Sales & Operations Planning and Advanced Planning Systems bring clear value to manufacturing companies. They help structure decisions, improve visibility, and support better alignment across functions.
Still, the same frustration persists in the field. Despite years of investment in planning processes and tools, decision-making remains slow, trade-offs stay unclear, and discussions often end in compromise rather than clarity. And that is because planning processes still follow assumptions that were developed decades ago. And our planning systems still support those same assumptions.
If we want planning to better support business decisions, it is time to challenge some of the traditional logic.
The foundations of S&OP and APS go back almost 40 years. Since then, technology has improved a lot. Planning tools are faster, cloud-based, and can process larger volumes of data.
But when you look at the core logic, many APS systems still do more or less what they did years ago. The technology stack has changed, but the planning approach often has not. That creates a gridlock. Companies keep asking for traditional planning functionality, and vendors keep building around that demand. As a result, planning teams often get better tools for old ways of working, instead of new ways of making decisions.
A traditional S&OP process often works like this: a statistical forecast is created. Sales reviews and adjusts that forecast, then the business tries to agree on one consensus demand number. On paper, that sounds like alignment. In practice, it often becomes a negotiation.
Sales may push for higher volumes because if demand is not in the plan, the business may never produce it and never sell it. Supply chain may push back because if the business produces too much and demand does not materialize, inventory risk goes up. Finance may be more conservative because it prefers to underpromise and overdeliver.
So what happens? Teams settle on a number somewhere in the middle. The issue is that this consensus number hides the real discussion. Different functions do not look at demand in the same way because they do not carry the same risks.
Sales is naturally more optimistic or opportunistic. Supply chain wants to be realistic because it is measured on both service and inventory. Finance tends to be more cautious because its commitments are judged differently. A single consensus demand number ignores these differences instead of making them visible.
A stronger approach is to separate demand into layers. First, there is the base demand, this is the stable demand that can be statistically forecasted. This part should be built through analytics and should remain untouched by commercial negotiation.
Then there are opportunities an these are potential upsides or downsides that sit on top of the base demand. For example, a possible customer win, a tender, a promotion, or a risk of losing volume. These opportunities should be captured separately, with both volume and probability. That creates a clearer demand picture.
Instead of turning uncertainty into one compromise number, you make uncertainty explicit. For example:
That means expected demand may be 120, but the business still understands the uncertainty behind it. This is far more useful than forcing one consensus number too early in the process.
Sales teams should not have to work across multiple systems to support planning. The process needs to be practical. If they already manage opportunities in CRM, then that is where those opportunities should be maintained. Planning should connect to that reality, not fight it.
This matters because planning success is not only about algorithms. It is also about adoption. If the process is too heavy, people will not use it in the right way.
Once base demand and opportunities are separated, supply planning becomes more powerful. At that point, the question is no longer: what is our one agreed demand number? The better question is: how do we want to balance sales opportunity with inventory risk?
That is where scenario-based planning should become standard. Rather than running ad hoc analyses every time, companies should define a small set of standard supply scenarios. A simple way to think about this is through planning modes:
This type of scenario logic makes planning easier to understand and easier to use in management discussions.
One of the biggest mindset shifts is this: the final planning choice should not sit with one function alone. Choosing whether to plan 100 or 150 is not just a sales, supply chain or finance decision. It is a business decision.
That is why planning should not aim for consensus at the start of the process. It should aim for clarity at the start, and consensus at the end. Start with base demand and opportunities. Run clear scenarios. Then let the business decide which trade-off it wants to make. That is a very different role for S&OP. It becomes less about negotiation and more about decision support.
Another gap in traditional planning is the strong focus on volume only. If companies want planning to steer the business, every important planning decision should show financial impact as well. Planners should be able to understand what a scenario means for revenue, margin, inventory, and cash.
This does not mean every plan has to be optimized by a financial solver. But it does mean financial visibility should be built into the planning process itself. Too often, supply chain builds an operational plan and finance later translates it into value. That creates duplicate work, delays, and a risk of misalignment. Planning should not create a parallel world where operations and finance each calculate a different answer.
S&OP and APS have an important role to play. But to get more value from them, companies need to move beyond outdated planning habits. That means:
For leaders in manufacturing, this is where the real next step sits. Not in more complexity, but in a better planning logic. At Solventure, we help manufacturing companies rethink planning processes, improve S&OP maturity, and get more value from APS solutions.