Capture of the result of a 9 box that evaluates potential and performance

April 13, 2020

How to make a 9-Box Talent Matrix (Nine Box)

What is a 9 Box Matrix?

The Talent Maps or Talent Matrixes, usually presented in a 9-box (or box) format, are a tool with which we can identify our key employees: those who show career potential in the organization and high performance. In this way, we can have a visual map on which to position each employee and ensure that their professional development needs are kept up to date, that they feel engaged in the organization, and that they assess their ability to become leadership benchmarks; look at your strongest contributors and determine what they need to keep pace on their journey, or if they show potential, help them develop it with the right initiatives; and finally, it allows us to identify people who are not performing well and don't seem to have the potential to improve.

What data is related in a 9 Box Matrix?

A 9-box matrix, or talent matrix, allows us to classify the people in an organization according to the results of two assessments, usually a potential assessment and a performance assessment.

For those of you who already know what a 9-box is, in this post we will explain how to easily create them with Hrider.

Graphically, we use a map divided into 9 quadrants is used (hence the 9-Box), where the Y-axis is the score obtained from Potential and the X-axis is the score obtained from Performance. Therefore, each person evaluated will have a single quadrant, the one that contains the coordinate resulting from his or her scores (X, Y).

For example, an appraisee with a score of 90 in Potential and 90 in Performance will correspond to box number 1, while an apraisee with a socre of 50 in Potential 90 in Performance will correspond to box number 3.

In Hrider you will be able to create not only talent matrixes with 9 quadrants, but you can also do it with 4, 16 and 25 quadrants, it is what we call an N-Box:

For a 9-Box the quadrants go from 1 to 9 and their default labels are:

5. Enigma.
2. High potential.
1. Super star.
8. Dilemma.
6. Key employee.
3. Star in your area.
9. Consider post.
7. Good performance.
4. Excellent performance.

These labels as well as the colors are fully configurable, you can change them, even change the color and number of each of the quadrants if you wish.


We are going to give you in a detail way the steps to create your own talent matrix:

Step 1: Create a new evaluation type N-Box

From the Evaluations section, click on the "New" button and in the wizard select the option N-Box.

Step 2: Select the initial data

To populate the N-Box you have two options, choose two already completed evaluations, one for the Y axis, and another for the X axis. Or, create an empty N-Box and then import the results from a file Excel.

Step 3: Add the rest of the data

Whether you selected two reports in the previous step or decided to create it empty, you can add people individually using the "Add Person" button on the toolbar, or you can do it massively by importing an Excel file. You can do this whenever you want, the data will be automatically added to the current N-Box to reflect the changes. This import option is very useful if you had the data in another system and now want to have it in your HRIder account.
Once populated, you will be able to see the people distributed in the N-Box in their respective quadrants:

Among other functions, you can move the mouse over a person to see their data, zoom in on the graph, change its size or calibrate a person's scores.

Step 4: Calibration

The calibration process allows us to change the current coordinates that correspond to a person, and thus the quadrant to which they are assigned.
Depending on the initiatives in which we want each employee to participate, it will be more appropriate for us to place them in one or another box of our talent matrix. In addition, calibration allows us to homogenize the criteria by which each person has been evaluated by pooling all the results.
To calibrate, we simply select the person in the graph and press the "Calibrate" button, which allows us to set new values for both the X and Y coordinates. Once the changes have been confirmed, the graph now shows the person in his new position, with a dashed line marking the original position he had before calibration.


Step 5: Configuration

Finally, as usual the configuration options are excellent with Hrider. From the "Settings" section, you can change the name of the axes, the dimensions of the N-Box, you can go from one of 9 quadrants to one of 16, 25 or 4, at any time, also you can change the colors of each quadrant, the number they are assigned and their label.

Use Cases 

The 9-Box is a versatile tool that can be used in a variety of talent management and organisational development scenarios. Some of the most common use cases for the 9-Box include:
· Identifying high-potential talent: It allows for the identification of high performing employees with potential for future development within the organisation.
· Succession planning: Assists at identifying and developing employees who could fill key positions in the future, thus facilitating succession planning.
· Performance management: Facilitates the interpretation of performance evaluations and helps identify areas for improvement and development.
· Development decision-making and resource allocation: Enables HR leaders to make strategic decisions about development more effectively by identifying areas where more attention is needed.
· Strategic human resources planning: Helps leaders make informed decisions about human resource allocation and talent development to support the organisation's strategic objectives.

Standardisation of scores in the 9 Box

When assessing who stands out the most in our teams, taking into consideration performance and potential, we sometimes face a challenge: original scores may appear uniform, resulting in people clustering in a single quadrant rather than being distributed across our N-Box. To overcome this difficulty and make the information on the chart more useful, we can standardise the scores. This helps us better understand the differences among contributors, as they are centred around an optimal value, the mean, and scaled according to the standard deviation.
In standardisation, also known as z-score normalisation, data is centred and scaled so that it has a mean of 0 and a standard deviation of 1. This is achieved by subtracting the mean from each value and dividing by the standard deviation. The formula for standardising a variable is 𝑧 = ( 𝑥 −𝜇 )/𝜎 where 𝜇 is the mean of the variable and 𝜎 is the standard deviation.
By standardising the data, the original measurement units are removed, making it easier to compare different variables that may have different scales and units.