A useful indicator answers a decision, not a curiosity
Many property dashboards pile up numbers that are accurate but inert: contacts this month, calls made, viewings held. These volumes read well in a meeting and almost never change a decision. The question to ask before adding a line is simple: if this number doubles or collapses, what do I do differently tomorrow?
An indicator earns its place when it points to an action: follow up on a segment of prospects, review the price of a property type that is not selling, reinforce a team on one project, or work through a list of overdue records. If it only leads to a comment, it belongs in the report, not on the dashboard.
Three to five indicators tracked seriously beat twenty consulted once a quarter.
1. Stock absorption, by project and by property type
This is the structuring indicator in property development: how much of the inventory has sold, at what pace, and how long the rest will last at the current pace. Read across a whole project, it usually hides what matters. Read by property type, it shows three-room units selling while the larger floor areas stall.
Pace matters as much as the cumulative figure. A project that is half sold may be healthy or stalled for two months, depending on how reservations are spread over time. Tracking reservations per period, not only the total, keeps a strong launch from being mistaken for sales that are still moving.
- Available, optioned, reserved and sold inventory, per project.
- The same breakdown by property type and by phase.
- Reservations per month, not just the running total.
- Remaining inventory measured against the pace of recent periods.
2. Conversion between stages, not the volume of contacts
The volume of incoming prospects mostly tells you how much you spent on visibility. What can be managed is the move from one stage to the next: qualified contact, viewing held, option placed, reservation signed. A clear drop between two stages locates the problem far faster than an overall conversion rate.
That assumes the stages mean the same thing to everyone. If « qualified » means « picked up the phone » to one person and « has a verified budget » to another, the rate no longer measures anything. Defining the stages is a team decision, to be written down before measuring.
- The step between each stage, rather than a single overall rate.
- A written, shared definition of every stage.
- The same measure by lead source, so you compare like with like.
- The average time spent in each stage, which reveals bottlenecks.
A conversion rate only means something if the starting and ending stages are defined the same way across the whole team.
3. Cycle time and the age of open records
The time between first contact and reservation drives the sales forecast. But the average on its own is misleading: a few very long records pull it upwards without saying anything about the majority. It is more useful to look at the spread, and above all at the age of the records still open.
A record with no movement for several weeks is not a record in progress: it is a decision that has not been made. Tracking the time since the last action produces a concrete worklist, which an average cycle time never will.
- The spread of cycle times, not only the average.
- The age of each open record since its last action.
- The number of records with no next action scheduled.
- Active records per salesperson, to spot overloaded portfolios.
4. Actual collections, kept separate from signed revenue
A signed reservation is not cash received. The sales dashboard has to keep that distinction visible, otherwise management steers on revenue that has not arrived yet. Three readings are enough: what the payment schedule plans, what is due today, and what has been collected.
The indicator that triggers the most action is how long a payment has been overdue. An amount ten days late and an amount four months late do not call for the same treatment, and adding them into a single total makes the urgency disappear.
- Planned, due and collected amounts, per project.
- Overdue amounts grouped by age, not merged into one total.
- Every payment attached to its record and its unit.
- Signed reservations with no payment schedule attached.
The most common traps when reading the numbers
The first trap is averaging across situations that have nothing in common: mixing a project at launch with one at the end of its sales cycle produces a number nobody can use. Segmenting by project, property type and period is almost always more informative than consolidating.
The second trap is the silent change of definition. If the qualification rule changes mid-year, the historical series becomes incomparable without the chart signalling it. Noting the date of rule changes next to the indicator prevents false conclusions about a trend.
The third trap is the indicator nobody can move. A number that depends entirely on the market or on buyer financing is worth knowing, but it does not belong at the same level as indicators the team actually acts on.
- Segment before consolidating.
- Date every change of definition.
- Separate what the team drives from what it absorbs.
- Check that an indicator always leads back to the records behind it.
Build the dashboard starting from the decisions
The fastest method is to list the recurring decisions first: whether to push a property type, reinforce a project, adjust a price, or chase overdue payments. Each decision calls for one or two indicators, and the list naturally stops at a reasonable size.
Every figure on display must open up to the records it aggregates. An indicator that does not lead to a concrete list of actions ends up being challenged in meetings, then ignored. It is also the best protection against data-entry gaps: errors become visible once you can drill down to the record.
A dashboard is judged on one thing: how many decisions it let you take earlier.
Frequently asked questions
How many indicators should we start with?
Three to five are enough to begin: stock absorption by property type, conversion between two key stages, the age of open records, and actual collections. The list can grow once those figures are reliable and genuinely used in meetings.
How often should these KPIs be reviewed?
Worklists — records with no movement, overdue instalments — are worth checking weekly. Trend indicators such as absorption or cycle times are read monthly: at a shorter interval, noise outweighs signal.
Should we compare our rates to market averages?
With caution. Published rates rarely rest on the same stage definitions as yours, which makes the comparison unreliable. Your own historical series, with constant definitions, is a firmer benchmark.
How do we stop the numbers being challenged in meetings?
By making every indicator traceable down to the records behind it, and by fixing each stage definition in writing. The discussion then turns to the decision to take rather than to whether the figure is valid.