Projections

The Projections Input Table is a tool used exclusively by managers to set future performance goals for their team members.

In this section, you define the specific targets you expect your team to achieve. Whether based on historical performance or future business needs, you can set minimums and goals for any team member. These projections allow you to clearly establish expectations.

Examples of targets you can set include:

The number of calls to book by a setter.
The net revenue to generate by a closer.
A specific close rate percentage to achieve.

Once set, these targets serve as a benchmark, allowing you to track your team's progress over various timeframes (weekly, monthly or yearly) to see how they are performing against the established goals.

Below is a preview of how this page looks:

If in doubt, remember that every term has a detailed definition and can be found in the Glossary of Variables.

Glossary of Variables

The columns highlighted in the picture are the ones that the user is meant to modify and must be correctly completed to ensure accurate and appropriate reporting of each projection. You don’t need to—and won’t be able to—modify the other columns, as they are there to help you track the status of each projection you’ve set as the projector.

The modifiable columns include: Name ('Clients'), Name ('Team'), Variable, Frequency, Start Date 📅, Bare-ass Minimum, Goal, Progress.

Each of these fields plays a vital role in defining what is being tracked, over what period, and how much progress has been made.

Filling out these fields accurately is essential. They enable us to track each team member’s performance, measure whether they are meeting minimum standards, and help identify what is working, what is not, and how to support the team’s improvement. Without this information, we lack the clarity needed to make informed decisions.

The system has been designed to facilitate easy and accurate completion of all tasks. If any required field is left blank or if the entered information doesn’t make sense, the system will automatically detect the issue and flag it in the "NOT_filled" column. When the entry is complete and correct, this column will show “Good”. If something is missing or inconsistent, an “Error” message will be displayed, indicating that an item needs to be reviewed or corrected.

To help you fully understand how it works, let’s look at two examples—one correctly filled and one with errors.

To give some context, this is a test dashboard where the client is named "Test," and the only sales rep is labeled "Testing." In a real scenario, you would replace "Test" with the actual business name and "Testing" with the relevant team member's name.

Here is a visual example of how a row should be filled out correctly to ensure all data is processed without issues:
If any key data is missing or wrong, the system will turn the missing cells red like this:

Las columnas resaltadas en la imagen son las que el usuario debe modificar y deben completarse correctamente para asegurar un reporte preciso y adecuado de cada proyección. No necesitas —y no podrás— modificar las demás columnas, ya que están ahí para ayudarte a hacer seguimiento del estado de cada proyección que hayas definido como el proyector.

Las columnas modificables incluyen: Name ('Clients'), Name ('Team'), Variable, Frequency, Start Date 📅, Bare-ass Minimum, Goal, Progress.

Cada uno de estos campos cumple un papel fundamental al definir qué se está siguiendo, durante qué periodo y cuánto progreso se ha logrado.

Completar estos campos con precisión es esencial. Nos permite hacer seguimiento del rendimiento de cada miembro del equipo, medir si están cumpliendo con los estándares mínimos y ayudar a identificar qué está funcionando, qué no, y cómo apoyar la mejora del equipo. Sin esta información, no tendríamos la claridad necesaria para tomar decisiones informadas.

El sistema ha sido diseñado para facilitar la realización de todas las tareas de forma sencilla y precisa. Si algún campo obligatorio queda en blanco o la información ingresada no tiene sentido, el sistema detectará automáticamente el problema y lo marcará en la columna “NOT_filled”. Cuando la entrada esté completa y correcta, esta columna mostrará “Good”. Si falta algo o hay inconsistencias, mostrará “Error”, indicando que se debe revisar o corregir algún elemento.

Para que comprendas completamente cómo funciona, veamos dos ejemplos: uno correctamente completado y otro con errores.

Para darte un poco de contexto, este es un panel de prueba donde el cliente se llama “Test” y el único representante de ventas está etiquetado como “Testing”. En un escenario real, reemplazarías “Test” con el nombre real del negocio y “Testing” con el nombre del miembro del equipo correspondiente.

Aquí tienes un ejemplo visual de cómo debe completarse una fila correctamente para asegurar que todos los datos se procesen sin problemas:
Si falta algún dato clave o es incorrecto, el sistema resaltará las celdas faltantes en rojo, así:

You already know that the system highlights any mistakes made, but what exactly qualifies as a mistake? Let’s explore some specific cases with visual examples to clarify this.

The start date must match the selected frequency—weekly projections must begin on the first day of the week, monthly on the first day of the month, and yearly on the first day of the year. Here you have some examples:
The most common error could be missing data; a projection cannot have missing data, as it would be flagged. Here you have some examples:
Another mistake is that the Bare-ass Minimum cannot be higher than the Goal.