Taking the risk out of critical planning decisions

Scenario

A beverage producer makes wine across a large portfolio of brands. Every year the producer has to decide how much wine to make and how many grapes to buy to meet expected demand. The call is made in a monthly planning meeting, where planners, winemakers, and buyers consider the stock on hand, the demand forecast, how long each wine needs to age, and how it is blended, then set production volumes and release dates.

In fast-moving industries, many planning mistakes can be fixed within a week or month. In this industry, it is more complicated. Once the grapes go into the vat, the decision is locked in for years. So if you get the volumes wrong, you either have wine you cannot sell or you run short on wine you cannot make more of until the next batch.

What is worse, there is currently an oversupply of wine across the wine industry. U.S. wine stock has climbed to around $24 billion, up from about $18 billion in 2021. For every $100 of wine sold, roughly $165 sits unsold in warehouses (Vinetur, 2025). France has spent about €200 million destroying surplus wine. This means that if you get the forecast and planning wrong, then not only do you have a surplus, in a shrinking industry you would have a lot of waste.

Challenge

For such an important decision, one that is difficult to rectify once made, the process needs to be automatic, reliable, and trustworthy. In this case, it was manual, which made it brittle. 

The plan was built by hand. Every month, a planner spent a full weekend pulling data from several systems: demand forecasts, past sales, bottled stock, and bulk wine held in tanks. Each one came in a different format and unit, so the planner had to spend the weekend cleaning and converting the data before any planning could even start.

The planning logic sat inside complex Excel files that only a few people really understood. If you lose one person, the company loses critical knowledge about its planning process. Small errors then slipped into the data, causing downstream issues. And there was no way to quickly test "what if" scenarios while discussing the plans.

Solution

The model that used to live in a few spreadsheets now lives in a planning and decision system. The know-how is built in, the data is clean and checked, and all calculations run in a few seconds. Planners can test options all day and commit only once they have thoroughly tested the decision, instead of trusting numbers someone prepared days earlier. One of the biggest benefits is that they do this without drastically changing their existing workflow, which supported adoption from day one.

Where this applies

This is not only a problem in the wine industry. Any business that runs a big decision on spreadsheets that break easily, fed by outside data and understood by only a few people, has similar weak spots. This shows up in domains like manufacturing, production, retail, and logistics. If an important plan or decision process in your business works in a similar way, it can be operationalized to remove risk and improve outcomes.