The 6-Criteria Solution Framework: How to Choose the Right Fix for $50K–$100K Operators
The systematic scoring method that reveals which solution fits your constraints best so you stop wasting months on wrong fixes.
The Executive Summary
Founders, consultants, and operators at $40K–$90K/month keep wasting 90-day cycles on “good-sounding” fixes; a 6-criteria solution framework scores every option in 3 hours so the right move wins before you execute.
Who this is for: Mid-five to low-six-figure founders, consultants, and agencies who’ve correctly diagnosed problems like flat $35K revenue or margin compression but keep choosing solutions that burn 6–12 weeks with little to show.
The Wrong-Fix Problem: First-instinct, availability-bias solutions send you into 12-week detours that can destroy $150K–$200K in upside or trigger $168K in avoidable damage when the “obvious” move (like cutting team or building lead gen) doesn’t fit your constraints.
What you’ll learn: The 6-Criteria Solution Framework (Effectiveness, Feasibility, Reversibility, Speed, Cost, Leverage), the scoring matrix, context-weighting rules, and full examples where a 3-hour evaluation flips the winner from popular choice to optimal move.
What changes if you apply it: You replace 20-minute gut picks with 3-hour structured design, avoid low-scoring traps like premature hires or full productization, and repeatedly choose solutions that unlock moves like $35K to $42K or $95K with fewer wasted cycles.
Time to implement: Spend 1–2 hours generating 5–10 options, 60–90 minutes scoring them across six criteria, then 30–60 minutes turning the highest-scoring solution into an implementation plan you can execute within 2–4 weeks.
Written by Nour Boustani for mid-five to low-six-figure founders and operators who want compounding wins without burning 90 days on fixes that never fit their real constraints.
You don’t need more ideas — you need a way to pick the right one. Upgrade to premium and stop spending 90 days on the wrong fix.
How to Choose the Right Solution Systematically
Start with a simple scoring matrix. Create a table with your solution options as rows and the six criteria as columns. Score each option 1–10 on effectiveness (does it solve the problem?), feasibility (can you execute it?), reversibility (can you undo it?), speed (how fast?), cost (what’s required?), and leverage (multiple benefits?). Sum the scores, let the highest total win, and trade 3–4 hours of evaluation for months of avoided wrong turns.
Most business failures aren’t from missing the problem - they’re from solving it wrong.
Revenue stuck at $35,000? You’ve diagnosed the problem correctly. Now you’re choosing between raising prices, hiring salespeople, building lead generation, productizing services, or adding an upsell tier. Pick wrong, waste 90 days and $15,000. Pick right, unlock $20,000 monthly growth.
Team member overwhelmed? Problem identified. Should you hire another person, redistribute workload, automate tasks, reduce client count, train for efficiency, or set better boundaries? First instinct says hire. Strategic analysis might reveal that redistribution solves it in 3 days with zero cost, while hiring takes 8 weeks and $50,000 annually.
Here’s what picking wrong solutions costs: one operator diagnosed margin compression correctly (problem clear: costs rising faster than revenue). The solution seemed obvious - cut the team to reduce costs. Spent 4 weeks on layoffs and restructuring. Revenue dropped 28% because the team was doing revenue-generating work, not overhead. The problem got worse. Six months to recover. Total damage: $168,000 in lost revenue plus legal costs.
Strategic solution design would’ve revealed: raising prices scores 72 on combined criteria, cutting team scores 34. Price increase takes 2 weeks, costs nothing, fixes margin without touching capacity. Cutting team takes 4 weeks, creates $8,000 legal costs, reduces delivery capacity 40%, triggers client churn cascade.
Same problem. Two solutions. One adds $180,000 annually. One loses $200,000 annually. The difference? Three hours of systematic evaluation versus twenty minutes of gut reaction.
The math: gut decisions succeed roughly 40% of the time (slightly better than random because you have domain knowledge). Systematic evaluation succeeds 75-85% of the time because you’re scoring solutions against actual criteria that matter for your context.
You’re not failing because you’re bad at solving problems. You’re failing because you’re implementing the first solution that sounds right without evaluating whether it’s optimal for your situation.
Wrong solutions implemented efficiently still produce zero results. Right solutions implemented messily still move the business forward.
Why First-Instinct Solutions Fail Predictably
You’re not picking bad solutions randomly. You’re picking them systematically - and that’s why the pattern repeats.
This happens because humans default to availability bias. The solution you thought of first feels right because it’s familiar, not because it’s optimal. Your brain retrieved it quickly because you’ve seen it before, not because it matches your specific context.
Here’s the trap: familiar solutions feel safer than unfamiliar ones, even when unfamiliar solutions score higher on actual evaluation criteria. You’ve seen other operators hire salespeople, so hiring feels like “the right move” even when redistribution would solve the problem faster and cheaper.
The Bottleneck Audit reveals what’s broken in your business. Solution design reveals which fix actually works for your constraint type, timeline, and resources.
Here’s what changes when you design solutions systematically instead of reactively.
Before systematic design: Problem identified. The first solution sounds good. Implement. Realize 6 weeks later, it’s not working. Try a different solution. Waste another 8 weeks. Eventually, you find something that works. Total time: 4-6 months.
After systematic design: Problem identified. Generate 6 potential solutions. Evaluate each against 6 criteria in 3 hours. Choose an optimal solution for the context. Implement. Works as designed. Total time: 2-4 weeks.
The math compounds. If you’re choosing first-instinct solutions, you’re wasting 70-80% of implementation time on approaches that don’t fit your context. If you’re designing systematically, you’re implementing optimal solutions that match your constraints.
One more pattern worth noting: operators at $80,000 monthly, diagnosing “need more leads” and immediately building a lead generation system. Systematic evaluation would reveal the close rate is 19% (should be 35-40%). Lead generation scores 42 on combined criteria. Fixing the sales process scores 72. One takes 12 weeks and $8,000. Other takes 2 weeks and $400. Both could work. Only one fits the constraint.
The Repeatable Sale provides the sales system framework. Solution design reveals when the sales process is the right intervention versus when something else scores higher.
You’ve probably experienced this: chose a solution that seemed right, worked hard implementing it, and realized months later it was the wrong approach for your situation. That’s what happens when selection stays reactive. Hard work applied to a suboptimal solution equals wasted effort.
The difference between reactive and strategic operators isn’t intelligence or work ethic - it’s evaluation methodology. Strategic operators spend 3 hours designing solutions to save 90 days implementing wrong ones.
Here’s the framework that prevents that.
The Solution Design Framework: Six Evaluation Criteria
Solution design isn’t one question - it’s six scoring criteria that reveal which option fits your context best.
The Framework Structure:
SOLUTION OPTIONS (5-10 generated)
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CRITERION 1: EFFECTIVENESS (Does this solve it?) - Score 1-10
CRITERION 2: FEASIBILITY (Can we execute?) - Score 1-10
CRITERION 3: REVERSIBILITY (Can we undo?) - Score 1-10
CRITERION 4: SPEED (How fast?) - Score 1-10
CRITERION 5: COST (What's required?) - Score 1-10
CRITERION 6: LEVERAGE (Multiple benefits?) - Score 1-10
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TOTAL SCORE (Sum or weighted)
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OPTIMAL SOLUTION (Highest score for context)
Criterion 1 - Effectiveness: Does this actually solve the problem?
Criterion 2 - Feasibility: Can we actually execute this with current capability?
Criterion 3 - Reversibility: Can we undo this if we’re wrong?
Criterion 4 - Speed: How fast can we implement and see results?
Criterion 5 - Cost: What does this require in money, time, and opportunity?
Criterion 6 - Leverage: Does this solve multiple problems simultaneously?
Most operators evaluate on one or two criteria (usually effectiveness and cost). Strategic operators evaluate all six systematically because context determines which solution works best.
Here’s what each criterion reveals and why it matters.
Criterion 1 - Effectiveness (Does This Actually Solve the Problem?)
The question: Will this fix the root cause or just treat symptoms?
What you’re scoring: The degree to which this solution addresses the actual problem versus making you feel busy.
Scoring guide:
1-3: Treats symptom, doesn’t fix root cause
4-6: Partially addresses the problem, full solution requires additional fixes
7-9: Solves problem substantially, minor issues may persist
10: Completely resolves the root cause, the problem won’t recur
Critical distinction: Effectiveness measures problem resolution, not implementation difficulty.
Example scoring:
Problem: Revenue flat at $42,000 for 10 weeks
Solution options with effectiveness scores:
Hire salesperson: 7/10 (might increase pipeline, but doesn’t fix conversion issue)
Build email nurture sequence: 9/10 (directly addresses follow-up gap killing conversions)
Reduce pricing: 4/10 (might close more, but doesn’t fix systematic issue)
Fire low performers: 3/10 (treats symptom, not cause)
The email sequence scores highest on effectiveness because it fixes the actual problem (prospects going cold due to no systematic follow-up) rather than compensating fora broken system.
Time investment: 30 minutes to score effectiveness across all solution options.
Criterion 2 - Feasibility (Can We Actually Execute This?)
The question: Do we have the capability, resources, and conditions needed to implement this?
What you’re scoring: Realistic assessment of whether you can actually do this given current constraints.
Scoring guide:
1-3: Missing critical capability, resources, or prerequisites - very difficult
4-6: Have some pieces, missing others - challenging but possible
7-9: Have most of what’s needed - straightforward implementation
10: Can execute immediately with existing resources - trivial
Critical distinction: Feasibility isn’t about money alone. It’s about total capability to execute, including knowledge, time, team, and systems.
Example scoring:
Problem: Team member is overwhelmed with the workload
Solution options with feasibility scores:
Hire another team member: 6/10 (have budget but takes 6-8 weeks to recruit, onboard)
Redistribute workload: 9/10 (can start today, requires 4 hours of mapping work)
Automate repetitive tasks: 7/10 (know which tasks, need time to set up automation)
Reduce client count: 8/10 (can execute but creates revenue risk)
Redistribution scores highest on feasibility because you can start immediately with existing resources, versus hiring, which requires extensive time and process.
Time investment: 20 minutes to assess capability gaps across options.
Criterion 3 - Reversibility (Can We Undo This If Wrong?)
The question: Is this permanent, or can we reverse course if results don’t match expectations?
What you’re scoring: Exit cost and flexibility if the solution doesn’t work as planned.
Scoring guide:
1-3: Permanent decision, high exit cost, can’t be reversed easily
4-6: Can reverse but with significant cost or effort
7-9: Mostly reversible, low exit cost
10: Completely reversible, zero exit cost
Critical distinction: Higher reversibility = lower risk. Prefer reversible solutions when uncertainty is high.
Example scoring:
Problem: Should productize services or stay custom?
Solution options with reversibility scores:
Full productization: 2/10 (permanent model shift, can’t easily go back)
Stay fully custom: 10/10 (maintain status quo, always reversible)
Hybrid model: 6/10 (can shift back but requires client communication)
Gradual transition: 9/10 (test with subset, easy to pause or reverse)
Gradual transition scores highest on reversibility because you can test the approach with 5 clients while keeping the existing model for others. If it fails, you simply stop - no permanent damage.
Time investment: 15 minutes to map exit costs and reversibility paths.
Criterion 4 - Speed (How Fast Can We Implement and See Results?)
The question: Time to implement plus time to validate results?
What you’re scoring: Combined speed of execution and feedback loop.
Scoring guide:
1-3: Months to implement, months to see results - very slow
4-6: Weeks to implement, weeks to see results - moderate pace
7-9: Days to implement, days to see results - fast
10: Hours to implement, immediate results - instant
Critical distinction: Speed includes both implementation time AND time-to-feedback. Fast implementation with slow feedback still scores medium.
Example scoring:
Problem: Margin compressing despite revenue growth
Solution options with speed scores:
Raise prices 20%: 10/10 (announce this week, see impact next billing cycle)
Automate delivery: 4/10 (6 weeks to build, 8 weeks to measure margin impact)
Renegotiate vendor contracts: 6/10 (4 weeks of negotiation, immediate impact)
Productize to reduce labor: 3/10 (12 weeks to productize, 8 weeks to validate margin)
Price increase scores highest on speed because you can implement in days and see results within one billing cycle, versus automation requiring months of development.
Time investment: 10 minutes to estimate implementation timeline and feedback loop.
Criterion 5 - Cost (What Does This Require?)
The question: Total resource investment, including money, time, and opportunity cost?
What you’re scoring: Complete cost picture, not just dollar amount.
Scoring guide:
1-3: Extremely expensive in money, time, or opportunity - high cost
4-6: Moderate investment required - medium cost
7-9: Low investment required - cheap
10: Near-zero cost - essentially free
Critical distinction: Cost includes financial cost, time cost, and opportunity cost (what you’re NOT doing while doing this).
Example scoring:
Problem: Client churn is accelerating
Solution options with cost scores:
Hire customer success manager: 3/10 ($60,000 annually + 8 weeks to hire)
Build quarterly check-in system: 9/10 (8 hours to design, 2 hours monthly to maintain)
Improve onboarding experience: 7/10 (20 hours upfront, minimal ongoing cost)
Add surprise bonus deliverables: 5/10 (low financial cost but high time cost, monthly)
Quarterly check-in scores highest on cost efficiency because it requires minimal investment upfront and minimal ongoing time versus hiring, adding $60,000+ annually.
Time investment: 15 minutes to calculate the total cost, including hidden costs.
Criterion 6 - Leverage (Does This Solve Multiple Problems?)
The question: Does this intervention create compounding benefits beyond the primary problem?
What you’re scoring: Breadth of impact and secondary benefits.
Scoring guide:
1-3: Single-purpose solution, solves only the stated problem
4-6: Solves primary problem plus 1-2 minor benefits
7-9: Solves primary problem plus creates multiple secondary benefits
10: Solves primary problem and unlocks chain of downstream improvements
Critical distinction: Leverage solutions improve multiple areas simultaneously. Single-purpose solutions fix one thing.
Example scoring:
Problem: Founder working 60 hours weekly despite $95,000 revenue
Solution options with leverage scores:
Hire executive assistant: 6/10 (frees founder time but doesn’t build systems)
Build delegation map: 9/10 (frees time + documents processes + trains team + scales business)
Reduce client count: 3/10 (frees time but reduces revenue, single benefit)
Implement project management system: 7/10 (coordinates team + improves efficiency + creates visibility)
Delegation map scores highest on leverage because it simultaneously frees founder time, documents tribal knowledge, trains team for independence, and creates scalable business systems, versus other solutions providing a single benefit.
Time investment: 20 minutes to map secondary and tertiary benefits.
The Solution Design Process: From Problem to Implementation
Now that you understand the six criteria, here’s how to use them systematically.
Step 1: Generate Options (1-2 hours)
Goal: Create 5-10 potential solutions without judging quality yet.
Process:
Set a timer for 45 minutes
Brainstorm every possible solution, obvious and unconventional
Include “do nothing” as an option (sometimes the best choice)
Don’t evaluate yet - divergent thinking only
Get to at least 5 options minimum, ideally 7-10
Output: List of 5-10 solution options
Example:
Problem: Revenue stuck at $35,000 monthly for 12 weeks
Generated solutions:
Raise prices 30%
Hire salesperson
Build a lead generation system
Productize services
Add a upsell tier
Improve sales process
Do nothing (optimize current operations)
Partner for referrals
Reduce delivery time to serve more clients
Fire low-converting leads, focus on high-intent
Critical: Generate first, evaluate second. Don’t kill options during brainstorming, or you’ll miss non-obvious solutions.
Step 2: Evaluate Against Criteria (2 hours)
Goal: Score each solution on all 6 criteria objectively.
Process:
Create scoring matrix (solutions as rows, criteria as columns)
Usea spreadsheet tool like Airtable, Notion, or simple Google Sheets
Score each solution 1-10 on each criterion
Use data where available, not just gut feel
Be honest - don’t inflate scores for the preferred solution
Calculate total score (simple sum gives equal weight to all criteria)
Output: Completed scoring matrix with totals
Example:
Problem: Revenue stuck at $35,000
Interpretation: Raising prices scores 53 (highest) - most effective, fastest, most feasible, essentially free. Hiring a salesperson scores 31 (lowest) - expensive, slow, hard to reverse.
Critical: Scoring reveals non-obvious winners. Upsell tier scores higher than productization, despite productization seeming more strategic.
Step 3: Identify Optimal Solution (30 minutes)
Goal: Choose a solution that fits your specific context best.
Process:
Review the highest-scoring solution
Check if context requires weighting criteria differently
Validate choice matches your constraints
Consider combining the top 2-3 solutions if complementary
Output: Selected solution with implementation plan
Context weighting examples:
Normal conditions: Equal weight all criteria (simple sum works)
Crisis mode: Weight Speed 3x (need results immediately)
Experimental: Weight Reversibility 2x (testing unproven approach)
Resource constrained: Weight Cost 3x (cash flow limited)
Example:
Problem: Revenue stuck at $35,000
Standard scoring: Raise prices wins (score 53)
If the founder is risk-averse: Weight Reversibility 2x - Upsell tier might win (reversibility 9 vs 8)
If cash flow crisis: Weight Speed 3x - Raise prices still wins (speed 10 dominates)
Critical: The highest score usually indicates an optimal solution. Context weighting only matters when the top 2-3 solutions are close.
Step 4: Design Implementation (2 hours)
Goal: Turn selected solution into an executable action plan.
Process:
Map timeline (what happens when) - use Miro or FigJam for a visual timeline
Identify resources needed (tools, people, budget)
Define success metrics (how to measure if working)
Plan contingencies (what if it doesn’t work as expected)
Output: Complete implementation plan with timeline and metrics
Example:
Problem: Revenue stuck at $35,000. Solution: Raise prices 30% (from an average of $4,800 to $6,240)
Implementation plan:
Week 1:
Research competitor pricing (validate $6,240 is market-appropriate)
Analyze client segments (identify price-sensitive vs value-focused)
Design two-tier structure (standard $5,600, premium $7,200)
Week 2:
Draft communication to existing clients (grandfather 60 days, then $5,600)
Update website and sales materials to $6,240 for new clients
Train sales on new pricing and value communication
Week 3:
Launch new pricing publicly
Communicate with existing clients
Monitor response and objections
Week 4-8:
Track metrics: close rate, churn rate, revenue impact
Expected: 20% churn, 50% revenue increase = net +20% revenue ($35,000 to $42,000)
Success metrics:
Revenue: $35,000 to $42,000+ within 60 days (20% churn expected)
Close rate: Maintains 30%+ (validates pricing is market-appropriate)
Churn: Under 25% of existing clients
Contingencies:
If churn exceeds 30%: Offer transition pricing at $5,200 to retain marginal clients
If the close rate drops below 25%: Value communication needs work, not a pricing issue
If no one takes the premium: Adjust the premium offering or positioning
Step 5: Execute and Validate (Ongoing)
Goal: Implement the solution and validate it’s working as designed.
Process:
Implement according to the timeline
Track metrics weekly
Compare actual results to expected results
Iterate based on data (don’t abandon prematurely)
Document learnings for next solution design cycle
Output: Results validation and capability improvement
Example:
Problem: Revenue stuck at $35,000. Solution: Raise prices 30%
Execution tracking (8 weeks):
Week 2: New pricing live, existing clients notified
Week 4: 3 existing clients churned (12%), 2 new clients at $6,240
Week 6: 2 more existing churned (total 20%), 5 new clients at a higher price
Week 8: Revenue $35,000 to $41,400 (+18%)
Validation:
Expected churn: 20% (Actual: 18%) - better than target
Expected revenue: $42,000+ (Actual: $41,400) - close to target
Expected close rate: 30%+ (Actual: 32%) - validated
Solution worked as designed
Learning: Price increase succeeded. Two-tier structure unnecessary - market accepted full price. The premium tier can be added later as a separate offer.
Real Solution Design: Three Complete Examples
Here’s how the framework works across different problem types.
Example 1: Revenue Flat at $35,000
Context: Consultant stuck at $35,000 monthly for 12 weeks after growing consistently for 8 months. Pipeline healthy. Diagnosed problem: not enough perceived value to justify current prices, losing deals to cheaper alternatives.
Generated Solutions:
Raise prices 30%
Hire a salesperson to improve the close rate
Build lead generation for more volume
Productize services for easier delivery
Add a upsell tier for additional revenue
Do nothing, optimize current operations
Evaluation Matrix:
Analysis:
Raising prices scores 53 - highest total. Why?
Effectiveness: 9/10 - directly addresses the value perception issue
Feasibility: 9/10 - can implement this week with existing resources
Reversibility: 8/10 - can adjust if market rejects
Speed: 10/10 - change pricing, see results next billing cycle
Cost: 10/10 - zero financial cost, minimal time investment
Leverage: 7/10 - improves revenue + filters for better clients + increases perceived value
Hiring salesperson scores 31 - lowest total. Why?
Feasibility: 5/10 - takes 6-8 weeks to recruit, train
Speed: 3/10 - slow to implement, slow to see results
Cost: 4/10 - $50,000+ annually plus management overhead
Optimal Solution: Raise prices 30% (score 53)
Implementation: Two-week price increase protocol. Expect 20% existing client churn, 50% revenue increase from new pricing = net $35,000 to $42,000 monthly (+20%).
Result: Implemented price increase. Actual churn 18%. Revenue $35,000 to $41,400 in 8 weeks (+18.3%). Solution worked as designed. Time invested in evaluation: 3 hours. Time saved by avoiding wrong solutions: 6-8 weeks.
Example 2: Team Member Overwhelmed
Context: Key team member working 60 hours weekly, quality declining, burnout imminent. Diagnosed problem: workload exceeds capacity for one person.
Generated Solutions:
Hire another team member
Redistribute workload across the existing team
Automate repetitive tasks
Reduce client count to a manageable level
Train for efficiency improvements
Set better boundaries around working hours
Evaluation Matrix:
Analysis:
Redistribute workload scores 50 - highest total. Why?
Feasibility: 9/10 - can start today with the existing team
Reversibility: 9/10 - easy to rebalance if it doesn’t work
Speed: 9/10 - one week to audit and rebalance
Cost: 10/10 - zero financial cost, 8 hours to implement
Hiring scores 27 - lowest total. Why?
Reversibility: 3/10 - permanent hire, difficult to reverse
Speed: 2/10 - 6-8 weeks to recruit, onboard
Cost: 3/10 - $50,000 annually plus training time
Optimal Solution: Redistribute workload (score 50)
Secondary Solution: If redistribution is insufficient after 2 weeks, implement automation (score 43).
Implementation: One-week workload audit. Identified 25 hours weekly redistributable to other team members with capacity. Redistributed over 3 days.
Result: Overwhelmed team member dropped from 60 to 38 hours weekly. Quality recovered. Crisis averted. No hiring needed. Total cost: $0. Total time: 8 hours across one week.
Example 3: Productize vs Stay Custom
Context: Agency at $110,000 monthly revenue, fully custom delivery. Margin compressing (45% to 32% over 8 months). Team stressed. Considering productization to restore margin and reduce complexity.
Generated Solutions:
Full productization (packages only)
Stay fully custom
Hybrid model (packages + custom tier)
Gradual transition (test packages with subset)
Franchise delivery model
Do nothing, accept current margins
Evaluation Matrix:
Analysis:
Gradual transition scores 48 - highest total. Why?
Feasibility: 9/10 - can test with 5 clients while keeping custom for others
Reversibility: 9/10 - easy to stop if it doesn’t work
Speed: 7/10 - 4 weeks to design package, 8 weeks to validate
Cost: 9/10 - minimal investment, reuses existing processes
Full productization scores 35 despite being “most strategic.” Why?
Reversibility: 2/10 - permanent model shift, can’t easily undo
Speed: 3/10 - 12+ weeks to transition entire client base
Feasibility: 6/10 - requires convincing existing clients to switch
Optimal Solution: Gradual transition (score 48)
Implementation: Eight-week pilot program. Create a productized package for 5 new clients. Keep custom delivery for the existing 24 clients. Test market response, margin impact, and delivery efficiency.
Result: Launched productized tier at $8,400 monthly (vs custom at $6,200 average). Five clients signed in 8 weeks. Margin on productized: 52% (vs custom 32%). Validated model works. Expanded productized to 40% of new client acquisition over the next 6 months. The hybrid model emerged as a permanent strategy.
Why Systematic Design Beats First Instinct
Here’s what changes when you design solutions instead of picking them reactively:
You avoid expensive mistakes before making them.
Systematic evaluation reveals low-scoring solutions before you waste months implementing them. One operator scored “hire COO” at 28 versus “build founder delegation system” at 67. Saved $120,000 annually and 6 months of painful discovery.
Solutions match your actual constraints.
First instinct doesn’t account for feasibility, reversibility, or cost. Systematic design ensures the chosen solution fits your timeline, resources, and risk tolerance.
Implementation speed increases dramatically.
When you choose an optimal solution for the context, execution goes smoother. No mid-stream pivots. No, “this isn’t working, try something else.” Higher confidence = faster execution.
Results become predictable.
Scoring reveals expected outcomes. When the price increase scores 53, and you implement it, you know roughly what to expect. When results match predictions, you validate methodology. Compound learning over time.
Decision confidence eliminates second-guessing.
Most operators doubt solutions mid-implementation. “Should we have done X instead?” Systematic design eliminates doubt - you evaluated X, it scored 34, your solution scored 52. Data supports decision.
Team alignment improves.
Showing the scoring matrix gets the team on the same page. Instead of “I think we should do Y” debates, you have objective criteria everyone can evaluate against.
Business learning accelerates.
Track solutions and outcomes over time. After 10 solution design cycles, patterns emerge. Discover your business responds better to speed-focused solutions, or that low-cost solutions succeed more often than high-investment approaches. Use data to refine future designs.
The Cost of Reactive Solution Selection
Here’s what happens when solution selection stays reactive:
You implement wrong solutions efficiently. Fast execution on poorly selected solution equals wasted effort. Operator chose “build lead generation system” (took 8 weeks, $12,000). The problem was the conversion rate, not the lead volume. New leads exposed the broken sales process faster. Net revenue impact: zero. Systematic design would’ve revealed sales process scores of 72 and lead generation scores of 41.
Solutions conflict instead of compound. Picking solutions individually without holistic evaluation creates conflicts. Solution A helps revenue but hurts margin. Solution B helps the margin but reduces growth. You’re fighting yourself. Systematic design reveals these conflicts during evaluation, not after implementation.
Opportunity cost stays invisible. Every week, implementing a suboptimal solution is NOT implementing an optimal solution. The operator spent 12 weeks productizing when redistribution + automation would’ve solved the problem in 3 weeks. Lost 9 weeks of progress.
Founder confidence erodes. Failed solutions undermine confidence in decision-making. After 3-4 wrong picks, paralysis sets in. “Nothing works.” Not true - wrong solutions don’t work. The right solutions work consistently.
Team trust degrades. Team watches founder choose solution, implement poorly, pivot to a different solution, repeat. Trust erodes. “Does founder know what they’re doing?” Systematic design shows rigorous thinking. Team sees the evaluation process, trusts decisions more.
The math: if you’re picking first-instinct solutions, you’re succeeding 40% of the time and wasting 60% of implementation effort. If you’re designing systematically, you’re succeeding 80% of the time and wasting only 20%.
Every solution you implement without systematic design costs you weeks of potential progress.
Solution Design Integration
Solution design doesn’t exist in isolation. Here’s the tactical sequence for using it with other frameworks:
Sequence 1 - After Problem Analysis:
Start with a strategic analysis to understand the root cause. The 5-Layer Analysis reveals what’s broken and why. Then use solution design to evaluate which specific intervention scores highest for your constraints.
Analysis reveals WHAT to fix. Design reveals HOW to fix it optimally.
Sequence 2 - Before Major Decisions:
When facing high-stakes decisions, use solution design to evaluate options systematically. The Next Ceiling identifies growth constraints. Solution design evaluates which intervention breaks it most effectively.
Don’t jump to a solution. Generate options. Score them. Choose deliberately.
Sequence 3 - Resource Allocation:
Use the solution design’s cost criterion to identify the highest ROI interventions. Then use Focus That Pays to protect hours needed for implementation.
Solution design identifies what to work on. Focus framework protects time to actually do it.
Sequence 4 - Team Decisions:
When the team debates which direction to take, use solution design to create an objective evaluation. The Delegation Map shows what to delegate. Solution design shows whether to delegate, hire, or automate based on scoring.
Run a scoring session together. Gets everyone aligned on criteria and removes emotional attachment to specific solutions.
Sequence 5 - Crisis Response:
In crisis situations, weight Speed criterion 3x and Reversibility 2x. Need fast results and low risk. Solution design prevents panic decisions while maintaining rigorous evaluation.
The pattern: Solution design is a decision-making methodology. Use it whenever choosing between 2+ options with meaningful resource implications.
The Question That Reveals Your Solution Quality
Here’s the diagnostic question:
When you face a business problem, do you implement the first reasonable solution, or do you generate multiple options and evaluate systematically?
Most operators implement the first solution. That’s why most operators waste 60% of implementation time on suboptimal approaches.
Strategic operators design multiple solutions, score rigorously, and choose deliberately. Solutions work as expected. Implementation time drops 40-60%.
The difference compounds exponentially over time.
Your Solution Design Practice Starts Now
Strategic thinking isn’t theory - it’s practice. Here’s your implementation sequence.
Next 30 minutes:
Pick one current problem you’re about to solve (revenue issue, team problem, delivery challenge, margin pressure)
Generate 5 solution options - don’t evaluate yet, just list possibilities
Set up scoring matrix (6 columns for criteria, rows for solutions)
This week:
Complete a full evaluation on those 5 solutions
Take 3-4 hours total - score each solution on all 6 criteria honestly
Calculate totals and identify the optimal solution for your context
By the end of the week, you should have a clear winner with an implementation plan
Before next month:
Implement the highest-scoring solution from your design
Track: Did systematic design lead to a better solution than the first instinct would have?
Measure: Time invested in design, success rate of solution, impact on business
Start the second design cycle on a different problem
Solution Design Milestones: What Good Looks Like
Week 1: Complete the first solution design in under 4 hours. Generate 5+ options, score across all criteria. Don’t expect perfection - focus on completing the framework systematically.
Week 4: Can generate 7-10 solutions per problem automatically. Stop defaulting to first instinct. Scoring reveals non-obvious winners 50% of the time.
Month 3: Solution design becomes a natural evaluation pattern. The team starts requesting scoring sessions before major decisions. Implementation success rate improves from 40% to 70%.
Month 6: Business decisions are measurably better. Track solutions implemented, success rates, and time savings. Solution design prevented 3-5 expensive mistakes worth $50,000-$150,000 total. Capability compounds across the organization.
FAQ: 6-Criteria Solution Framework
Q: How does the 6-Criteria Solution Framework stop $50K–$100K operators from wasting 90 days on the wrong fix?
A: It forces every option through six scores—Effectiveness, Feasibility, Reversibility, Speed, Cost, and Leverage—in a 3-hour pass so you choose the single best-fit solution before execution instead of burning 6–12 weeks on “good-sounding” moves that don’t match your constraints.
Q: How do I use the 6-Criteria Solution Framework with its scoring matrix before I commit to a 90-day project?
A: You generate 5–10 options in 1–2 hours, score each 1–10 across all six criteria in 60–90 minutes, weight criteria if you’re in crisis or constraint-heavy situations, then let the highest total (or weighted) score determine the solution you’ll implement over the next 2–4 weeks.
Q: Why do first-instinct and availability-bias solutions keep failing even when my problem diagnosis is correct?
A: Because you default to the most familiar move—like cutting team, building lead gen, or hiring—without checking Effectiveness, Feasibility, and Cost against your real constraint, which is how one operator turned a correct “margin compression” diagnosis into a $168,000 loss by cutting revenue-generating staff instead of raising prices.
Q: How do I practically build and use the 6-column scoring matrix for problems like flat $35K revenue?
A: You list solutions like raise prices, hire sales, build lead gen, productize, add upsell, and do nothing as rows, create columns for the six criteria, score each 1–10, then sum, which in the $35K example revealed “raise prices” at 53 beating “lead gen” at 42 and “hire sales” at 31 despite those feeling more exciting.
Q: When should I weight Speed, Reversibility, or Cost more heavily instead of treating all six criteria equally?
A: In crisis you weight Speed 3x so fast-to-validate options win, in high-uncertainty or experimental moves you weight Reversibility 2x so low-exit-cost options rise, and in cash-constrained situations you weight Cost 3x so low-investment options beat glamorous but resource-heavy plays.
Q: How does this framework change my decision when the “obvious” solution is to hire, productize, or build lead gen?
A: It often flips the winner by revealing that redistribution or automation scores 50 vs 27 for hiring in overwhelm cases, price changes score 72 vs 41 for lead gen when the real constraint is conversion, and gradual or hybrid productization scores in the high 40s vs mid-30s for full, irreversible model shifts.
Q: How do I use the six criteria for people and capacity problems, like an overwhelmed team member at 60 hours weekly?
A: You generate options like hire, redistribute, automate, reduce clients, train, and set boundaries, then score each; in the example, redistribution scored 50 and boundaries 49 while hiring scored 27, leading to an 8-hour redistribution project that cut the person from 60 to 38 hours without adding $50,000 in salary.
Q: What happens if I keep picking solutions based on effort or “strategic vibes” instead of six-criteria scoring?
A: You implement wrong solutions very efficiently, like an 8-week, $12,000 lead gen build that delivers zero net revenue because the real constraint was a 19% close rate, or full productization that takes 12 weeks, destabilizes clients, and could have been replaced by a low-risk gradual transition that validated the model with 5 clients.
Q: How do I integrate the 6-Criteria Solution Framework with 5-Layer Problem Analysis and growth constraint tools?
A: You use 5-Layer Problem Analysis or Bottleneck/Next Ceiling work to define the root problem and constraint, then feed only constraint-aligned options into the 6-criteria matrix so you’re not scoring fixes to the wrong problem, and finally protect implementation time with your focus/time-blocking system once the best solution wins.
Q: What should my solution design practice look like over the next 6 months if I want compounding benefits?
A: You start with one 3–4 hour cycle this week on a real problem, run 1–2 full solution designs per month, track success rate and avoided mistakes, and by month 6 you’ll have 10+ scored decisions, 3–5 expensive mistakes avoided worth $50,000–$150,000, and a default habit of designing solutions instead of reacting to the first reasonable idea.
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