Weekly planting, 2025–2029
42 bays, one white cultivar, revenue at the harvest week's expected price. The model adds a contract harvest floor, prices extra weekly capacity, and tests the Women's-Day window under price uncertainty.
The four-year outlook is the point of planning ahead rather than repeating last year: planting is committed months before prices are known, so the plan's value lies in what can be weighed in advance. The same horizon feeds the price-uncertainty analysis below — risks are evaluated before they arrive, not read off last season's results — and every new year of data makes those choices finer-tuned.
The plan — kappen planted per week
The price of fixed contracts
| Scenario | Revenue 2025–2029 | Cost of the commitment |
|---|
Flexibility to respond to the market
The Women's-Day price peak is certain — how high it goes is not
Planting is committed about ten weeks before Women's Day, but the price is only known at harvest — the plan cannot wait for it. So every candidate plan is tested against three futures: prices come in strong (50% above the estimate), as estimated, or weak (40% below). The tabs below compare how each plan holds up.
How this plan holds up in each future
What this plan changes on the ground
All plans side by side
| Plan | Strong prices (30% likely) | As estimated (45%) | Weak prices (25%) | Average outcome | If prices disappoint | Revenue in WD weeks |
|---|
Optimization for the plan, price scenarios for the risk
The plan comes from linear programming — a technique that, in effect, tries every allowed combination of weekly planting choices and returns the one with the highest revenue. "Allowed" means it respects the physical limits: 42 bays of space, at most 6 kappen planted per week (crew pace), and at least 2 harvested per week (contract commitments). Revenue counts at the harvest week's price. The Women's-Day analysis adds stochastic modeling: the same search is run against the three price futures at once, so the chosen plan is judged not only on its best guess but on how it holds up when prices swing — that is how risk gets a number instead of a feeling.
Prices here are estimates and the model currently maximizes revenue. Each new data stream completes more of the risk landscape: realized weekly auction prices turn the three futures into measured likelihoods, and cost and energy data turn revenue into profit — with the footprint line joining when the energy stream lands (see Calibrate).