Excel models look precise, but in volatile markets they hide assumptions, break under change, and give false confidence to investors.
Excel has been the backbone of project finance for decades. It is familiar, flexible, and powerful in the right hands. Almost every solar deal still starts and ends with an Excel model. That alone is not a problem. The problem is how Excel is being used in markets that no longer behave in predictable ways.
In stable markets, Excel works reasonably well. Assumptions do not change often. Payment behavior is consistent. Currency movements stay within narrow ranges. Models are updated occasionally, reviewed carefully, and then archived. Reality does not drift far from what was modeled.
In many emerging solar markets, this is not how things work.
Cash flows change often. Payment delays stretch and shorten. Currencies depreciate steadily. Regulations shift. Tariffs are revised. Offtaker behavior evolves under pressure. Excel models struggle to keep up with this level of movement, not because Excel is weak, but because it was never designed for continuous, real world uncertainty.
One core issue is assumption fragility. Most Excel models rely on a small number of key assumptions that sit quietly in input sheets. These assumptions are treated as fixed until the next formal update. In reality, many of them start breaking within months of financial close. Payment timing assumptions become outdated. FX assumptions drift. Operating costs rise faster than expected. The model still runs, but it no longer reflects reality.
Another issue is version chaos. In active projects, multiple versions of the same model often circulate at the same time. Small changes are made. New sensitivities are added. Old formulas remain hidden. Over time, no one is fully sure which version reflects the current truth. Decisions are then made using models that look correct but are no longer aligned with actual project behavior.
Excel also struggles with transparency. Complex models hide logic inside nested formulas and long calculation chains. When something breaks, it is difficult to trace why. Reviewers focus on outputs instead of understanding how those outputs are produced. This creates false confidence. Numbers feel precise because they are neatly formatted, not because they are robust.
There is also a behavioral problem. Excel encourages single point forecasts. One base case. One downside case. One upside case. Real markets do not move in neat scenarios. They drift, compound, and surprise. Excel can show scenarios, but it does not naturally force users to think in ranges, probabilities, or evolving risk. As a result, uncertainty is often underrepresented.
Some investors argue that Excel is not the issue, poor modeling is. That is partly true. Skilled modelers can do impressive work in Excel. But this argument ignores scale and repetition. As portfolios grow, as markets become more volatile, and as decisions need to be made faster, manual spreadsheet based systems become bottlenecks. Errors increase. Updates lag. Insight arrives late.
The cost of this failure is not academic. Projects approved on outdated assumptions struggle. Risks that could have been managed early appear suddenly. Trust erodes when models repeatedly need to be revised after reality intervenes. Excel does not cause these outcomes, but it enables them by giving an illusion of control.
This does not mean Excel should disappear. It remains useful for structuring, learning, and explanation. But relying on static spreadsheets as the primary decision engine in volatile solar markets is increasingly dangerous. Finance needs tools that can handle changing data, track assumptions over time, and reflect how projects actually behave once they are operating.
Solar markets are evolving faster than the tools used to analyze them. When the tool cannot keep up with the market, decisions suffer.
The question is no longer whether Excel can model solar projects. It clearly can. The question is whether Excel can keep pace with markets where uncertainty is constant and timing matters more than totals. In many emerging markets, the answer is increasingly no.