The demand consensus meeting is one of the most important steps in sales and operations planning (S&OP). After all, its output is a demand plan that serves as a critical input for all other S&OP process meetings. (For an in-depth explanation of consensus, check out the article I published in the ASCM blog a few years back.)
So, if the consensus meeting is so vital to the process, choosing to talk about the right items during consensus must be equally essential. But how do you decide what to bring to the table? Which items deserve attention, and which can be left to the mathematical muses to figure out? After considering these questions, I finally hit on the answer: exceptions.
When demand planning, we often set up a series of data-based exception reports that highlight singular problems — perhaps items with a high forecast error, ones that reveal no actual sales over three reporting periods, or product families that reflect trend mismatches between the prior year and the forward view. Then, we bring a dozen or so of these exceptions to the consensus meeting for discussion.
While these mathematical exceptions are heavily relied on, we also use judgmental filters that allow us to apply relevance, instinct and gut feeling to the demand plan. We consider whether a product is new or strategically important; if it has leadership attention because of its channel, customer or competitive activity; if the volume — measured either in dollars or unit volume — is worthy of special consideration or exclusion.
Following is a list of exceptions and filters that I use for facilitating consensus. Not every one will work for every business; some will intersect each other. But using these strategies, my demand planning teams have been able to improve the consensus focus by pointing the discussion toward what is significant and meaningful. They've identified a customer who planned to drop us, a volume decline caused by a change in shelf-level placement, fat-fingered budgets, bad allocation logic and shifts between channels or to a competitor — often before sales and marketing have even noticed the change. Here they are:
1. Relevance screen: Is the product on the long tail of the revenue stream or already planned for discontinuation? If yes, then manage these products to their likely demise and exclude them from consensus intervention. No one wants to discuss a $15,000/year stock-keeping unit (SKU). Establishing relevance filters — such as, “Let’s only discuss items with annual volume above $100,000 or with variance greater than 25%” — improves the conversation.
2. Newness magnifying glass: Consensus should include a discussion of all new product forecasts, regardless of volume expectations, from approval through prelaunch and postlaunch. The objective is to evaluate new, unplanned insights, such as product rejection or an add from a major customer. And during postlaunch, it’s wise to track actuals for both shipments and consumption because both were likely factors in the rationale for launch approval. Leadership always focuses on new products; you should too.
3. Level/trend/seasonality review: If product data reveals a notable change in trend, a step change up or down in demand, or a shifting of seasonality, then you need to discuss it.
4. Gap-to-budget test: Any item that varies more than 10% from quarterly budget expectations calls for examination. Gaps are often due to poor budgeting, poor demand planning or some combination of both. A budget is an expectation of top-line and bottom-line performance, and S&OP requires that any significant budget gaps are explained (and preferably closed).
5. Size matters scan: A significant volume shift or error affecting a large product family, customer or item always merits discussion. If Walmart’s business is off 10% and Walmart represents 50% of your company’s total volume, you need to take a deep dive. Similarly, when I was at Snapple, we would react strongly to any shift in the tea product family, especially those changes affecting lemon tea SKUs, because these were the largest volume drivers inside the portfolio. Consensus should always give plenty of attention to the workhorses.
6. Oops, I did it again recheck: I always revisit any items that were raised for discussion during the prior month’s consensus meeting. I do this for two reasons: to confirm whether the prior exceptions have been resolved, and because any metrics that are out of control for two months back-to-back merit another review.
7. Data can be messy acknowledgment: Is a product or a customer registering zero sales for the past couple of months? Is there an imbalance of volume shipping out of one warehouse versus another? What about those pesky, undefined product families in the hierarchy? Any of these scenarios can lead to either bad forecasts or execution, and they may indicate other problems. Data issues such as these are fair game for discussion at consensus.
8. Buzzworthy platforms audit: Review any platform or sales channel that might be subject to internal or external buzz, such as a new marketplace contender, a media shift by a competitor or a change in product awareness driven by a viral reel. Buzz alone (especially external buzz) can sometimes trigger change in volume; when that happens, a forecast adjustment is typically needed.
9. Strategic importance probe: I recall once being puzzled while working as a consultant for an alcoholic drink company because the planners obsessed over the forecast and prebookings for the same item every consensus cycle, even though it sold only 10,000 units per year. I came to realize it was a super-high-end Scotch that sold for $2,500 a bottle with a 90% profit margin — and also a bellwether that helped foretell the fates of some of the other higher-end brands. Some products are more important than their volumes may suggest.
10. Boy, did we screw up admission: Of course — and probably most importantly — items with the greatest forecast error should always be discussed during consensus.
