Investing Process and Tools


The process below is iterative and feeds back on itself. 

  1. Do research to identify trends – long, medium, short term – then prospects that fit the trends;
  2. Make investments based on investment criteria;
  3. Learn from successes and failures and document;
  4. Adjust investment criteria, then invest again based on research.  

Some links below are open and do not require login.


This process is for all levels of investing that I do, from early-stage startups to later-stage VC/PE backed pre-IPO and public companies. 



  1. Info Sources Dataset (login required).  Where research and data comes from. This dataset includes many free and paid sources, which I maintain and I cross-reference with most of the items below. 
  2. Data Lake (login required). Structured and unstructured data where all base research gets deposited.
  3. Company/Investment Dataset (login required).  Structured data on companies and specific investments, which contains structured info on them and links to that info in the Data Lake.
  4. Business ideas Dataset (login required). Business ideas I come across or think up on my own.
  5. Trends Dataset (login required).  From research, trends roll into this dataset as a master overview. These are long-term trends. 
  6. Focus Dataset (login required). Based on long-term trends (Trends Dataset), this dataset helps to narrow focus where I think I should be in terms of sectors, industries and specific markets for investment.
  7. Current Investment Themes. From my research in the Trends and Focus datasets, I create high level investment themes to help guide investment decisions. Investment Sub-Themes here.
  8. Future Planning (login required).  Short-term outlook (less than 1-yr) that attempts to put the information contained in the Trends and Focus datasets along with possibilities and events (known or anticipated) to a calendar that affects me and requires action from me.  This helps me think through and list actions to do ahead of time based on upcoming potential outcomes. This is a graphic like a Gant chart. While trends and focus datasets help narrow the where and why, this Gant chart attempts to layer on timing, or when to do the where/why.  
  9. Q & A/Discussion Board (login required).  Add Q&A and provide comments and discussion around any research in the datasets above.  
  10. Unclassified Dataset. This dataset is where I compile information that I want to keep but which either does not necessarily fit anywhere else in my organizational structure, or is information that is likely to become obsolete in the future.

Investment Principles and Criteria

  1. Securities Investment Principles (login required). A dataset of timeless principles to help with securities investing that I add to and maintain.
  2. Investment Criteria and SOP’s (login required).  This details my investment criteria, including style, trading strategies and screens.  I also include my standard operating procedures on what to do and when in terms of researching prospects, making and managing investments.  


  1. Current Investment Strategy (login required). I roll up all my research into a summary document that defines my current investment strategy, including the specific investment themes I am targeting, the upside and downside risks, and how much I allocate to each theme.
  2. Decision Analysis (login required).  This dataset includes investment prospects to choose from based on investment themes and risk/return calculations and projections.  I also include fields to record results and analysis if successful or not and why. 
  3. Investments Tracker (see template below). This spreadsheet tracks positions and near real-time results.   
  4. Current investments. My current list of investment prospects from which to choose.


  1. Investments Tracker. When I sell an investment, its row data gets copied into the transactions list, as well as in the net income sheet to track overall profits and losses. 
  2. Decision Analysis (login required).  Once exited from an investment, I try to include why sold, outcome, and analysis.  For long-term holds that not yet exited, I might update each prospect’s record entry with results to date and learnings. 
  3. Focus Dataset (login required). Items get archived in same dataset where they live when they are no longer relevant.
  4. Investing Log.  A Google doc that includes daily updates on what I do, learn, and what happens.  Keeping a daily log helps me track the minutia of what I am doing, which I roll up as needed into the above datasets.  See past weeks archives here (login required).
  5. Info Sources Report (login required).  I track where all my information originates.  This report counts the number of times an info source is referenced in my datasets. This helps me see which info sources are most valuable to track and keep my attention.


  1. Dataset/Database Documentation. Database architecture for the objects listed on this page.
  2. Soehnel Family Trust (login required).  See this page for a link to the data lake for all trust administration folders and files.
  3. Investments Tracker. This link is the template for the Google Sheets/Excel file.

Sector/Industry Specific Research

  1. Healthcare Research (login required).
  2. Digital Assets Research (login required).
  3. NFT Framework
  4. NFT Strategy Framework For Offline Artists