Thanks for the response. My answers to your questions are in blue.

Please provide more context on your environment and setup:

1.  Who else and what else is using this machine when these things are being processed? Are other people using this solution at the same time?
   
   Currently this is on our development server. We have 4 users who have access to this server. Normally only one person, usually me, is using the server when this publication is being processed.
   1. A single server is not the minimum recommended approach for Pyramid (check the scaling guide in help). 
      
      We have 198 total users and have no where near 25% concurrent use in our production environment.
   2. Where is the database repository? it should not be on the same machine. It can slow things down considerably.
      
      The database repository is on a separate server.
   3. How many threads are you running concurrently? Too many concurrent threads, on a single machine no less,  will slow things down.
      
      There are about 4,000 concurrent threads
2. Have you looked at the query times in the transaction log.
   1. How long are the queries taking to resolve on your cubes?
      
      It's taking the queries 223,030 MS to run
       
   2. Are your cubes performing well in general?
      
      I am not a SSAS expert but we do have an outside consultant that monitors the health and performance of our cubes and ensure that they are running optimally. 
3. How many reports are you generating per batch?
   
   1 report per batch is being run
4. Is the server a VM? If so, is it sharing cores with other VM's, such that you do not truly have 12 cores fully at your disposal?
   
   It is a VM. I will have to do some checking with our IT team on the VM setup.
5. The 300 text elements are being driven off the 4 queries:
   
   Let me try to provide a little more context. There are 3 filters (College, Department, Major) on the Publication but it is the Major filter that is doing most of the heavy lifting. The College filter is only being used to populate a page heading placeholder, the Department filter is also used to populate the page heading plus filter 1 Discover and 1 dynamic text element. Major is what filters the rest of the data.
   1. If you have very large queries to answer so many figures, you should change them into several smaller queries that do less work. Large queries with irrelevant data impact performance - unless you are using every element to resolve the 300 items.
      
      I don't think these are particularly large queries. I am using approximately 32 Discovers to populate the dynamic text. These Discovers are looking at data for a 5 year period for undergraduate students filtered by Major. 
   2. Are your 300 items reading 300 independent objects and building them into sentences? You are better off constructing larger, whole sentences with multiple values that resolve from multiple data points, producing fewer DT objects.
      
      I am using Matrix tables with dynamic text populating the the cell values. I have attached a screenshot to show you what I am doing.