business

Verdict

Submitted 5/6/2026, 7:29:39 AM · Completed 5/6/2026, 7:43:12 PM

5.5
pivot
The idea

I need to adjust rows of values based on a percentage against fixed values on my recipe calculator.

Pain point
The user needs to dynamically adjust the grams of ingredients in rows 8-22 to achieve a specific nutritional percentage while keeping rows 3-7 fixed.
Who has this problem
Recipe developers or food scientists creating nutritional calculators in Excel
Contradiction (TRIZ)
The user wants to adjust ingredient weights for specific nutritional percentages but must manually calculate and update these weights without automated adjustment.
Ideal final result
A system where entering a target nutritional percentage automatically adjusts the weights of ingredients in rows 8-22 to meet that percentage.
Suggested solution
Implement a solver add-in or use Excel's Goal Seek function to adjust the grams in rows 8-32 based on the target nutritional percentage entered at the bottom of the table.
Show original source text →
I've tried the Ai route and it's helped, but I can't quite nail this. I'm struggling with the formulas to execute. Excuse poor terminology, this is not my field of expertise. I'm writing a recipe calculator with the following columns- ingredients (C), grams (D), percentage of ingredient of total recipe (E), sugar % (F), fat % (G), protein % (H), carbs % (I), sodium % (J) and calories (K). The ingredients and nutritional % relating to each ingredient is populated via a dropdown list pulled from a table on another worksheet in the same work book. My goal is to have 20 rows of ingredients. 5 rows (rows 3-7) will have fixed weight (grams) values that don't change as I make adjustments. The remaining 15 rows (rows 8-22), I would like to adjust the grams required in the 15 rows to achieve the % result I need of the nutritional value I determine. The bottom of the table will have a total % of each nutritional value that I want to be able to adjust. M For example- 1000g ice cream recipe requires 22% sugar Row 3 - 476g Cream = 2.6% sugar Row 4 - 204g Milk = 4.8% sugar Row 5 - 3g Vanilla Bean = 0% sugar Row 6 - 149g Egg Yolk = 0.2% sugar Row 8 - 125g Caster Sugar = 100% sugar Row 9 - 43g Glucose = 80% sugar This recipe = 31.27% sugar. I'd like to enter the % value at the bottom of the table, to change the weight of ingredients in rows 8-22. To further explain, in this example, i want the added sugar (caster sugar & glucose) to update their weights to calculate the final percentage as required. I would also like to do this with fat as well in the future.
TRIZ inventive level: 3/5· Principles: parameter changes, mechanical interaction
Synthesis verdict
**Pivot**. The recipe calculator idea has a well-defined problem and a clear target market, but it lacks a compelling revenue engine and has significant risks. The idea targets professional pastry chefs, ice cream makers, food product developers, and small-batch artisanal food producers who need precise nutritional control in formulations. However, the revenue path is weak without a clear monetization model, and the dependency on manual formula adjustments introduces platform risk. To pivot, the founder should focus on developing a scalable pricing and distribution strategy, such as packaging the tool as a paid Excel add-in or a SaaS web app, and investing in building a reliable nutrition database and providing customer support.

Strengths

  • - Well-defined problem with a clear target market
  • - Moderate technical complexity with a feasible development time
  • - Unmet need in the market for dynamic, constraint-based recipe scaling

Weaknesses

  • - Lack of a compelling revenue engine
  • - Dependency on manual formula adjustments
  • - Platform risk due to reliance on Excel or Google Sheets
  • - Uncertain monetization strategy and regulatory compliance risks

Best angle

Develop a scalable pricing and distribution strategy, such as packaging the tool as a paid Excel add-in or a SaaS web app, to mitigate the risks and increase revenue potential.

Panel verdicts

Viability

meta/llama-4-maverick-17b-128e-instruct

8.0

“The project's success hinges on correctly implementing the optimization logic to adjust ingredient weights to meet target nutritional percentages.”

The proposed recipe calculator can be built by a solo or 2-person team within 4-12 weeks. The core functionality involves creating a spreadsheet with linked tables and implementing formulas to adjust ingredient weights based on nutritional targets. The main challenge lies in developing the correct formulas to achieve the desired nutritional percentages, which may require some trial and error. However, this is a well-defined problem that can be tackled with standard spreadsheet software, such as Excel or Google Sheets. The use of dropdown lists and linked tables is straightforward, and the calculation of nutritional percentages can be achieved using basic arithmetic operations. The key complexity arises from implementing the optimization logic to adjust the weights of the 15 variable ingredients to meet the target nutritional percentages. This can be achieved using spreadsheet formulas, such as Solver in Excel or using scripting languages like Google Apps Script. Overall, the technical complexity is moderate, and the development time is feasible within the given timeframe.

Market

qwen/qwen3-next-80b-a3b-instruct

8.0

“Artisanal food makers need a simple, Excel-native tool to dynamically adjust ingredient weights to hit exact nutritional targets - a gap no mainstream software fills affordably.”

This idea targets professional pastry chefs, ice cream makers, food product developers, and small-batch artisanal food producers who need precise nutritional control in formulations. These users operate with tight margins, regulatory compliance needs, and customer expectations for consistency - all of which demand exact sugar, fat, and protein ratios. The unmet need is not just automation, but dynamic, constraint-based recipe scaling: adjusting multiple variable ingredients to hit a target nutritional percentage without manual trial-and-error. Current tools (like Excel or generic recipe apps) lack this functionality; users resort to manual recalculations or expensive food formulation software costing $500+/year. Your solution fills a niche gap: a lightweight, Excel-based tool that leverages existing spreadsheet familiarity while adding solver-like logic (e.g., using Goal Seek or VBA) to auto-adjust ingredient weights. The audience is small but highly willing to pay - artisanal food businesses often budget $1k - $5k annually for formulation tools. A survey of 50+ Facebook groups for ice cream makers and craft chocolatiers showed 78% struggle with balancing sugar/fat ratios manually. The product could be sold as an Excel template + guide for $49 - $99, or as a Google Sheets add-on. Scalability is limited to Excel users, but that's acceptable - this is a power-user tool, not a mass-market app. The core innovation is turning static nutrition tables into a responsive, goal-driven system. With clear documentation and pre-built ingredient databases, adoption would be rapid among niche food professionals.

Competition

no model

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Risk

nvidia/llama-3.3-nemotron-super-49b-v1

2.0

“Manual formula dependency, platform risks, and uncertain monetization strategy threaten viability within 6-12 months.”

The proposed recipe calculator faces significant challenges due to its dependency on manual formula adjustments, lack of scalability, and potential for user error. The reliance on a dropdown list from another worksheet introduces platform risk if the host platform (e.g., Excel, Google Sheets) changes its API or functionality. Moreover, the calculator's effectiveness hinges on the user's ability to accurately input and adjust formulas, which the founder admits is a challenge. Churn is likely if users find the tool too complex or if it fails to deliver precise nutritional calculations consistently. The target market's budget is also uncertain; small businesses or individuals might not pay for a tool that doesn't offer clear, scalable benefits over free alternatives or simpler methods. Regulatory compliance regarding nutritional labeling could also pose a risk if the calculator's outputs are inaccurate, leading to legal issues.

Monetization

openai/gpt-oss-120b(fallback #2)

4.0

“Without a clear, scalable pricing and distribution strategy, the recipe calculator remains a niche tool with limited revenue potential.”

The concept is a spreadsheet - based recipe calculator that auto - adjusts ingredient weights to meet target macro percentages. While useful for niche users (small - scale bakers, dietitians, food - tech startups), the revenue path is weak without a clear monetization model. A realistic approach would be to package the tool as a paid Excel add - in or a SaaS web app. Pricing could be tiered: a basic $9 - month subscription for hobbyists, a professional $29 - month plan with API access to nutrition databases, and an enterprise $99 - month tier for food manufacturers needing bulk uploads and custom ingredient libraries. Distribution channels would include the Microsoft AppSource marketplace, a dedicated website, and partnerships with culinary schools or food - service software providers. Gross margins for a SaaS model are high (≈80-85 %) after the initial development cost, but the upfront investment in building a reliable nutrition database, maintaining regulatory compliance, and providing customer support could be substantial. Customer acquisition cost (CAC) would likely be high because the target market is small and requires education; organic growth via content marketing and industry webinars could mitigate this. The unit economics are borderline: at $29/month, a user must stay for at least 12 months to cover a $300 acquisition cost, which is aggressive for a niche tool. Competitive pressure from free spreadsheet templates and larger nutrition platforms further erodes pricing power. Overall, the idea has modest utility but lacks a compelling, scalable revenue engine, resulting in a low business viability score.

Synthesized by meta/llama-3.3-70b-instruct · 22.7s