My Investing Process and Tools


My mode of operation for learning and doing is to write what I learn and create tools that I can use.  I publish my content and tools so that hopefully others can benefit.

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.  


  • I use underline, caps, other text modifiers and symbols to help draw my attention to items.
  • I refer to this page constantly to keep me on track.
  • The main tools I use include a cloud-based database I built with many datasets (objects), Google Docs and Sheets, Evernote and Google Drive


My process on this page covers any level of investing, from startups through public opportunities.


Managing Information Flow

  • Hub Dataset 
    • All additions to my intelligence platform to help me retain information and use it for investing.


  1. Trends Dataset   
    • From research, trends roll into this dataset as a master overview. These are long-term trends. 
  2. Focus Dataset
    •  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.
  3. Current Investment Themes
    • From my research in the Trends and Focus datasets, I create high level investment themes to help guide investment decisions.
    • I RANK them based on current investment importance.
    • Investment Sub-Themes here
      • Another dataset that lists sub-themes to the main theme to help surface them for my information management purposes.
  4. Info Sources Dataset    
    • 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.
    • I RANK them and pay close attention to ones which have a high ranking. 
    • I keep my attention focused on those info sources that support my focus and investment themes.
    • I use a TASKS dataset and/or EVENTS dataset in my database to help remind me when to review these sources for any new information, but most of these sources automatically send new information because out via email, post to twitter, etc. or I setup search alerts.
  5. Startup & Early-Stage Project Growth Resources
    • This page is a FILTERED view of my Growth Resources Dataset  to only include those that represent good potential sources of startup and early-stage projects in which to invest.
    • I use a TASK LIST dataset and/or EVENT dataset in my database to help remind me when to review these sources for any new prospects they have supported which may be of interest to me.
  6. External Dataset
    1. I add external datasets that look interesting to this table. Could be anything I come across, whether publicly available or subscription/paid only.
  7. Data Lake  
    • This is unstructured data where all base research gets deposited.
    • It is folders or Evernote notes with embedded documents where base level content gets deposited.  
  8. Company/Project Dataset 
    • Structured data on companies and specific investments.
    • I am adding companies to this dataset all the time, even though most will not become an investment prospect, so I at least have a record that I looked at them. 
    • I rank them by LEVEL OF IMPORTANCE (named HIGH PRIORITY FILTER), so new ones added might get a high ranking and after additional research or over time, they may no longer be of investment interest, so I lower their rank so they stay out of this filter.
    • Other important FILTERS include:
      • Idea, startup and early-stage prospects (named STARTUP FILTER);
      • Prospects where I am working with them directly via mentoring, advising, consulting, providing services, etc. For these prospects, I keep a log of what I do for them via this dataset (named TRACKER SUMMARY).
  9. Business ideas Dataset 
    • Business ideas I come across or think up on my own.
    • I log them here so I do not forget about them and periodically review this list to see if they spark any new ideas.
  10. Future Planning    
    • 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.
    • I include everything professional and personal for my life in this tool, categorizing by month:
      • Events;
      • Opportunities;
      • Threats;
      • Upcoming accounting/financial-specific events
      • What to be on the lookout for that might not be tied specifically to a month or date range
      • I record what happened, including what was not anticipated so I can try and improve on the tool for the future.  
    • This helps me think through and list actions to do ahead of time based on what is upcoming. 
    • 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.  
  11. Q & A/Discussion Board    
    • Add Q&A and provide comments and discussion around any research in the datasets above. 
    • This dataset is really for any questions that might not be tied to a specific investment prospect, to help them stay top of mind so I can get answers to them.
    • I use a discussion board around each question because I have others which I allow access to my process and they can participate.

Investment Principles and Criteria

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


  1. Current Investment Strategy 
    • 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, short-term considerations, and how much I allocate to each theme, when to sell and, and risks to watch out for that may require me to change my investment strategy.
    • This high level document serves as a gut check
    • It helps keep me focused on the path when it is easy to get lost in the detail and go down rabbit holes.
  2. Decision Analysis    
    • If a company becomes an investment prospect, it is added to this dataset.
    • ANALYSIS FRAMEWORKS and WORKFLOWS:  there are varying levels of research and analysis done prior to reaching entry into this dataset.  A lot comes to me from other analysts I subscribe to (for public investment, for example), but for private startup and early-stage investing, I do the analysis myself using specific analysis frameworks and workflows I have created.
    • This dataset includes investment prospects to choose from based on INVESTMENT THEMES and RISK/RETURN CALCULATIONS  and PROJECTIONS.  But not all prospects, especially startups, have risk/return calculations as it is not feasible to try and project for them.
    • I include fields to record results and analysis if successful or not and why
    • Startup Filter 
      • This dataset FILTERS the Decision Analysis dataset to only include startup and early-stage investments.
  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
    • I update this spreadsheet to reflect current ownership and maintain transaction logs.   
  2. Decision Analysis   
    • 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  
    • Items get archived in same dataset where they live when they are no longer relevant.
  4. Loose Notes Page   
    • This is an Evernote created for each week of the year that includes links, documents and copied text from research to review.  Once all the items are reviewed, the note is archived.  Sometimes research builds up and runs into the next week so this note stays active until everything is completed.  
  5. Info Sources Report  
    • I track where a lot of my information originates.  This report counts helps me see which info sources are most valuable to track and keep my attention.   

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