You've just deployed new or edited computations. This means their definition is now stored in the library of computations.
Now to use them in a Customer Fit model, there is one more step to do before you can visualize it or use it in the model. This step is called "reloading your computations". Why? A model is based on a dataset, loaded at some point in time. If the dataset was loaded before new computations were deployed, then this dataset doesn't contain the new computation. Hence the need for reloading the computations calculated for the dataset.
How to reload computations
To reload your computation(s), go to the Overview section and click on Reload computations so that the datasets can be enriched with the new computation(s) you created.
Once the dataset is enriched and loaded, you should receive a confirmation email.
What reloading computations does
Reloading computations does 3 things:
 includes any new computation in the model where you reloaded computations
 updates any computation whose definition has been updated
 refreshes any existing computations
For example, on Dec 2021 you loaded a dataset, and the enrichment (computations) is as follows:
has converted  industry  employees  country 
employees combined 
hiring positions 

john@slack.com  yes  software  2,500  US  2,500  250 
mary@amplitude.com  no  software  400  US  400  20 
...  ...  ...  ...  ...  ...  ... 
A year later, you
 create a new computation called is competitor,
 change the definition of employees combined to prioritize Salesforce enrichment over MadKudu enrichment
 and you reload the computations
has converted  industry  employees  country 
employees combined 
hiring positions 
is competitor  
john@slack.com  yes  software  2,500  US  3,000  250  no 
mary@amplitude.com  no  software  400  US  650  40  yes 
...  ...  ...  ...  ...  ...  ...  ... 
The dataset enrichment therefore gets updated with the new computation and the new values of the existing computation "employees combined", according to its new definition.
The computation "hiring position" also changes as a company frequently opens and closes job opening and our provider PredictLeads sends us monthly fresh data.
Impact of reloading computations on a model
How does reloading computation impact a model?

You can now use new computations in the model: visualize the computation insights and use the computations for overrides, signals, tree nodes...
To visualize this computation on the training dataset for a model, head to Insights and search for the label of your computation to check out the result (learn more on How to read the Customer Fit insights). 
The distribution of scores in the model can change. When deploying your model the scores in your CRM can change even if you have not changed the model. Confused? Hang on you'll see
 Since the enrichment can change, the decision tree values can change and therefore the distribution of scores can change.
 Let's take an extreme example
Let's say you have a split in your decision tree separating companies with less than 500 employees. On Sept 2021, there were more companies with employees combined <= 500 than with > 500
A year later, you update the computation employees combined to prioritize your Salesforce enrichment over MadKudu enrichment, which has higher company size estimations than MadKudu enrichment. Therefore some companies that were in node 2 move to node 3 and now node 3 converts better than node 2.
and now larger companies get scored higher than smaller companies.
By just changing and reloading the computation, now your model has changed without you touching the configuration of the model itself. Therefore when you'll deploy the model the scores in your CRM may change.