Why S&OP fails in practice: the three causes and how to address them
In our S&OP projects, I have seen the same pattern for years. The process has been introduced, meetings are held monthly, and the planning tool is in place. Yet decisions are still driven by gut feeling. According to an analysis by Alvarez & Marsal (2024), around 70 per cent of companies have a formal S&OP process. However, only around a quarter implement it consistently and in full.
It is not the concept that fails, but its implementation. S&OP fails at three structural levels: process design, the data foundation and governance. These three factors reinforce one another. Many companies then try to break the cycle with even more meetings or even more data. This leads nowhere.
Conversely, this means that those who tackle all three levels together will turn the same S&OP into a management tool that actually works. This article highlights the weaknesses that render S&OP ineffective and identifies three immediate measures at the process, data and governance levels that can be implemented within 30 to 90 days. You do not need to change your system. You need decisions to be made in the right places.
Three interrelated problem areas
Three structural weaknesses explain why so many S&OP programmes fail to deliver on their intended control objectives: inadequate process design, a flawed data foundation and a lack of governance.
The figures are clear. According to the Alvarez & Marsal analysis from May 2024, around 70 per cent of companies operate a formal S&OP process, but only around 25 per cent do so consistently and across the entire organisation. Added to this is a second finding: 72 per cent of the companies surveyed have only introduced their S&OP in the past five years.
Planning maturity and S&OP adoption are two different things. Adoption is a date. The process has been approved, the dates are in the calendar, and the roles are set out in the organisation chart. Maturity, on the other hand, is a state of being, and this only develops over the course of planning cycles. Sales treats its forecast as a compulsory exercise until it realises that production is actually manufacturing according to it and that an overly high figure will later come back to haunt it. This learning process requires repetition, usually a year or more. Anyone who introduced their S&OP eighteen months ago therefore has, for the time being, a process. They do not yet have a system for managing it.
These three levels rarely occur in isolation. Weak governance allows data deficiencies to persist because no one is responsible for rectifying them. Inadequate data undermines the process because every decision is made on an unreliable basis. And a poorly structured process ensures that governance decisions never find their way into day-to-day planning.
A systematic literature review by IMT Mines Albi identifies precisely these dimensions as the most common causes of S&OP errors: process, data and people – or governance. Addressing just one level treats a symptom. Addressing all three changes the control logic.
A common misdiagnosis, which I regularly hear in initial discussions, is: “We lack the methodology.” Companies react to weak S&OP by introducing IBP or increasing the frequency of meetings. Both merely shift the problem. Let’s go through the three causes one by one.
Process issues in S&OP: Where the control loop breaks down
The most common mistake: S&OP meetings are run as status updates. Participants report on what has happened. No decisions are made.
There is a lack of defined inputs, expected outputs and binding decision-making rules. If an S&OP meeting begins without first clarifying which questions are to be answered and who has the final say, the outcome is predictable: an hour of discussion, no binding decision. Following the CSCMP EDGE Conference 2025, *Supply Chain Management Review* reported that ownership and accountability are the main causes of S&OP failures, not technology or planning models.
Closely related to this is the lack of exception management. A good S&OP operates on the principle of exceptions: anything that is going according to plan is not discussed. Anything that deviates is escalated and a decision is made. In many companies, however, everything ends up on the table because there is no system to filter out the exceptions, prioritise them and assign them to the appropriate decision-maker. Meetings go on for too long, and critical decisions get lost in the crowd.
The third process flaw concerns the rhythm. Quarterly cycles are unmanageable in a market with short response times. The minimum standard is monthly cycles with weekly brief updates on critical exceptions. Anyone who extends the cycle to save effort is trading manageability for convenience. Not a good trade-off.
A functioning planning process requires that process design and decision-making architecture are clarified before the first meeting, not during it.
Closely related to this is the lack of exception management. A good S&OP operates on the principle of exceptions: anything that is going according to plan is not discussed. Anything that deviates is escalated and a decision is made. In many companies, however, everything ends up on the table because there is no system to filter out the exceptions, prioritise them and assign them to the appropriate decision-maker. Meetings go on for too long, and critical decisions get lost in the crowd.
The third process flaw concerns the rhythm. Quarterly cycles are unmanageable in a market with short response times. The minimum standard is monthly cycles with weekly brief updates on critical exceptions. Anyone who extends the cycle to save effort is trading manageability for convenience. Not a good trade-off.
A functioning planning process requires that process design and decision-making architecture are clarified before the first meeting, not during it.
The lack of plausibility checks is the fourth structural problem. They prevent obviously incorrect planning proposals from slipping through unnoticed. If a product that has not been manufactured for three months is suddenly forecast to have a demand of 10,000 units, this should be flagged. Without automated plausibility rules, this usually goes unnoticed.
This is where demand sensing regularly comes into play. This refers to a short-term forecasting method: it processes real-time signals from day-to-day operations – such as sales, order intake or stock movements – and continuously updates the forecast. The traditional statistical forecast, by contrast, calculates figures on a monthly basis using historical data. Demand sensing does not replace it; rather, it adds a short-term corrective layer on top.
A level-headed approach is advisable when it comes to expectations. These methods can measurably improve forecasting accuracy: according to a study by Alvarez & Marsal, improvements ranged between 11 and 21 per cent, depending on the product group. Recent research also demonstrates how AI-based demand sensing models, in controlled studies, significantly improve forecast accuracy – measured as MAPE – compared with naive baselines. MAPE (Mean Absolute Percentage Error) is the mean absolute percentage forecast error, the most commonly used metric for forecast accuracy.
However, the benefits only materialise with short replenishment lead times, such as those typical in the FMCG sector. This is where many projects go wrong. I put it to my clients like this: a better forecast is only of use to you if you can still react to it. If the replenishment lead time is several weeks or months, the order will have been placed long before the short-term signal even arrives. Anyone introducing demand sensing in the technical trade, for capital goods or for long-run products is buying the wrong solution.
The MAPE itself also warrants caution. Here at Abels & Kemmner, we do not recommend it as the primary metric for forecast accuracy. In the case of sporadic demand and zero values in the time series, it is systematically distorted. Anyone wishing to systematically improve forecast quality needs metrics that can handle zero values.
The fundamental problem remains: data quality trumps data volume. Feeding more data into a poorly configured planning system simply produces the wrong results more quickly.
Governance shortcomings: Who decides when nobody decides?
The most common governance shortcoming in S&OP: there is a lack of binding decision-making rules, and there is no clear executive sponsor.
Estimates based on real-world experience, including those from Ventana Research, suggest that 70 to 80 per cent of companies have not embedded their S&OP at executive level. Consequently, decisions either never reach the right desk at all, or arrive far too late. What I often hear in initial discussions is: “Senior management has been informed.” Being informed is not the same as a decision having been made. Alvarez & Marsal cite a lack of executive commitment as the most common cause of stagnating S&OP processes.
Underlying this is a design flaw: misaligned incentives. Sales focuses on turnover, production on capacity utilisation, and procurement on unit costs. No one within the system has an organisational mandate to jointly improve overall costs and delivery readiness. When these different logics clash, power – rather than planning – prevails when in doubt. This is the real conflict of objectives in S&OP. It is not resolved by better figures, but by clearly defined decision-making authority.
Governance without KPI alignment is like a thermostat without a heating system. It measures the deviation but does not correct anything. A functioning S&OP governance system requires three elements:
a designated S&OP owner with decision-making authority in the event of conflicting objectives,
KPIs that are bindingly linked to decisions and not merely measured,
an escalation pathway that determines which issues are escalated to the next level of management and when.
The Oliver Wight maturity model for IBP shows that companies which consistently build up governance and executive ownership achieve average annualised ROI figures of 63 per cent from their S&OP and IBP programmes. Control capability is the lever that makes investments in processes and data effective in the first place.
Proactive supply chain management requires that decision-making authority is actually exercised in every meeting, rather than merely existing on paper.
What really helps: three interventions over 30 to 90 days
Targeted interventions at all three levels are effective. A peer-reviewed case study involving a medium-sized automotive supplier demonstrates the potential benefits. In the first seven months following the introduction of the S&OP process, average monthly inventory costs were 18.42 per cent lower. At the same time, stock turnover rose from 2.63 to 5.25 and the on-time delivery rate from 95 to 98 per cent. This is a single case study, not a body of research. However, the direction is consistent with what I see in my own projects. The three transformation principles from Alvarez & Marsal also focus on process, people and data.
Process (Weeks 1 to 4): Restructure the S&OP meetings, with clear inputs, defined outputs and written minutes of decisions. Before each meeting, it is established which scenarios will be discussed, what decision is expected and who has the final say. This shortens the discussion and makes the results binding.
Data (Weeks 2 to 8): Introduce the ‘Top 50 SKU’ rule. In most product ranges, 50 to 100 items account for the majority of sales and capacity variance. Those who set up automated plausibility checks for these key items first will see results quickly. For product groups with short replenishment lead times, modern demand-sensing approaches also deliver measurable improvements in forecasting accuracy.
Governance (Weeks 1 to 2): Appoint an S&OP owner. This is a single decision, involving no budget and no system change. The owner has the final say in the event of conflicting objectives between sales, production and procurement. There is also a simple escalation rule: anything that cannot be decided at the S&OP meeting is referred to senior management within 48 hours.
When I start working with a new client, I almost always begin with governance. It costs no money, it requires just a signature, and it delivers results the quickest. Three interventions, one for each level of the problem, with visible results within 30 to 90 days. Stable operations follow after 6 to 12 months of consistent application. Anyone wishing to use data-driven planning models on a long-term basis needs this stability as a foundation.
S&OP or IBP: When is it worth taking the next step?
When does traditional S&OP no longer suffice? The answer depends less on the size of the company than on the maturity of its planning processes.
IBP (Integrated Business Planning) extends S&OP to include financial integration and strategic scenario planning. The transition requires significantly greater data accuracy and a revised governance structure. According to a McKinsey analysis, mature IBP practitioners achieve an EBITDA improvement of 1 to 2 percentage points compared with pure S&OP operations. The Oliver Wight maturity model for IBP describes revenue growth of up to 15 per cent in mature implementations. This growth does not align with our experience in the SME sector.
Even with lower benefits, IBP can still be worthwhile. However, two prerequisites must be met: a stable data foundation and effective governance within the existing S&OP process. Replacing an unstable S&OP process with IBP simply shifts the problem to a more complex system.
The transition from S&OP to IBP is a substantial one. If IBP goes beyond broad financial indicators, very detailed financial and production data must be available and continuously maintained: margin data at product level, rolling contribution margin calculations, capacity cost plans, and investment scenarios. Many planning departments that operate a robust S&OP process have neither the capacity nor the specialist financial staff to manage this.
That is why we at Abels & Kemmner recommend that responsibility for IBP should lie within the CFO’s remit – that is, in Controlling or Financial Planning – rather than with operational S&OP management. Whoever manages day-to-day S&OP should not also be responsible for the IBP transformation. There is a lack of capacity, and the professional perspective is different.
A sequential approach has proven effective: first stabilise the S&OP process, clean up the data, and establish governance. Once reliable figures are coming out of S&OP month after month, the groundwork for IBP is in place. The IBP pilot then starts in parallel with the ongoing S&OP, under the leadership of Finance, with a clearly defined scope.
APS systems such as DISKOVER support the operational S&OP level with regard to stock levels, forecast quality and planning parameters. IBP, however, requires financial planning that goes beyond operational planning systems.
Anyone wishing to develop an integrated planning approach should start with a stable S&OP and set up IBP as a separate programme under the leadership of Finance as soon as the foundation is solid.
Where to start next month
S&OP rarely fails because of the software. I have yet to come across a company that has become capable of making decisions simply by introducing a new planning tool. What is missing are clear decision-making processes, up-to-date figures and someone who has the final say in the event of conflicts. You can change this within your own organisation, without needing budget approval or a project proposal.
Focus on the next planning cycle. Before the meeting, write down the two decisions that need to be made there, and at the end, ensure the minutes record who is doing what by when. Decide who will make the call in the event of a conflict between delivery readiness and capacity utilisation, and state that person’s name in front of everyone involved. And take a close look at your planning template: how old is the oldest figure in it?
That’s all you need to get started. Companies whose S&OP runs smoothly rarely have a better process on paper. They have the process they actually put into practice, and they started using it at some point rather than waiting for the next system roll-out. Your next cycle starts in four weeks. Make the most of it.
FAQ – Frequently Asked Questions
What is S&OP?
S&OP (Sales & Operations Planning) is a monthly management process. It reconciles the sales forecasts produced by the sales department with the capacity and materials planning carried out by production and procurement, and combines the two into a binding plan. The process operates at monthly and product group levels, not at item or daily levels. The outcome is a decision, not a report.
Why Does S&OP So Often Fail in German Companies?
S&OP typically fails for three structural reasons: a lack of executive sponsorship, poor data quality, and unclear decision-making rules within the planning process. It is rarely caused by a single issue. More often, deficiencies in processes, data, and governance reinforce one another. According to an Alvarez & Marsal analysis (2024), while 70% of companies have a formal S&OP process in place, only about 25% execute it consistently.
How Can S&OP Be Successfully Implemented in Practice?
S&OP succeeds when process, data, and governance are addressed together—not sequentially and not in isolation. In practice, this means: an S&OP meeting with clearly defined inputs, expected outputs, and documented decision minutes; automated data validation checks, initially focused on the 50 to 100 SKUs with the greatest impact on revenue and capacity variability; and a designated S&OP owner with the authority to resolve cross-functional trade-offs. These three measures do not require a system replacement and can deliver measurable results within 30 to 90 days.
Which Roles Are Essential for an Effective S&OP Process?
An effective S&OP process requires at least five clearly defined roles: the S&OP Owner (overall accountability and decision-making authority), the Demand Manager (demand planning), the Supply Manager (capacity and supply planning), the Finance Business Partner (financial integration), and the Executive Sponsor (strategic direction and executive alignment). Without an Executive Sponsor, S&OP remains an operational tool rather than a strategic management process.
How Long Does It Take to Implement an S&OP Process?
The first measurable improvements can typically be achieved within 30 to 60 days by establishing a clear meeting structure and well-defined decision-making rules. A stable and reliable S&OP process is usually in place after 6 to 12 months of consistent execution. The fastest path to success is to start with governance while implementing process improvements and data enhancements in parallel over the same eight-week period.
What Is Demand Sensing?
When Does Demand Sensing Make Sense—and When Doesn't It?
Demand sensing delivers the greatest value in environments with short replenishment lead times, such as the FMCG sector, where companies can still respond to short-term demand signals. When replenishment lead times extend to several weeks or months, the approach becomes largely ineffective because purchase orders have already been placed before the signal arrives. A more accurate forecast only creates value if it can still influence a business decision. For this reason, demand sensing is generally not the right investment for technical distribution, capital goods, or products with long lead times. According to an Alvarez & Marsal study, forecast accuracy can improve by 11% to 21% for suitable product categories.
What Is the Difference Between S&OP and IBP?
S&OP aligns demand and supply planning at the operational level. Integrated Business Planning (IBP) extends this process by incorporating financial integration and strategic scenario planning. IBP requires significantly higher data quality and a more mature governance model, with the finance organization—typically led by the CFO—playing a central leadership role. Transitioning to IBP only makes sense once the foundational S&OP process is stable, consistent, and operating effectively.
