Run a fair test to learn whether a route, pricing, service, staffing, equipment, promotion, or capacity decision improves both customer service and the landscaping company's financial result.
This activity uses a fictional landscaping and lawn care model. The goal is not to discover a guaranteed winning setup. Form a testable claim, change one main variable, collect connected operating and financial evidence, calculate the effect, and make a recommendation that acknowledges uncertainty.
Name: Date: Class/team:
1. Frame the landscaping decision
Choose one investigation and turn it into a claim that the simulator evidence could support or reject.
Pricing: Will budget, balanced, or premium contract pricing improve profit after its effects on demand, average job value, and contribution?
Service mix: Will weekly mowing, seasonal cleanup, fertilizer and maintenance, or landscape installation improve margin without overwhelming the route?
Staffing: Will another crew member, dispatcher, equipment technician, or manager reduce lost jobs and route time enough to cover payroll?
Equipment and quality: Will a vendor, maintenance, or quality-investment change protect equipment condition, job speed, reviews, and repeat demand?
Promotion: Will extra demand create profitable work after promotion cost, travel, fuel, service quality, and capacity effects?
Capacity: Will another crew truck serve enough additional jobs to cover the truck, crew, fuel, equipment, utility, and coordination burden?
Decision question
Prediction and business reason
Precommit the evidence
Primary outcome (month profit, contribution, cash, or net worth):
Operating driver (jobs completed, average job, route time, quality, or equipment condition):
Guardrail that must not become unacceptable (lost jobs, route inefficiency, satisfaction, reviews, morale, or cash):
2. Design a controlled test
Keep the same business format, city, service area, challenge, run length, starting state, and decision timing. Record a baseline month before changing one main control. Repeat the stronger setting. Label a rain-delay week, HOA contract inquiry, neighborhood review, parts delay, mower downtime, or spring-cleanup rush rather than treating it as part of the decision.
Period
Main setting
Settings held constant
Start / stop day
What would support the claim?
Baseline
Test
Repeat
Fair-test check: If students change price, service mix, staffing, vendor, quality, advertising, promotion, and trucks together, they may improve the score but cannot identify the cause. Save a multi-variable redesign until after the controlled comparison.
3. Calculate route and job economics
Use figures from the same day or completed monthly report. State whether each figure is shown by the simulator or calculated. The daily profit breakdown reports contribution per job and break-even jobs; use the formulas to explain why those values change.
Average revenue per job = service revenue ÷ jobs completed
Contribution per job = (revenue − fuel/equipment − inefficiency − job-linked utilities) ÷ jobs
Break-even jobs = fixed period costs ÷ contribution per job
Job completion rate = jobs completed ÷ service requests × 100%
Change in outcome = test result − baseline result
The simulator groups payroll, rent, fuel and equipment, route inefficiency, utilities, and marketing. If you classify a cost as fixed or job-linked, state that assumption. Route time is a simplified indicator rather than a real travel-time estimate.
Baseline calculation
Test calculation
Assumption / data limit
4. Record connected evidence
Copy results at the same point in each period. Use completed monthly reports for monthly claims and daily values only for a clearly labelled daily comparison.
Measure
Baseline
Test
Repeat
Meaning / direction
Service requests
Jobs completed
Lost jobs
Average job value
Route time
Route inefficiency
Service quality
Equipment condition
Satisfaction / review
Month revenue
Month costs
Month profit
Cash / net worth
Morale / turnover risk
Unexpected event or alert:
5. Diagnose the result before recommending
Use a pattern across measures. A rise in requests, revenue, or net worth alone does not prove the decision improved the landscaping system.
Observed pattern
Likely explanation
Next controlled test
Requests rise, but lost jobs and route time rise.
Promotion or price created demand beyond current crew, dispatch, or truck capacity.
Hold demand steady; test staffing or route capacity.
Jobs rise, but inefficiency and fuel/equipment share erase profit.
Scattered work or a complex service mix weakens route density and contribution.
Test a tighter route, simpler mix, or higher job value.
Equipment condition falls with quality and completed jobs.
Workload exceeds maintenance or vendor reliability.
Hold demand steady; test maintenance or vendor choice.
Premium price lifts job value but reduces requests.
The higher contribution may or may not offset lower conversion.
Compare contribution, break-even jobs, and profit across equal periods.
More staff lowers route time but payroll share rises sharply.
Coverage improved before enough profitable demand existed.
Test one fewer role or a denser route with the same crew.
Profit rises once, but the repeat does not confirm it.
Seasonality, an event, starting conditions, or random variation may explain the change.
Repeat again or narrow the claim.
Claim supported, partly supported, or rejected?
Two measures that justify the judgment:
6. Make an evidence-bounded recommendation
Write a decision that connects the control, mechanism, result, guardrail, and uncertainty. Avoid claims such as “always profitable” or “best route.”
Recommended decision:
Because it changed these operating and financial measures:
Risk, model limit, or condition that could change the recommendation:
Crew-truck expansion stop rule: recommend another truck only when a maintained, appropriately staffed operation repeatedly loses profitable jobs to physical capacity; contribution from realistically added work covers the truck and added crew/operating burden; cash remains above a stated reserve; and route time, quality, equipment condition, morale, and customer satisfaction remain acceptable. Otherwise improve route density, staffing, maintenance, price, or service mix first.
Teacher guide and suggested answers
50-minute lesson
5 minutes: introduce route density and distinguish requests, completed jobs, average job value, contribution, and profit.
8 minutes: teams choose one decision, state a mechanism, and precommit an outcome, driver, and guardrail.
20 minutes: run baseline, test, and repeat periods; record events and equal-period evidence.
10 minutes: calculate completion rate, contribution, break-even jobs, margin, or change in outcome.
7 minutes: exchange recommendations and challenge whether the evidence identifies cause.
30-minute route: provide a common baseline, let teams run one test and short repeat, then require one calculation and a two-measure recommendation. 15-minute route: project two prepared monthly reports and ask students to diagnose the constraint and choose the next fair test. No-device route: print or read a baseline/test dataset and use sections 3, 5, and 6 as a case analysis.
Suggested answer patterns
A strong route-density answer explains that more requests are useful only when the business completes them at adequate contribution without excessive route time, inefficiency, lost jobs, or quality damage.
A strong staffing answer compares the payroll increase with added contribution and checks morale, route time, completion, and service quality. It does not assume either the smallest or largest crew is automatically best.
A strong equipment answer links condition to job speed and quality, then compares maintenance or vendor cost with avoided downtime, lost work, and reputation risk.
A strong expansion answer applies the stop rule and treats a one-period rush or contract inquiry as insufficient evidence for a permanent truck.
A careful conclusion distinguishes what the model showed from real-world predictions and names seasonality, travel geography, job scope, safety, regulation, and weather as omitted or simplified factors.
12-point quick rubric
Criterion
0 points
1 point
2 points
Question and prediction
Missing
Vague or untestable
Specific control, outcome, and mechanism
Fair-test design
No comparison
Some controls or unequal periods
Baseline/test/repeat with constants and events labelled
Evidence record
Missing
Partial or mixed periods
Connected operating and financial measures
Calculation
Missing
Attempted with unclear units
Correct formula, figures, units, and interpretation
Diagnosis
Opinion only
One metric
Pattern across outcome, driver, and guardrail
Recommendation
Unsupported
Evidence used without limitation
Bounded decision with risk or next test
Responsible real-world boundaries
The simulator is an educational model, not a forecast, operating manual, employment plan, pesticide guide, contract, or professional advice. Real landscaping businesses differ by climate, route geography, service scope, equipment, customer contracts, labor market, and local law.
Follow current worker-safety, vehicle, equipment, chemical and pesticide, water-use, noise, environmental, licensing, insurance, employment, tax, accessibility, and consumer rules.
Use truthful, substantiated advertising. Do not claim guaranteed lawn outcomes, hide recurring contract terms, imitate reviews, misuse customer data, or pressure people with deceptive urgency.
Keep any advertising clearly separated from simulator controls, worksheet actions, navigation, and educational conclusions. Never create clicks, traffic, testimonials, or results artificially.
Do not enter real customer, worker, address, payment, health, or contract information. The activity does not require personal data.
Frequently asked questions
What should students change first in the Landscaping Simulator?
Choose one main variable—price strategy, service mix, staffing style, quality investment, equipment vendor, promotion, or route capacity—and hold the other settings steady. A one-variable test makes the result easier to explain.
How many runs are needed for this landscaping worksheet?
Use at least one baseline period, one test period, and a repeat of the stronger setting. Compare equal periods and label unusual events such as rain delays, contract inquiries, parts delays, mower downtime, reviews, or a spring cleanup rush.
How can students tell whether another crew truck is justified?
First confirm that a well-staffed, maintained operation repeatedly loses profitable jobs because of capacity. Then compare added job contribution with the truck, crew, fuel, equipment, and operating costs while protecting cash, quality, route time, and equipment condition.
Can this landscaping activity work with one shared device?
Yes. Assign an operator, recorder, calculator, and evidence checker, or project one run and let teams predict each result before the class changes one setting.
Does this simulator provide real landscaping, safety, or legal advice?
No. It is a simplified educational model. Real operators must follow current local licensing, pesticide, water-use, noise, vehicle, worker-safety, employment, environmental, insurance, tax, contract, consumer, privacy, and advertising requirements.