Seven worked pro formas and appraisals, built from your live project rather than hardcoded numbers. Opening one fills it with your own areas, unit counts and usage rates, so it is a working starting point rather than a demo to look at.
Open an example workbook
Click File ▾ in the toolbar.
Choose one of the seven examples under the Examples · illustrative only heading. Hover over an example to see a one-line summary of what it models.
🚨 Opening a worked example workbook replaces the workbook currently open, and the copy saved in the project once it next saves. Use File ▾ → Save a .json copy first if you want to keep what is open now.
The examples are illustrative. Their assumptions, like rents, yields, and cost rates, are placeholders. Check each one against your own numbers before relying on the result.
Areas by usage
A project-wide summary block, then a live schedule with one row per usage:
Summary: site area, building footprint, site cover (footprint ÷ site area), gross floor area, net area, saleable area, plot ratio (gross ÷ site area), overall efficiency (net ÷ gross), construction cost (
GI.SUMEACH("grossArea * hardCost")), gross revenue (GI.SUMEACH("saleableArea * salePrice")), and margin ((revenue − cost) ÷ revenue).Schedule by usage: columns for Usage, Footprint, Gross, Net, Saleable, Efficiency, Cost, Revenue and FAR, one row per usage, each pulled with a filtered
GI.TOTAL,GI.WEIGHTEDAVGorGI.SUMEACH, plus a Total row.
A bar chart plots revenue and cost by usage side by side. Cost and revenue use GI.SUMEACH because it does the math for each geometry first.
Unit mix
Unit counts by bed type and usage, with a saleable-area check:
Summary: total dwellings, dwellings in residential usages only, distinct usage count, and saleable area per dwelling.
By bed type: Bed type, Units, Share and Saleable area, one row per bed type (1BED through 4BED), reading
GI.TOTAL("dwelling-1BED-Count")and so on, with each bed type's share of saleable area worked out from its share of units.Mix by usage: a live block with Usage, 1 bed, 2 bed, 3 bed, Total units and Saleable area, one row per usage.
A bar chart plots units by bed type. The dwelling mix arrives as one field per bed type, such as dwelling-2BED-Count, rather than as values of a single "bed type" column, which is why this example lists the mix fields as columns rather than as a pivot. A project with its own bespoke unit types shows its own field names here.
Residual appraisal
Assumptions, a schedule by usage, and the appraisal itself:
Assumptions: fees and contingency (15%), selling costs (3%), developer profit on revenue (20%), and finance rate (7.5%, shown as a reference figure).
Schedule by usage: Usage, Gross area, Saleable, Sale rate (
GI.WEIGHTEDAVG("salePrice")) and Revenue (saleable × sale rate), one row per usage, with a Total row.Appraisal: gross development value (total revenue), minus selling costs (revenue × 3%), minus construction cost (
GI.WEIGHTEDAVG("hardCost")× total gross area), plus fees and contingency (construction cost × 15%), minus developer profit (revenue × 20%), giving the residual land value. Two more rows convert that into land value per dwelling and per m² of site.
A doughnut chart breaks revenue down by usage. You can also build the same calculation step by step from individual GI.* formulas.
Monthly cashflow
A 24-month draw and sales programme, with the return calculated at the bottom:
Programme assumptions: build months (18), first settlement month (13), and an annual discount rate (9%).
Total cost and total revenue: total cost is
GI.WEIGHTEDAVG("hardCost")× total gross area, marked up 15% for contingency; total revenue is total saleable area ×GI.WEIGHTEDAVG("salePrice").Monthly rows, one column per month: an S-curve weight (a sine curve that rises and falls across the build months), a construction cost draw (the total cost spread across months in proportion to that weight), a sales revenue draw (zero until the first settlement month, then the total revenue spread evenly across the remaining months), a net row (cost draw plus revenue draw), and a cumulative row (each month's net added to the running total).
Returns: NPV at the discount rate (
=NPV(discount_rate/12, net_row_range)), IRR monthly (=IRR(net_row_range)), and IRR annualised (=POWER(1+monthly_IRR,12)-1).
A line chart plots the cumulative position across the 24 months, the classic J-curve shape of a development's cash position. Drag the first month's date to move the whole programme, since every later month and formula follows it.
Build to sell vs build to rent
One residential scheme priced two ways: sold on completion, or let, held for ten years, and then sold. The workbook has three sheets, and opens on Inputs.
Inputs: the residential usage to price (Residential by default, and you can type another), then dwellings, gross floor area, saleable area, construction cost (
GI.SUMEACH("grossArea * hardCost")) and gross development value (GI.SUMEACH("saleableArea * salePrice")) for that usage, read from the model.Shared assumptions: land cost per dwelling (80,000), professional fees (10%), contingency (5%), finance rate (7%), and build period (24 months). Finance assumes land is drawn on day one and build cost is about half drawn on average.
Build to sell assumptions: selling costs (2.5%) and target profit on cost (20%).
Build to rent assumptions: rent per dwelling per month (3,000), other income per dwelling per month (100), vacancy and bad debt (4%), operating costs (28% of income), rental growth (3% a year), exit yield (4.75%), disposal costs (1.5%), and discount rate (7.5%).
Summary: sell and rent side by side for total development cost, profit at completion, profit on cost, yield on cost, unlevered IRR, and profit over the ten-year hold.
Build to sell sheet: revenue, costs, profit, profit on cost, margin on GDV, profit per dwelling, and the land value that hits your target profit, with the headroom over your land cost.
Build to rent sheet: a stabilised first year down to net operating income, the yield on cost and value on completion, and a ten-year hold with unlevered IRR, NPV, profit over the hold, and equity multiple.
A bar chart on the Build to rent sheet plots net cash flow by year. The workbook needs a residential usage with dwelling counts, areas, and hardCost and salePrice rates. Without them, the numbers show as zero.
Hotel appraisal
A hotel priced on its trading. Keys, room rate, and occupancy give revenue, a stack of percentage costs brings that down to net operating income, and a yield turns that into value to compare with cost per key.
Keys: worked out from the net area of your Hotel usage at 38 m² (or ft²) per key. If the project has no hotel modelled, the workbook uses 180 keys so it still shows numbers.
Assumptions: average daily rate (220), stabilised occupancy (76%), food and beverage (28% of rooms), other revenue (6% of rooms), departmental costs (32%), undistributed costs (24%), management fees (3%), FF&E reserve (4%), exit yield (7%), land per key (40,000), construction per key (250,000), FF&E and pre-opening per key (35,000), fees and contingency (15%), finance rate (7%), build period (30 months), and ADR growth (3% a year).
Stabilised year: RevPAR, rooms revenue, food and beverage, other revenue, and total revenue, down through costs and fees to net operating income and NOI margin.
Value and cost: value at the exit yield and per key, the development cost stack, total cost and cost per key, profit, profit on cost, and yield on cost.
Ramp-up: occupancy, ADR, revenue, and NOI for the first five years, with occupancy rising from 80% of stabilised to 100% by year three.
A bar chart plots revenue and NOI across the first five years.
Data centre appraisal
A data centre priced per megawatt of IT load instead of floor area. Rent is per kW and build cost is per MW. Power is passed through to the tenant at cost, so it isn't counted as income.
Capacity: IT load worked out from the net area of your Data Centre usage at 1.5 kW per m² (or ft²). If the project has no data hall modelled, the workbook uses 24 MW. A PUE of 1.3 gives the grid connection you need.
Assumptions: rent per kW of IT per month (140), stabilised occupancy (95%), operating costs (12% of rent), exit yield (6.5%), land and grid per MW (1,500,000), construction per MW (11,000,000), fees and contingency (12%), finance rate (7%), and build period (30 months).
Stabilised year: contracted rent, operating costs, and net operating income.
Value and cost: value at the exit yield and per MW, the development cost stack, total cost and cost per MW, profit, profit on cost, and yield on cost.
Lease-up: occupancy, rent, and NOI for the first five years, with occupancy rising from 40% of stabilised to 100% by year four.
A bar chart plots rent and NOI through lease-up.
The hotel and data centre workbooks look for usages named exactly Hotel and Data Centre. If your usages have other names, type yours into the usage cell at the top of the sheet.
You can build a schedule like these from scratch, and learn what happens to an example workbook once you start editing it.