From the 1978 UNIDO template to AI: why a long study is no longer a sign of quality, and what an investor’s decision really needs before committing.
The way feasibility studies are written is changing worldwide. Here are five ideas researchers and practitioners raise today, and how we apply them in the investment decision check at Al Tamkeen.
A decades-old template
The most cited reference for industrial feasibility study structure is a guide published by UNIDO in 1978. Many firms still copy its sections verbatim. Weight isn't always a sign of quality — it can be an inherited habit.
We start from the investor's question, not a template.
Untested assumptions
One of the most influential management books, The Lean Startup, attacked the "detailed plan, then capital, then build" pattern because it rests on assumptions never validated before commitment.
We test the assumption against market indicators before you commit, and we say what still needs verifying.
The rigid document vs. the living framework
Multiple sources describe traditional plans as "long and rigid, outdated the moment circumstances change." That's why the Business Model Canvas emerged, condensing the model into one editable page.
We build a decision file that can be updated whenever the numbers or the location change.
Whoever pays the bill wants the answer to be "yes"
Extensive academic studies on major projects (the most notable being the work of Bent Flyvbjerg and colleagues) have found that costs are generally underestimated and benefits are overestimated in the vast majority of cases, and that the party with a vested interest in approving the project tends to be optimistic. The takeaway: the figures you are comfortable with are not necessarily accurate.
Our sources are dated and disclosed, and we show what supports the decision and what threatens it, even when the result is not what you hoped for.
AI: speed, with a risk of fabrication
AI use in market analysis is accelerating, and many warn it can produce confident conclusions with no basis in the data — a fatal risk in a financial decision.
Every indicator in the decision file traces back to a dated source. Analysis tools help with sorting; the advisor, not the tool, reviews the result and frames the hypotheses.
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