HARTI

Tell us what to change or add.

1. Check a decision

Open a decision below. Check the area, period, inputs, result and proposed next step.

2. Try the inputs

Use Change example to try different values. Use Data needed to check the fields and sources. The land-use change decision has its own comparison views.

Record your corrections below, then download your answers or print them.

3. Check each decision

1. Investigate large comparable farmgate wholesale and retail spreadsDEC-DP25-001 · Price spreads
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Compare matching purchase and sale quotations after stated costs and mass loss.

Validation required

Fictional default example · 2025.

Fictional case / areaQuoted net return per purchased kg [LKR/kg]Unadjusted quoted spread [LKR/kg]Next check
Laggala Pallegama — price spreads / 202510.942Check matching product grades, quantities, losses and quote periods
Rattota — price spreads / 202510.9550Check matching product grades, quantities, losses and quote periods
Panvila — price spreads / 2025835Check matching product grades, quantities, losses and quote periods

What the selected record shows. Quoted net return per purchased kg: 10.9 LKR/kg.

Next step. Check matching product grades, quantities, losses and quote periods. Prepare quote comparison in the prototype creates a visible, downloadable draft. It is unassigned and not sent.

A spread does not establish excess profit, market power or an actual realised return.

Example chart
Quoted net return per purchased kg — fictional 2025 examples
Inputs, method and sources
Supplied inputValueUnit
Comparable purchase quotation180LKR/kg
Comparable selling quotation222LKR/kg
Non-overlapping transfer costs20LKR/kg
Expected saleable mass loss5%
Product, grade and price basisTomato / same stated grade / per purchased kilogram

Quoted spread = sell−buy. Net scenario return per purchased kg = sell×(1−loss%/100)−buy−matching transfer costs.

Use matching grade, price date, currency, mass basis and payment terms. This quotation scenario excludes unlisted costs and is not realized profit or a forecast.

Other required records: Commodity; grade; market role; price; unit; date; transfer costs.

Calculation appendix

  • SHARED domain decision contracts — Validation required. Domain decision rules and matching fictional examples. Local comparisons, constraints, source matching, sorting and follow-up proposals; developer checks do not establish scientific or client approval.
Your checks for this decision
2. Prioritize commodities with unusual price variabilityDEC-DP25-002 · Price volatility
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Review variation in comparable commodity-price observations.

Verified published formula · Sample coefficient of variation

Fictional default example · 2025.

Fictional case / areaObserved value [LKR/kg]Next check
Laggala Pallegama — price volatility / 2025104Check the comparable series and the reason for its variation
Rattota — price volatility / 2025111Check the comparable series and the reason for its variation
Panvila — price volatility / 2025118Check the comparable series and the reason for its variation

What the selected record shows. Observed value: 104 LKR/kg.

Next step. Check the comparable series and the reason for its variation. Prepare variation report in the prototype creates a visible, downloadable draft. It is unassigned and not sent.

A short series does not forecast prices or establish market instability.

Inputs, method and sources
Supplied inputValueUnit
Comparable observation104LKR/kg

Display observations in dated order. Sample SD uses n−1; coefficient of variation = 100 × SD / positive mean.

Match definitions, methods, grade, location and reference basis. Gaps are not joined. Descriptive variation is not a forecast, causal effect or significant trend.

Other required records: Regular prices; commodity grade; market; observation dates; baseline; missingness.

National Institute of Standards and Technology United States · Dataplot Coefficient of Variation
Government publication · Description, sample coefficient of variation and ratio-scale restrictions

Use a meaningful zero and positive mean. Local series selection and decision limits still need confirmation.

Calculation appendix

  • NIST Coefficient of Variation — Government publication. Definition of sample CV. Published sample SD/mean ratio; positive ratio-scale mean is needed.
  • SHARED domain decision contracts — Validation required. Domain decision rules and matching fictional examples. Local comparisons, constraints, source matching, sorting and follow-up proposals; developer checks do not establish scientific or client approval.
Your checks for this decision
3. Inform seasonal marketing using comparable historical patternsDEC-DP25-003 · Seasonal markets
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Review historical prices for the same commodity, grade and period basis.

Validation required

Fictional default example · 2025.

Fictional case / areaObserved value [LKR/kg]Next check
Laggala Pallegama — seasonal markets / 2025104Check source and period comparability before using the trend
Rattota — seasonal markets / 2025111Check source and period comparability before using the trend
Panvila — seasonal markets / 2025118Check source and period comparability before using the trend

What the selected record shows. Observed value: 104 LKR/kg.

Next step. Check source and period comparability before using the trend. Prepare trend report in the prototype creates a visible, downloadable draft. It is unassigned and not sent.

A few annual observations do not establish within-year seasonality or a forecast.

Inputs, method and sources
Supplied inputValueUnit
Comparable observation104LKR/kg

Display observations in dated order. Sample SD uses n−1; coefficient of variation = 100 × SD / positive mean.

Match definitions, methods, grade, location and reference basis. Gaps are not joined. Descriptive variation is not a forecast, causal effect or significant trend.

Other required records: Multi-year prices; season; market; grade; inflation basis; observation coverage.

Calculation appendix

  • SHARED domain decision contracts — Validation required. Domain decision rules and matching fictional examples. Local comparisons, constraints, source matching, sorting and follow-up proposals; developer checks do not establish scientific or client approval.
Your checks for this decision
4. Identify markets requiring closer price-distribution studyDEC-DP25-004 · Market comparisons
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Compare the spread of supplied matching price observations.

Validation required

Fictional default example · 2025.

Fictional case / areaObserved value [LKR/kg]Next check
Laggala Pallegama — market comparisons / 2025104Check the observations, spread and coverage of the selected series
Rattota — market comparisons / 2025111Check the observations, spread and coverage of the selected series
Panvila — market comparisons / 2025118Check the observations, spread and coverage of the selected series

What the selected record shows. Observed value: 104 LKR/kg.

Next step. Check the observations, spread and coverage of the selected series. Prepare distribution report in the prototype creates a visible, downloadable draft. It is unassigned and not sent.

A small example distribution does not establish a representative market distribution.

Inputs, method and sources
Supplied inputValueUnit
Comparable observation104LKR/kg

Display observations in dated order. Sample SD uses n−1; coefficient of variation = 100 × SD / positive mean.

Match definitions, methods, grade, location and reference basis. Gaps are not joined. Descriptive variation is not a forecast, causal effect or significant trend.

Other required records: Commodity; grade; comparable price quotes; market; period; sample count.

Calculation appendix

  • SHARED domain decision contracts — Validation required. Domain decision rules and matching fictional examples. Local comparisons, constraints, source matching, sorting and follow-up proposals; developer checks do not establish scientific or client approval.
Your checks for this decision
5. Expand observations where price reporting is incompleteDEC-DP25-005 · Market coverage
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Find missing and unknown price-reporting coverage.

Validation required

Fictional default example · 2025.

Fictional case / areaVerified coverage [%]Known uncovered [quotes]Unknown coverage [quotes]Next check
Laggala Pallegama — market coverage / 202565305Check the records behind the uncovered and unknown groups
Rattota — market coverage / 202585150Check the records behind the uncovered and unknown groups
Panvila — market coverage / 2025454015Check the records behind the uncovered and unknown groups

What the selected record shows. 30 quotes are known to be uncovered; 5 have unknown coverage. 65% are confirmed covered.

Next step. Check the records behind the uncovered and unknown groups. Prepare coverage follow-up in the prototype creates a visible, downloadable draft. It is unassigned and not sent.

A quote count does not establish market representativeness or price quality.

Example chart
Verified coverage — fictional 2025 examples
Inputs, method and sources
Supplied inputValueUnit
Required eligible frame100quotes
Distinct members of that frame covered65quotes
Frame members with unknown coverage5quotes

100 × distinct covered eligible units / eligible frame. Known uncovered = frame − covered − unknown.

Count each eligible unit once for the selected service and period. Received messages, attendance, adoption and outcomes are separate measures.

Other required records: Market frame; commodity list; required quotes; valid quotes; collection dates.

Calculation appendix

  • SHARED domain decision contracts — Validation required. Domain decision rules and matching fictional examples. Local comparisons, constraints, source matching, sorting and follow-up proposals; developer checks do not establish scientific or client approval.
Your checks for this decision
6. Compare documented food-basket costs across locationsDEC-DP25-006 · Food affordability
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Compare costs of the same specified rice, dhal and sugar basket.

Validation required

Fictional default example · 2025.

Fictional case / areaStated three-item basket cost [LKR]Next check
Laggala Pallegama price-basket scenario / 20251,740Check matching product grades and price sources
Rattota price-basket scenario / 20251,810Check matching product grades and price sources
Panvila price-basket scenario / 20251,775Check matching product grades and price sources

What the selected record shows. 5 kg rice × 220 + 1 kg red dhal × 350 + 1 kg white sugar × 290 = 1740.00 LKR. The quantities and prices are labelled scenario assumptions.

Next step. Check matching product grades and price sources. Prepare cost comparison in the prototype creates a visible, downloadable draft. It is unassigned and not sent.

The fictional three-item basket is not an official cost-of-living measure.

Example chart
Stated three-item basket cost — fictional 2025 examples
Inputs, method and sources
Supplied inputValueUnit
Raw rice in the stated basket5kg
Comparable raw-rice price220LKR/kg
Red dhal in the stated basket1kg
Comparable red-dhal price350LKR/kg
White sugar in the stated basket1kg
Comparable white-sugar price290LKR/kg

Basket cost = rice kg × rice LKR/kg + red-dhal kg × red-dhal LKR/kg + white-sugar kg × white-sugar LKR/kg. Compare locations only for the same quantities, product specifications, currency and price period.

This is a fictional three-item basket with stated quantities. It is not an official consumer-price index, nutritional basket, current market quotation or household expenditure estimate.

Other required records: Basket composition; quantities; local prices; income benchmark; period; definitions.

Calculation appendix

  • SHARED domain decision contracts — Validation required. Domain decision rules and matching fictional examples. Local comparisons, constraints, source matching, sorting and follow-up proposals; developer checks do not establish scientific or client approval.
Your checks for this decision
7. Assess enterprise margins for policy researchDEC-DP25-007 · Farmer returns
Try this decision

Compare farm-enterprise gross margins under matching output and cost conventions.

Verified published formula · Enterprise gross margin

Fictional default example · 2025.

Fictional case / areaEnterprise gross margin [LKR]Gross margin per hectare [LKR/ha]Variable-cost break-even price [LKR/kg]Next check
Laggala Pallegama — farmer returns / 2025135,000135,00080Review the prices, quantities and costs behind the margin
Rattota — farmer returns / 2025135,000135,00080Review the prices, quantities and costs behind the margin
Panvila — farmer returns / 2025135,000135,00080Review the prices, quantities and costs behind the margin

What the selected record shows. The supplied 4,500 kg at 110 LKR/kg gives 495,000 LKR revenue. After 360,000 LKR variable costs, gross margin is 135,000 LKR.

Next step. Review the prices, quantities and costs behind the margin. Prepare margin comparison in the prototype creates a visible, downloadable draft. It is unassigned and not sent.

Gross margin excludes some fixed and opportunity costs and does not establish profit.

Inputs, method and sources
Supplied inputValueUnit
Saleable output4,500kg
Realized price110LKR/kg
Variable costs360,000LKR
Matching crop area1ha
Crop and saleable-output basisPaddy rough rice / fictional one-hectare crop enterprise / same season

Gross margin = saleable output × realized price − variable costs. Divide by matching hectares for margin/ha; variable-cost break-even price = variable costs / output.

Keep fixed costs, family-labour opportunity cost, taxes and financing identifiable. Gross margin is not net profit. Crop, prices and costs are fictional coherent enterprise assumptions. Gross margin excludes fixed and financing costs; it is not household income or net profit.

Other required records: Crop revenue; variable costs; hectares; production system; sample weights.

Food and Agriculture Organization of the United Nations · Farm Management for Asia A Systems Approach
Institution publication · Chapter 4, Gross margin and section 4.7.1

Per-hectare and variable-cost break-even outputs are algebraic rearrangements. Local costs, prices and interpretation still need confirmation.

Calculation appendix

  • FAO enterprise and activity budgeting — Institution publication. Section4 enterprise and activity budgeting. Published enterprise gross margin/revenue and variable-cost distinction.
  • SHARED domain decision contracts — Validation required. Domain decision rules and matching fictional examples. Local comparisons, constraints, source matching, sorting and follow-up proposals; developer checks do not establish scientific or client approval.
Your checks for this decision
8. Identify value-chain stages requiring loss studiesDEC-DP25-008 · Marketing losses
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Reconcile input mass with saleable output, by-products, transfers and stock.

Validation required

Fictional default example · 2025.

Fictional case / areaUnaccounted physical share [%]Unaccounted mass [kg]Next check
Laggala Pallegama — marketing losses / 20256.66780Reconcile the input, output, stock and transfer records
Rattota — marketing losses / 20256.66780Reconcile the input, output, stock and transfer records
Panvila — marketing losses / 20256.66780Reconcile the input, output, stock and transfer records

What the selected record shows. Unaccounted physical share: 6.667 %.

Next step. Reconcile the input, output, stock and transfer records. Prepare loss-balance review in the prototype creates a visible, downloadable draft. It is unassigned and not sent.

An unaccounted balance does not establish where or why physical loss occurred.

Inputs, method and sources
Supplied inputValueUnit
Batch input on stated moisture basis1,200kg
Saleable output970kg
Usable by-product85kg
Closing stock45kg
Documented transfers out20kg

Unaccounted = input − saleable output − usable by-products − closing stock − transfers out. Share =100 × unaccounted / input.

Use a consistent moisture basis and process boundary. Unaccounted mass is not automatically avoidable food loss or spoilage.

Other required records: Batch input; output; losses; quality degradation; stage; measurement protocol.

Calculation appendix

  • FAO food loss measurement — Institution publication. Full method locator not established. Institutional context; does not establish the calculation or local approval.
  • SHARED domain decision contracts — Validation required. Domain decision rules and matching fictional examples. Local comparisons, constraints, source matching, sorting and follow-up proposals; developer checks do not establish scientific or client approval.
Your checks for this decision
9. Investigate persistent differences between connected marketsDEC-DP25-009 · Market integration
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Compare connected-market quotations after stated transport costs and losses.

Validation required

Fictional default example · 2025.

Fictional case / areaQuoted net return per purchased kg [LKR/kg]Unadjusted quoted spread [LKR/kg]Next check
Laggala Pallegama — market integration / 202510.942Check matching product grades, quantities, losses and quote periods
Rattota — market integration / 202510.9550Check matching product grades, quantities, losses and quote periods
Panvila — market integration / 2025835Check matching product grades, quantities, losses and quote periods

What the selected record shows. Quoted net return per purchased kg: 10.9 LKR/kg.

Next step. Check matching product grades, quantities, losses and quote periods. Prepare quote comparison in the prototype creates a visible, downloadable draft. It is unassigned and not sent.

A price difference does not prove arbitrage feasibility or market inefficiency.

Example chart
Quoted net return per purchased kg — fictional 2025 examples
Inputs, method and sources
Supplied inputValueUnit
Comparable purchase quotation180LKR/kg
Comparable selling quotation222LKR/kg
Non-overlapping transfer costs20LKR/kg
Expected saleable mass loss5%
Product, grade and price basisTomato / same stated grade / per purchased kilogram

Quoted spread = sell−buy. Net scenario return per purchased kg = sell×(1−loss%/100)−buy−matching transfer costs.

Use matching grade, price date, currency, mass basis and payment terms. This quotation scenario excludes unlisted costs and is not realized profit or a forecast.

Other required records: Matched prices; transport costs; grade; trade flows; dates; restrictions.

Calculation appendix

  • SHARED domain decision contracts — Validation required. Domain decision rules and matching fictional examples. Local comparisons, constraints, source matching, sorting and follow-up proposals; developer checks do not establish scientific or client approval.
Your checks for this decision
10. Evaluate agricultural policy outcomes with credible comparisonsDEC-DP25-010 · Policy evaluation
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Compare enterprise-income changes in the supplied treatment and comparison records.

Verified published formula · Difference-in-differences arithmetic

Fictional default example · 2025.

Fictional case / areaDifference in changes [LKR/ha]Next check
Laggala Pallegama — policy evaluation / 2025100,000Obtain the missing evidence listed below
Rattota — policy evaluation / 2025100,000Obtain the missing evidence listed below
Panvila — policy evaluation / 2025100,000Obtain the missing evidence listed below

What the selected record shows. Treatment change: 170,000; comparison change: 70,000; difference in changes: 100,000 LKR/ha. This comparison alone does not establish causation or benefit.

Next step. Obtain the missing evidence listed below. Prepare evidence request in the prototype creates a visible, downloadable draft. It is unassigned and not sent.

Information still needed
  • Study design and evidence that the treatment and comparison records are comparable

A difference in changes does not establish a causal policy effect.

Inputs, method and sources
Supplied inputValueUnit
Treatment Real enterprise income on stated price basis before420,000LKR/ha
Treatment Real enterprise income on stated price basis after590,000LKR/ha
Comparison Real enterprise income on stated price basis before390,000LKR/ha
Comparison Real enterprise income on stated price basis after460,000LKR/ha
Study design and comparability evidenceMissing
Outcome definition, method and reference basisReal enterprise income on stated price basis /example matching definition1

(Treatment after−before) − (comparison after−before), using the same outcome definition and periods.

The arithmetic alone does not establish causation. Design, parallel trends, confounding, attrition, uncertainty and adverse effects need appropriate evidence.

Other required records: Policy exposure; baseline; follow-up; comparison group; prices; weather; confounders.

World Bank · Impact Evaluation in Practice Second Edition
Institution publication · Chapter 7, table 7.2, printed page 140, PDF page 170

The formula is verified. Causal interpretation still requires a defensible study design, comparison and assumptions.

Calculation appendix

  • World Bank Impact Evaluation in Practice Second Edition — Institution publication. Chapter7 difference-in-differences. Published difference-in-differences estimator and study assumptions; aggregate examples do not establish causation.
  • SHARED domain decision contracts — Validation required. Domain decision rules and matching fictional examples. Local comparisons, constraints, source matching, sorting and follow-up proposals; developer checks do not establish scientific or client approval.
Your checks for this decision
11. Investigate shifts in agricultural input expenditureDEC-DP25-011 · Input markets
Try this decision

Compare expenditure for the same specified input quantity and price basis.

Validation required

Fictional default example · 2025.

Fictional case / areaItem expenditure [LKR]Next check
Laggala Pallegama — input markets / 202510,500Review cost components and comparable verified outputs
Rattota — input markets / 202510,500Review cost components and comparable verified outputs
Panvila — input markets / 202510,500Review cost components and comparable verified outputs

What the selected record shows. Item expenditure: 10,500 LKR.

Next step. Review cost components and comparable verified outputs. Prepare cost comparison in the prototype creates a visible, downloadable draft. It is unassigned and not sent.

An expenditure change does not separate price, quantity and product-quality effects automatically.

Inputs, method and sources
Supplied inputValueUnit
Specified basket/input quantity50kg
Comparable unit price210LKR/kg
Item, grade and basket specificationUrea / stated same grade and bag basis

Specified quantity × comparable unit price. Sum only non-overlapping items from the same basket specification, location and price period.

An absent or zero denominator has no unit-cost result. Keep fixed, variable and opportunity costs identifiable. Fictional same-grade urea prices are in LKR/kg. Quantity and unit price effects are kept separate; no current market price is implied.

Other required records: Input type; price; quantity; location; period; farm system.

Calculation appendix

  • SHARED domain decision contracts — Validation required. Domain decision rules and matching fictional examples. Local comparisons, constraints, source matching, sorting and follow-up proposals; developer checks do not establish scientific or client approval.
Your checks for this decision
12. Identify organizational barriers to collective marketingDEC-DP25-012 · Farmer organization research
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Compare collective-marketing approaches using participation, governance and buyer evidence.

Validation required

Fictional default example · 2025.

Fictional case / areaPotential benefit · assumptionResources and adverse effectsSupporting records / conditionsNext check
Improve group governance and records / Laggala PallegamaImprove group governance and records.Needs participation, financial controls, representation and reliable records.Records: Not provided; condition evidence: Not providedObtain the missing records before choosing
Coordinate collective sales / Laggala PallegamaCoordinate collective sales.Needs agreed quantities, grades, timing, accountability and buyers.Records: Not provided; condition evidence: Not providedObtain the missing records before choosing
Improve grading and buyer access / Laggala PallegamaImprove grading and access to buyers.Needs product standards, handling capacity and confirmed buyer requirements.Records: Not provided; condition evidence: Not providedObtain the missing records before choosing

What the selected record shows. There is not enough information to choose this option. Obtain the records and evidence about conditions listed below. The supplied budget less cost is 300,000 LKR.

Next step. Obtain the missing records before choosing. Prepare evidence request in the prototype creates a visible, downloadable draft. It is unassigned and not sent.

Information still needed
  • Records needed: Organization evidence; participation; costs; sales outcomes; governance; research design
  • Applicable conditions, what was checked and the supporting reference

Cost alone does not establish collective readiness or a marketing benefit.

Inputs, method and sources
Supplied inputValueUnit
Option cost1,500,000LKR
Available budget1,800,000LKR
Mandatory constraintsMet
Potential benefit and its evidence or assumptionImprove group governance and records.
Resource needs and adverse effectsNeeds participation, financial controls, representation and reliable records.
Required records available for this optionNot provided
Reference for the required recordsNot provided
Applicable conditions, check result and supporting referenceNot provided

Compare each alternative's stated benefit, adverse effects, domain evidence and mandatory constraints. Where cost and budget are supplied, budget balance = budget − option cost. A budget balance alone does not determine domain feasibility or select an option.

Cost alone does not establish collective readiness or a marketing benefit.

Other required records: Organization evidence; participation; costs; sales outcomes; governance; research design.

Calculation appendix

  • SHARED domain decision contracts — Validation required. Domain decision rules and matching fictional examples. Local comparisons, constraints, source matching, sorting and follow-up proposals; developer checks do not establish scientific or client approval.
Your checks for this decision
13. Review farm labour costs and labour-use differencesDEC-DP25-013 · Land and labour
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Compare cash labour cost and total recorded effort per matching hectare.

Validation required

Fictional default example · 2025.

Fictional case / areaCash labour cost per hectare [LKR/ha]Total labour per hectare [person-days/ha]Next check
Laggala Pallegama — land and labour / 202572,00028.5Check matching outputs, denominators and operating conditions
Rattota — land and labour / 202572,00028.5Check matching outputs, denominators and operating conditions
Panvila — land and labour / 202572,00028.5Check matching outputs, denominators and operating conditions

What the selected record shows. Cash labour cost per hectare: 72,000 LKR/ha.

Next step. Check matching outputs, denominators and operating conditions. Prepare performance comparison in the prototype creates a visible, downloadable draft. It is unassigned and not sent.

Unpaid family labour is effort and is not included as a cash wage payment.

Inputs, method and sources
Supplied inputValueUnit
Person-days worked45person-days
Cash wage per hired person-day3,200LKR/person-day
Matching cultivated area2ha
Unpaid family labour12person-days

Cash cost/ha = hired days×cash wage/area. Total effort/ha=(hired+unpaid family days)/area. Do not value unpaid labour as zero opportunity cost.

Other required records: Labour days; wages; crop; season; hectares; family and hired labour.

Calculation appendix

  • SHARED domain decision contracts — Validation required. Domain decision rules and matching fictional examples. Local comparisons, constraints, source matching, sorting and follow-up proposals; developer checks do not establish scientific or client approval.
Your checks for this decision
14. Prioritize research on documented market supply shocksDEC-DP25-014 · Food supply disruptions
Try this decision

Compare reported supply observations with their matching reference values.

Validation required

Fictional default example · 2025.

Fictional case / areaDifference [kg]Relative change [%]Next check
Laggala Pallegama — food supply disruptions / 2025-10-10Check the unusual observation and its comparison basis
Rattota — food supply disruptions / 202555Check the unusual observation and its comparison basis
Panvila — food supply disruptions / 2025-2-2Check the unusual observation and its comparison basis

What the selected record shows. Difference: -10 kg.

Next step. Check the unusual observation and its comparison basis. Prepare investigation brief in the prototype creates a visible, downloadable draft. It is unassigned and not sent.

A difference needs source checks before identifying a shock or its cause.

Example chart
Difference — fictional 2025 examples
Inputs, method and sources
Supplied inputValueUnit
Comparable reference value100kg
Later/comparison value90kg

Later/comparison value minus Comparable reference value. Relative change = 100 × difference / Comparable reference value when the earlier value is positive.

Other required records: Arrivals; prices; transport interruptions; crop output; event timing; baseline.

Calculation appendix

  • SHARED domain decision contracts — Validation required. Domain decision rules and matching fictional examples. Local comparisons, constraints, source matching, sorting and follow-up proposals; developer checks do not establish scientific or client approval.
Your checks for this decision
15. Compare storage and handling options for perishablesDEC-DP25-015 · Storage investments
Try this decision

Compare storage cash-flow scenarios under the stated investment and discount assumptions.

Verified published formula · Discounted cash-flow NPV

Fictional default example · 2025.

Fictional case / areaFive-year net present value [LKR]Next check
Base cash-flow scenario / 2025109,847.353Review the cash flows, discount assumptions and constraints
Lower net-receipts scenario / 2025-497,196.989Review the cash flows, discount assumptions and constraints
Higher initial-cost scenario / 2025-370,152.647Review the cash flows, discount assumptions and constraints

What the selected record shows. At the supplied 8% annual discount assumption, the five-year cash flows and residual value give 109,847.353 LKR net present value after the initial investment. The figure compares cash flows under these assumptions.

Next step. Review the cash flows, discount assumptions and constraints. Prepare cash-flow comparison in the prototype creates a visible, downloadable draft. It is unassigned and not sent.

Net present value does not establish avoided spoilage or investment suitability.

Example chart
Five-year net present value — fictional 2025 examples
Inputs, method and sources
Supplied inputValueUnit
Initial investment2,400,000LKR
Net cash flow year1400,000LKR
Net cash flow year2550,000LKR
Net cash flow year3680,000LKR
Net cash flow year4720,000LKR
Net cash flow year5760,000LKR
Residual value at end of year5120,000LKR
Example discount rate8%

NPV = −initial investment + sum of year1…5 net cash flows discounted at the stated annual rate, including residual value once in year5.

Match currency, price year, real/nominal basis and cash-flow timing. The example rate and five-year horizon are assumptions, not institutional financing terms; no credit approval follows.

Other required records: Storage costs; losses; capacity; price seasonality; energy; shelf life.

Food and Agriculture Organization of the United Nations · Guidelines for defining financial economic environmental and social information
Institution publication · Sections 2.2.2 and 2.2.3, discounting and Net Present Value

The five-year horizon, discount rate and cash assumptions are local settings. Verification does not approve an investment or loan.

Calculation appendix

Your checks for this decision
16. Select agrarian research sampling strategiesDEC-DP25-016 · Survey design
Try this decision

Compare agrarian study designs using the research question, frame and variance evidence.

Validation required

Fictional default example · 2025.

Fictional case / areaPotential benefit · assumptionResources and adverse effectsSupporting records / conditionsNext check
Stratified farm-household survey / Laggala PallegamaUse a stratified farm-household survey.Needs a frame, inclusion probabilities, variance methods and access.Records: Not provided; condition evidence: Not providedObtain the missing records before choosing
Panel of matched farm enterprises / Laggala PallegamaFollow a panel of matched farm enterprises.Needs selection, attrition, comparability and repeated-measure design evidence.Records: Not provided; condition evidence: Not providedObtain the missing records before choosing
Cluster-based field study / Laggala PallegamaUse a cluster-based field study.Needs cluster selection, design effects, field costs and valid estimation methods.Records: Not provided; condition evidence: Not providedObtain the missing records before choosing

What the selected record shows. There is not enough information to choose this option. Obtain the records and evidence about conditions listed below. The supplied budget less cost is 300,000 LKR.

Next step. Obtain the missing records before choosing. Prepare evidence request in the prototype creates a visible, downloadable draft. It is unassigned and not sent.

Information still needed
  • Records needed: Target population; strata; expected variability; research question; cost; precision
  • Applicable conditions, what was checked and the supporting reference

A low-cost option does not establish valid selection or causal identification.

Inputs, method and sources
Supplied inputValueUnit
Option cost1,500,000LKR
Available budget1,800,000LKR
Mandatory constraintsMet
Potential benefit and its evidence or assumptionUse a stratified farm-household survey.
Resource needs and adverse effectsNeeds a frame, inclusion probabilities, variance methods and access.
Required records available for this optionNot provided
Reference for the required recordsNot provided
Applicable conditions, check result and supporting referenceNot provided

Compare each alternative's stated benefit, adverse effects, domain evidence and mandatory constraints. Where cost and budget are supplied, budget balance = budget − option cost. A budget balance alone does not determine domain feasibility or select an option.

A low-cost option does not establish valid selection or causal identification.

Other required records: Target population; strata; expected variability; research question; cost; precision.

Calculation appendix

  • SHARED domain decision contracts — Validation required. Domain decision rules and matching fictional examples. Local comparisons, constraints, source matching, sorting and follow-up proposals; developer checks do not establish scientific or client approval.
Your checks for this decision
17. Resolve contradictory market observations before releaseDEC-DP25-017 · Publication quality
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Compare conflicting market measurements with matching units, grades and periods.

Validation required

Fictional default example · 2025.

Fictional case / areaDifference [LKR/kg]Relative change [%]Next check
Laggala Pallegama — publication quality / 2025-10-10Reconcile the original records using their source references
Rattota — publication quality / 202555Reconcile the original records using their source references
Panvila — publication quality / 2025-2-2Reconcile the original records using their source references

What the selected record shows. Difference: -10 LKR/kg.

Next step. Reconcile the original records using their source references. Prepare source comparison in the prototype creates a visible, downloadable draft. It is unassigned and not sent.

A difference does not identify which source should be corrected.

Inputs, method and sources
Supplied inputValueUnit
Original source measurement100LKR/kg
Independent comparison measurement90LKR/kg
Original measurement unitSample matching unit
Comparison measurement unitSample matching unit
Compared measure and definitionSample comparable LKR/kg measure; same input scope

Later/comparison value minus Earlier/source value. Relative change = 100 × difference / Earlier/source value when the earlier value is positive.

Keep both originals, units, scope, method, calibration and correction history. A difference does not identify which source is correct; no automatic averaging or overwrite.

Other required records: Observation ID; independent quote; unit; grade; collection date; verification.

Calculation appendix

  • SHARED domain decision contracts — Validation required. Domain decision rules and matching fictional examples. Local comparisons, constraints, source matching, sorting and follow-up proposals; developer checks do not establish scientific or client approval.
Your checks for this decision
18. Target agrarian training to documented capability gapsDEC-DP25-018 · Training priorities
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Find participants with a recorded capability gap who lack matching training.

Validation required

Fictional default example · 2025.

Fictional case / areaVerified coverage [%]Known uncovered [participants]Unknown coverage [participants]Next check
Laggala Pallegama — training priorities / 202565305Check the records behind the uncovered and unknown groups
Rattota — training priorities / 202585150Check the records behind the uncovered and unknown groups
Panvila — training priorities / 2025454015Check the records behind the uncovered and unknown groups

What the selected record shows. 30 participants are known to be uncovered; 5 have unknown coverage. 65% are confirmed covered.

Next step. Check the records behind the uncovered and unknown groups. Prepare coverage follow-up in the prototype creates a visible, downloadable draft. It is unassigned and not sent.

Attendance does not establish competence or the effect of training.

Example chart
Verified coverage — fictional 2025 examples
Inputs, method and sources
Supplied inputValueUnit
Participants with a documented relevant capability gap100participants
Those participants receiving the matching training65participants
Participants with unknown training status5participants

100 × distinct covered eligible units / eligible frame. Known uncovered = frame − covered − unknown.

Count each eligible unit once for the selected service and period. Received messages, attendance, adoption and outcomes are separate measures. Training coverage is not verified adoption or a measured gain in capability.

Other required records: Needs assessment; participant frame; previous training; adoption; location.

Calculation appendix

  • SHARED domain decision contracts — Validation required. Domain decision rules and matching fictional examples. Local comparisons, constraints, source matching, sorting and follow-up proposals; developer checks do not establish scientific or client approval.
Your checks for this decision
19. Prioritize policy-analysis requests by decision deadlinesDEC-DP25-019 · Research requests
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Identify policy-analysis requests past their recorded decision-response date.

Validation required

Fictional default example · 2025.

Fictional case / areaOpen days past due [days]Calendar age [days]Next check
Laggala Pallegama — research requests / 20252990Follow up overdue case; confirm the missing condition evidence
Rattota — research requests / 20252990Follow up overdue case; confirm the missing condition evidence
Panvila — research requests / 20252990Follow up overdue case; confirm the missing condition evidence

What the selected record shows. Open days past due: 29 days. Follow up overdue case.

Next step. Follow up overdue case; confirm the missing condition evidence. Prepare evidence request in the prototype creates a visible, downloadable draft. It is unassigned and not sent.

Information still needed
  • Documented critical unresolved condition: Unknown

A deadline does not determine policy importance or authorise a conclusion.

Inputs, method and sources
Supplied inputValueUnit
Received or defect observed2025-04-01
Recorded due date2025-06-01
Assessment date2025-06-30
Case/work closedNo
Documented critical unresolved conditionUnknown
Responsible office or maintainerProposed responsible office
Actual closure date when closedNot provided

Open age = assessment date − received date. Days past due = max(0, assessment date − recorded due date) for open cases. Show documented critical conditions separately.

Example due dates are not legal service standards. Do not alter statutory deadlines by silently subtracting pauses, or infer severity from age alone.

Other required records: Request; question; responsible institution; evidence availability; due date; analyst capacity.

Calculation appendix

  • SHARED domain decision contracts — Validation required. Domain decision rules and matching fictional examples. Local comparisons, constraints, source matching, sorting and follow-up proposals; developer checks do not establish scientific or client approval.
Your checks for this decision
20. Independently reproduce agrarian research findingsDEC-DP25-020 · Evidence reproducibility
Try this decision

Check whether supplied inputs reproduce a stated agrarian-research result.

Validation required

Fictional default example · 2025.

Fictional case / areaDifference [LKR/ha]Relative change [%]Next check
Laggala Pallegama — evidence reproducibility / 2025-10-10Investigate reproduction difference
Rattota — evidence reproducibility / 202555Investigate reproduction difference
Panvila — evidence reproducibility / 2025-2-2Investigate reproduction difference

What the selected record shows. Difference: -10 LKR/ha. Investigate reproduction difference.

Next step. Investigate reproduction difference. Prepare reproduction-check note in the prototype creates a visible, downloadable draft. It is unassigned and not sent.

Arithmetic reproduction does not validate the research design or policy inference.

Inputs, method and sources
Supplied inputValueUnit
Earlier/source value100LKR/ha
Independently reproduced value90LKR/ha
Original measurement unitSample matching unit
Comparison measurement unitSample matching unit
Compared measure and definitionSample comparable LKR/ha measure; same input scope
Documented absolute comparison tolerance0.01LKR/ha
Expected input/method versionSample input1 /method1
Reproduced input/method versionSample input1 /method1
Original result creatorPreparation officer
Independent reproducerIndependent checking officer

Reproduced minus expected result, within an explicitly supplied absolute tolerance, using the same exact input/method versions and a separate checker. Retain originals, code, parameters and environment evidence.

Other required records: Dataset edition; survey design; code; model; assumptions; result; reviewer.

Calculation appendix

  • SHARED domain decision contracts — Validation required. Domain decision rules and matching fictional examples. Local comparisons, constraints, source matching, sorting and follow-up proposals; developer checks do not establish scientific or client approval.
Your checks for this decision

4. Existing data forms for your institution

Check which existing source fields can supply the decision inputs.

Wholesale food prices — 2026-10-28 · Markets & Value Chains

Existing form reference: 5ef25f806a9c3864

FieldUnitRequired
CommodityConfirm if neededNo
MarketConfirm if neededNo
DateConfirm if neededNo
Average priceConfirm if neededNo
UnitConfirm if neededNo
Source pageConfirm if neededNo
Wholesale food prices — 2026-10-27 · Markets & Value Chains

Existing form reference: 65fb55fc4bacaeb4

FieldUnitRequired
CommodityConfirm if neededNo
MarketConfirm if neededNo
DateConfirm if neededNo
Average priceConfirm if neededNo
UnitConfirm if neededNo
Source pageConfirm if neededNo
Wholesale food prices — 2026-10-26 · Markets & Value Chains

Existing form reference: 3d27791c0b26d5a7

FieldUnitRequired
CommodityConfirm if neededNo
MarketConfirm if neededNo
DateConfirm if neededNo
Average priceConfirm if neededNo
UnitConfirm if neededNo
Source pageConfirm if neededNo
Wholesale food prices — 2026-10-23 · Markets & Value Chains

Existing form reference: 362fe913ea87b4d5

FieldUnitRequired
CommodityConfirm if neededNo
MarketConfirm if neededNo
DateConfirm if neededNo
Average priceConfirm if neededNo
UnitConfirm if neededNo
Source pageConfirm if neededNo
Wholesale food prices — 2026-10-22 · Markets & Value Chains

Existing form reference: 4c6b93b0f4ec772d

FieldUnitRequired
CommodityConfirm if neededNo
MarketConfirm if neededNo
DateConfirm if neededNo
Average priceConfirm if neededNo
UnitConfirm if neededNo
Source pageConfirm if neededNo
Wholesale food prices — 2026-10-21 · Markets & Value Chains

Existing form reference: edf7d040b8bcbc45

FieldUnitRequired
CommodityConfirm if neededNo
MarketConfirm if neededNo
DateConfirm if neededNo
Average priceConfirm if neededNo
UnitConfirm if neededNo
Source pageConfirm if neededNo
Wholesale food prices — 2026-10-20 · Markets & Value Chains

Existing form reference: f462aa65988abf9a

FieldUnitRequired
CommodityConfirm if neededNo
MarketConfirm if neededNo
DateConfirm if neededNo
Average priceConfirm if neededNo
UnitConfirm if neededNo
Source pageConfirm if neededNo

5. Documents and images

Your institution has its own document and image library. Use the same library for reports, photos and other evidence.

HARTI Documents and images prototype screen
HARTI. Prototype screen. Select the image to enlarge it.

What you can try

  1. Open Documents and images. Check the institution name.
  2. Use All files, Documents or Images to find a file. Open its preview or download the original.
  3. Use a sample file to try Add file. Private is the starting choice. Public needs a source, permission to share and review.
  4. Use Access preview to try the institution reviewer and Public visitor views.

Files added in the prototype stay in this browser. Public sharing is an access preview. Existing public reference links already work online.

What your institution needs to confirm

6. Data structure management

Data structure keeps the existing source tree, records, charts and map. Manage structure adds a place to propose changes to definitions.

HARTI Data structure management prototype screen
HARTI. Prototype screen. Select the image to enlarge it.

What you can try

  1. Open Data structure and choose Manage structure.
  2. Use Add base domain for a main information area. Add inside creates a subject area, a nested subject, an entity type or a field under the right parent.
  3. Give the definition a clear name, code and meaning. Reuse an existing definition when the meaning is the same.
  4. For a field, check the data type, unit, required value, limits and missing-value rule. Save a Draft, then try the separate reviewer view.

An entity type means a kind of thing or event, such as a reservoir or an inspection. Drafts stay in this browser. A demo approval does not change real definitions, data, chart links or sharing rights.

What your institution needs to confirm

7. Users and access

User management shows example profiles for each institution. People and Roles and access let you review the proposed account screens.

HARTI Users and access prototype screen
HARTI. Prototype screen. Select the image to enlarge it.

What you can try

  1. Open User management and choose the institution. The rows are examples, not a list of your staff.
  2. Use View access to check a role. An administrator title alone does not give access to Private files.
  3. Try Preview invitation or Preview access change. Check the role, start date, optional end date and reason.
  4. Review the example permissions and tell us which job roles should receive each one.

These are interface previews only. They create no account, send no email and change no access. Use example details in the preview. Institution verification does not grant a real permission.

What your institution needs to confirm

8. Can you share data regularly?

We currently use public data and published reports where available. Please confirm whether your institution can provide data directly, so we can avoid retyping or reading figures from PDFs.

Do not enter passwords, access keys or private account details.

9. Anything else we should change?

Use the Download answers button at the top of this page. Share the downloaded file or printed copy through your agreed review channel. Nothing is sent automatically.