The problem was easy to describe and hard to see clearly. When organizations discuss merchandise planning, the conversation often focuses on forecast accuracy. Understandably, most retailers want to improve their ability to predict demand, reduce inventory risk, and respond more quickly to changing customer behavior. However, one of the observations from a recent retail planning transformation was that forecast accuracy was not always the primary challenge. In many areas of the business, planners already had access to sufficient data, robust planning tools, and detailed forecasts. The more significant challenge was determining where planners should spend their time.

As assortments grow and planning processes become more detailed, planning teams are increasingly asked to support a larger number of products, scenarios, and decisions. While modern platforms can generate forecasts at scale, the business must still manage the volume of decisions created by those forecasts. The real challenge was not the volume of information available to planners but identifying where their expertise could have the greatest impact.

Observation #1: More detail does not always lead to better planning

One of the assumptions frequently encountered in planning initiatives is that additional detail will naturally lead to better decisions. If planners can forecast at a lower level, review more products, or access more information, the expectation is that planning outcomes will improve. In practice, the relationship is often more complicated.

During this transformation, planners were responsible for a large assortment of products with varying levels of demand stability, business importance, and planning risk. Some products required active management, while others behaved predictably and changed very little from one planning cycle to the next. Despite these differences, many products received a similar level of review. As the planning team evaluated how planners were spending their time, an important pattern emerged: a significant amount of effort was being dedicated to maintaining plans that were already behaving largely as expected.

This observation does not suggest that detailed planning is unnecessary. Rather, it highlights the importance of understanding where additional detail creates value and where it simply creates additional work.

The lesson learned was that granularity and sophistication are not the same thing. Planning processes can become highly detailed while simultaneously becoming more difficult to operate, maintain and update. The ultimate goal should not be to maximize the amount of information available to planners. Instead, the goal should be to ensure that planner attention is directed toward decisions where intervention is likely to improve the outcome.

Observation #2: Not every product deserves the same amount of planning effort

A second observation emerged when the team began examining how products were being managed throughout the planning cycle. Many planning processes evolve with good intentions. New reports are introduced to address business questions, additional review steps are added to reduce risk, and exception reports expand to capture more potential issues. Over time, these changes can create a process that requires increasing levels of maintainability.

What starts as exception management can gradually become a review process for a substantial portion of the assortment. In this case, the team found that planners were often reviewing products that exhibited predictable demand patterns and limited variation from previous expectations. While individual reviews were generally reasonable, the cumulative effort required to manage large numbers of products reduced the time available for more strategic activities.

One of the most valuable discussions during the project centered around a simple question: Should every product receive the same amount of planning attention? For many organizations, the answer is likely no. Some products are strategically important, some exhibit volatile demand patterns, and others represent significant inventory or financial risk. These products often warrant active planner involvement because business context and judgment can materially influence the outcome. Others follow relatively predictable patterns and may benefit from a more standardized planning approach.

The lesson learned was not that planners should be removed from the process. Rather, the lesson was that planner expertise creates the most value when applied selectively. Organizations should consider whether their planning processes help planners focus on the decisions that matter most or whether they inadvertently encourage equal attention across the entire assortment.

Observation #3: The most valuable planning decision is sometimes not to intervene

As the project progressed, the team began reframing how success was defined. Historically, planning effort was often measured by activity. More reviews, more overrides, and more adjustments could create the appearance of greater control over the planning process. However, activity alone does not necessarily improve planning outcomes.

One of the goals of the transformation was to establish planning approaches that could manage routine decisions consistently while helping planners identify situations that genuinely required intervention. This led to a broader discussion about the difference between managing transactions and managing exceptions. In many planning organizations, planners are asked to make a large number of incremental adjustments. Individually, these changes may appear small, but collectively they can consume a significant portion of planner capacity.

As the team evaluated planning behavior, one of the most important capabilities proved to be helping planners distinguish between situations that required action and situations where the existing plan remained appropriate. While this may sound simple, it represented a meaningful shift in mindset because intervention was no longer viewed as the default response. Instead, planners were encouraged to consider whether intervention would materially improve the outcome. In many cases, allowing established planning logic to continue operating as intended was the most appropriate decision.

The lesson learned was that successful exception management is not simply about highlighting problems. It is about helping planners decide where not to spend their time.

What this means for planning leaders

Although every organization is different, these observations are becoming increasingly relevant as retailers modernize planning platforms and explore new AI-enabled capabilities. Much of the current discussion within the industry focuses on what new technology can help planning teams accomplish. Those conversations are important, but they can sometimes overlook a more fundamental question: How many planning decisions actually require human attention?

Organizations that cannot answer that question may find themselves accelerating complexity rather than reducing it. Before introducing additional automation, AI, or forecasting sophistication, planning leaders should evaluate whether their existing processes help teams focus on the decisions that create the greatest business value. In our experience, the most effective planning organizations are not necessarily the ones reviewing the most forecasts. They are the ones that have developed a clear understanding of where planner judgment genuinely matters.

Conclusion

One of the most important takeaways from this retail transformation was that planning complexity deserves far more attention than it typically receives. The challenge was never generating forecasts. Modern planning platforms are highly capable of doing that at scale. The challenge was determining how planners could effectively manage the volume of decisions created by those forecasts.

By focusing on where planners could create the most value, the organization was able to rethink how planning effort was allocated across the assortment. Rather than asking planners to spend equal time on every product, the planning process began emphasizing meaningful exceptions, repeatable planning patterns, and selective intervention.

For planning leaders facing similar challenges, the lesson may be worth considering: the future of planning is not simply creating more forecasts. It is creating planning processes that help organizations make better decisions about which forecasts deserve attention in the first place.

This article focused primarily on the business challenge of planning complexity and the observations that led the organization to rethink how planner time was being used. In a follow-up article, I will explore some of the approaches that supported this shift, including forecasting curves, layered planning structures, IBM Planning Analytics implementation, AI-assisted development, and exception-based workflows.

If this topic is of interest to you

If this topic is of interest to you, I encourage you to join me at IBM TechXchange 2026 for my session, “Curves Do the Work — Planners Handle Exceptions,” where I’ll discuss how these concepts were applied during a retail planning transformation and share some of the lessons learned along the way.