Each scenario is kept as a separate instance and is evaluated and prepared for the S&OP discussion.
Even if a company does not have an advanced planning system, the (semi-)manual evaluation should follow this same general approach. The focus, however, should lie on estimating the impact of the selected scenario shortlist on a simplified cost structure. While overall cost and main drivers need to be understood, additional analysis of KPIs (such as asset capacity utilization, inventory, and on-time delivery to customers) should be conducted as well.
Step 4: Conduct system-based evaluation
In the past, evaluating scenarios has been a tedious process, as many planning systems could not perform the required analysis automatically and a lot of manual effort was required. This was particularly cumbersome when it came to evaluating the impact of complex drivers such as product lifecycle changes, promotional activities, or changes in the existing production shift model. Planners had to replan and optimize the manufacturing program based on available raw materials, production capacities, or labor constraints considering the myriad of interactions with other products. This meant a considerable effort for every additional scenario that had to be maintained and updated. There are also interdependencies between variables that have to be take into consideration. For example, if a scenario allowed for an increase in capacity beyond the limitations of the existing shift model, the scenario would have to reflect any labor cost increases, driven, for example, by weekend overtime which may negate the positive effects of the scenario.
To handle the scenario-evaluation process without having to undergo an unacceptable level of effort, planners oftentimes leveraged more simplified models at aggregated levels, which did not fully capture the real-world complexities. In addition, the cost or capacity data used was often outdated, resulting in frequent deviations from the original expectations.
Advanced planning systems often have the capability to evaluate scenarios directly in the tool. Accordingly, the evaluation takes place directly in the planning environment, considering all relevant interconnections as well as the master and transactional data available in the system. With this type of system in place, the evaluation of more complex scenarios can be handled more easily and with higher accuracy compared to older systems. Nonetheless, it is still important to thoroughly set up steps 1–3 to add true value.
The remaining workload for the planners is finally determined by the tool’s ability to remember and (re-)use preconfigured scenario alternatives: Are alternative shift models (and related cost structures) pre-populated and available for scenario evaluation? Can a capacity ramp-up at a contract manufacturer easily be modeled? However, there might still be inaccuracies. For example, the system may not be able to capture certain nonlinear impacts, or actual costs might differ from the standard cost. Nevertheless, the effort for the evaluation is oftentimes massively reduced.
Step 5: Conduct scoring
When it comes to the criteria used to evaluate scenarios, companies typically need to consider a variety of different, sometimes even competing, metrics, such as margins, costs, lead times, inventories, or service levels. (See Figure 3.) Unfortunately, in most cases, there is not a single dominant metric that is superior across all performance dimensions. An air freight option, for example, might ensure that the delivery of the required sales volumes is on time, but it might be very expensive, leading to lower margins. Or a contract manufacturing option might be less expensive but not provide the full volume needed. Or the option to produce at another production site might be cheaper but would result in late deliveries. Each scenario needs to be evaluated for these different performance metrics and risks need to be flagged. (In Figure 3, risks are indicated by a red circle and “watch outs” are marked with orange triangles.)
[FIGURE 3] Stylized example of an S&OP scenario evaluation
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In such cases where trade-off decisions are needed, disagreements over which scenario to prefer can erupt between the different stakeholders in the S&OP meeting. This typically happens because conflicting objectives are not well aligned or because quantitative metrics (such as margin or inventory impacts) need to be weighted against qualitative criteria (such as the strategic importance of customers or the reputational risks).
Modern planning systems help resolve or even mitigate such disagreements by offering the option to aggregate the (quantitative) performance outcomes across the different dimensions, for example, based on a scoring approach. For that, planners need to define the weights of the different performance metrics (as seen on the right of Figure 3). (This process of establishing how much to weight different performance metrics only needs to occur once. After that initial weighting, those weights can be used for all subsequent scenario evaluations.) Then the system automatically calculates the total score for the different options which can be taken into consideration during the decision-making process. This can shorten the discussions in the S&OP meeting. In advanced systems, thresholds can be defined based on which scenarios are automatically selected if one scenario obtains a much higher score than all alternatives. Thus, planners can focus their manual decision making on the most critical issues only.
To illustrate the benefits of scenario planning, we have selected three real-world examples, each from a different industry segment. The following examples illustrate that, while the levels of automation and tool maturity may vary, every organization can tap into the potential of a well-run S&OP process using scenario planning. When companies follow a clearly structured scenario development and evaluation approach, they can use the S&OP process to drive true decision-making, distinguishing themselves from competitors.
Huntsman: Running a decision-oriented planning process
The chemical company Huntsman has a Polyurethanes division that serves over 3,000 customers in more than 90 countries with over 30 production and formulation facilities across the regions. A few years back, the Polyurethanes division introduced a new integrated business planning (IBP) process as a significant evolution of their traditional S&OP process. The implementation of IBP involved fundamentally upgrading its decision-making to enable a customer-centric and margin-optimal approach, while continuing to use its existing APS.
The new IBP process is oriented around enabling agile and robust decision-making. Each IBP meeting is essentially focused on making decisions on few identified problem areas, for which concrete scenarios on how to act have been identified and evaluated. In the course of the monthly planning process, most demand-supply imbalances can be resolved by the operational teams. However, based on defined value thresholds and in cases of strategic importance, some issues are escalated to the IBP meetings. In order to enable team members to make decisions during the meetings, relevant scenarios on how to potentially deal with the issues are predefined. These typical alternative strategies are defined by the planning team in advance, based on the nature of the issue (for example, a regional supply shortage or a transportation bottleneck).
The scenarios are then evaluated along standardized criteria covering volume, margin, and inventory consequences as well as strategic fit, risk level, and legal obligations. (Figure 4 shows the standardized evaluation sheet.) To assess the options, the planning teams use a margin evaluation tool that was developed in-house.
[FIGURE 4] Example of a template for decision making in S&OP meeting
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A core improvement has been to refocus the IBP meetings to spend more than 80% of the time exclusively on discussing any issues with prepared options to assess and then making decisions. Pure data sharing has been reduced to a minimum, focused on a performance overview and discussion at the beginning of each meeting.
During the past years of continuous supply chain disruptions, Huntsmen took to running the process on a weekly basis so that the company could make decisions quickly, while still being guided by the sound decision basis provided by the IBP process. Overall, the Huntsman example demonstrates the impact that decision-focused processes and meetings can have even while continuing to operate in the existing system landscape.
Hilti: Leveraging scenario planning
Hilti is a Liechtenstein-based multinational corporation focused on developing, producing, and selling products for professional end users in the building and construction industry. Hilti has about 32,000 employees and serves more than 120 countries.
For its core business planning, Hilti is running a cross-functional S&OP process. A core element of the S&OP process is the use of scenarios for:
The entire process also incorporates a financial perspective, seamlessly translating volumes into value.
The process follows a standard playbook with clear rules about which potential issues can be decided by the operational planners vs. which need to be discussed in the respective demand or supply review meetings or in the actual S&OP meeting. Hilti also employs a set of standard scenarios to evaluate for common issue types, such as excess production capacity or lack of production capacity. (Scenarios for less common issues are created on more of an ad-hoc basis.) The scenarios are then assessed mostly based on cost (including manufacturing and logistics costs), inventory impact, and potential lost sales/service level consequences. The pre-evaluated scenarios are then presented at the S&OP meeting via standard templates and decisions are made in a cross-functional setup.
Hilti uses an advanced planning solution from Blue Yonder to support the process and enable cross-functional optimization of the integrated S&OP plan. Going forward, Hilti is planning to further automate the identification and evaluation of scenarios using the Blue Yonder solution, enabling a faster execution and response to best fulfill its customer demand.
Avon: Margin-optimized evaluation
One of the world’s largest cosmetics companies, Avon offers over 30,000 products directly to approximately 5 million sales representatives worldwide. With such a level of complexity, Avon adapted the S&OP process to enable cross-functional strategy deployment that balances commercial, operational, and financial decision-making.
As a business that seeks to attract consumers by providing “permanent newness,” Avon needs to evaluate demand scenarios against multiple decision criteria: ensuring representatives’ satisfaction, managing short product lifecycles, protecting inventory health, and delivering profit and loss (P&L) targets. In preparation for the S&OP meetings, the planning team uses the newly implemented o9 cognitive planning tool to perform concurrent analysis and simulations of plans across the products, representatives, and P&L dimensions. The tool flags the biggest gaps to targets and allows planners to select which gap-closing scenarios are best from a perspective of both the top and bottom line.
With the cognitive planning tool, all teams have access to the most up-to-date information and the latest scenarios. They can also easily share and capture assumptions and recommendations. Leadership teams can easily look up both the planned and actual KPIs in all dimensions (for example, operating margin, revenue, average revenue per representative, inventory, and service, to name just a few) in various levels of granularity between markets, products, and sales channels.
During the S&OP meetings, teams compare scenarios by looking at different dimensions concurrently. Decisions are made live by understanding the root causes of gaps and simulating trade-offs along all those dimensions. If new information arises, the teams can build different alternatives during the S&OP meetings, recalculate the impact, and then make an informed, balanced decision without the need to delay actions.
In the first year since implementation, sales patterns are still being analyzed by the tool, and the teams are still learning how to fully utilize the tool’s functionalities. But what will using this approach (combining process, tool, and people’s capabilities) eventually mean for a general manager? When a demand gap to target is detected, a set of activities to close this gap will be automatically evaluated and recommended. Based on options selected by the team, any shortage (capacity, packaging, or raw material) will trigger an automatic alert. Based on recommended alternative demand and supply options, the new scenarios can be compared against P&L, service, and inventory impact, leading to better trade-off decisions.
Our experience shows that S&OP best practices can be found not only across industries but also across all levels of digital maturity. You don’t need to wait until you have the most modern planning system to start implementing a well-structured process. Instead, it is important to create a solid foundation early on, building on the available capabilities and system infrastructure.
As with any other journey, building S&OP capabilities takes time, effort, and talent. But there is one first and foremost success factor to keep in mind: choosing the most relevant scenarios to be discussed in the S&OP meeting, in order to solve the most important demand-supply imbalances. Only asking the right questions leads to the best answers.
We have outlined what can be perceived as best practice today, so what is next in increasing S&OP maturity? Overall, we expect the manual effort involved in conducting S&OP processes (such as scenario preparation and insights aggregation) to continuously decrease with increasing adoption of system support. This will make parallel evaluation of multiple demand-supply scenarios even faster. For operations and planning staff, this means they will be able to put even more emphasis on asking the right questions, clearly defining and prioritizing the right S&OP options to be evaluated, and linking insights with business and risk perspectives.
But to get to this next stage, companies must build their capabilities and skills correctly. To avoid the risk of “pilot purgatory,” there is a clear need to develop digital talent early on. Our recently published 2022 pulse survey on supply chain risk indicates that contrary to strong digitization investments, hiring and reskilling of labor is still lagging behind. Only 8% of the respondents to our August 2022 survey say they have sufficient digital talent in-house. With supply chain becoming an executive priority over the past months and years, now is the right time to lay the foundation of tomorrow’s S&OP talents.
Author Acknowledgements: We would like to explicitly thank the following people for sharing their experiences and offering to have their story told in this article: Holger Tewes-McCoy (European Supply Chain Director at Huntsman Polyurethanes), Federico Scotti di Uccio (Head of S&OP and Global Process Management at Hilti Group), and Agnieszka Dyduch (Operations Strategy Director at Avon).}
1. Knut Alicke, Edward Baribell, Tacy Foster, Julien Mauhourat, and Vera Trautwein, “Taking the pulse of shifting supply chains,” McKinsey & Co. (August 26, 2022): https://www.mckinsey.com/capabilities/operations/our-insights/taking-the-pulse-of-shifting-supply-chains
Knut Alicke (firstname.lastname@example.org) is a partner at McKinsey & Company in its Supply Chain Management practice.
Katharina Hauck (email@example.com) is an engagement manager in McKinsey & Company’s Supply Chain Management practice.
Kai Hoberg (firstname.lastname@example.org) is a professor of supply chain and operations strategy at Kuehne Logistics University.
Jürgen Rachor (email@example.com) is a senior expert and associate partner at McKinsey & Company in its Supply Chain Management practice.
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