I have a KPI for Actual vs Forecast. Where can I f...
# ask-stanley-ai
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I have a KPI for Actual vs Forecast. Where can I find where the data is getting pulled?
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AI generated answer (using internal Slack threads):
The data for the KPI of Actual vs Forecast is typically pulled from the financial data within your NetSuite system. This includes your actual sales, expenses, and other financial data, as well as your forecasted data which is usually inputted into the system based on your budget or financial projections. To find where this data is getting pulled from, you can navigate to the KPI setup in your dashboard. Here's how: 1. Go to your NetSuite dashboard. 2. Find the Key Performance Indicators (KPI) portlet. If it's not there, you can add it by clicking on 'Personalize Dashboard', then 'Add Portlet', and select 'Key Performance Indicators'. 3. In the KPI portlet, click on 'Set Up' which is usually located at the top right corner of the portlet. 4. In the setup screen, you can see a list of all the KPIs that are currently set up in your dashboard. Find your 'Actual vs Forecast' KPI in this list. 5. Once you find it, you can see the source of the data for this KPI. It's usually a specific financial report or a saved search that pulls the data from your financial records. Remember, the specific setup might vary depending on your NetSuite configuration and the specific KPI you're looking at. If you're not sure, you might need to consult with your NetSuite administrator or the person who set up the KPI. ****** Disclaimer: This response was generated by an artificial intelligence assistant based on previous conversations from multiple Slack channels, and may contain inaccuracies or mistakes. ******
Slack thread 1: here (available only if the original thread was posted in the last 90 days)
Similarity score: 0.806640685
Slack thread 2: here (available only if the original thread was posted in the last 90 days)
Similarity score: 0.805419922
Slack thread 3: here (available only if the original thread was posted in the last 90 days)
Similarity score: 0.804992676
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