Entrepreneurship is an Experiment

entrepreneurship-experiment

By Jon Isaacson

If we were honest with ourselves, we would admit as entrepreneurs that we make decisions based on our gut feelings. We think we are objective, but research shows that for most of us, our biggest blindspot is our own bias. We are not as objective as we think.

Some business leaders pride themselves on their presumed innate abilities to make the right decision, or at least they don’t interject when others proclaim their greatness. Others are more subtle, crediting their data-driven process for them making the right calls. Everyone uses a blend of the objective as well as the subjective. The ability to track, interpret, and apply data to our entrepreneurial experiments is a key differentiator in those organizations that are able to remain competitive year-to-year.  

Using data will increase your ability to make better decisions and achieve better outcomes for your entrepreneurial experiments.  

Setting the parameters of your experiment

If you want to test a theory or hypothesis, as a scientist, you would start with some form of data. For the business owner in the skilled trades, this initial “data” may be your own experience. For example, whenever managers get together to discuss the performance of project managers, they often say, “In my experience, each project manager needs to be able to produce $1-1.2 million dollars of revenue per year in order for our business to be successful.” Is this commonly held metric based upon facts and years of data analysis or is it one of those comparative myths that we accept as an industry standard? For our purposes, we will not argue whether this goal is realistic. Instead, we will discuss how to use it as a starting point to create a few key data points (objectivity) to test this entrepreneurial hypothesis.  

Hypothesis: A skilled project manager should be able to close $1-1.2 million dollars of revenue in a fiscal year to contribute to the success of our business.  

Collecting the data for your experiment

Our initial “data sets” (aka gut feeling) tell us that each project manager needs to produce $1-1.2 million dollars in revenue each year or they are not meeting the industry norms and their business will fail. Where do we go from here?  

Data sets for the project manager  

  • What is $1.2M per month?  
  • What is $1.2M per week?  

Data sets for the business  

  • What is our average job size?  
  • What is our average close rate (leads converted to contracted work)?
  • How many leads do we need per month to be on track with our revenue goals?  

Leads _______ x Close rate ________ x Average job size _________ = On track / Off track

For you to move your business from having a fighting chance to competing year after year, you need to add basic data to your modus operandi. While our gut (subjectivity) may have gotten us to a certain level of success, to build on our momentum, it is important to add objectivity to our process.  

In another article we recently shared, we discussed this subject:

Data does not have to be complicated to be useful. Gathering, analyzing, and applying data to a business serves as the checks and balances for entrepreneurs who are developing their professional skills and adapting their business year over year.”

Data collection starts as soon as the phone rings. For episode 86 of The DYOJO Podcast, we introduce how to create a clear and consistent client intake process. From there, the contractor begins to update their Project Tracker (data) so that they can keep a consistent flow throughout the project lifecycle. We go further into these topics in Episode 89 where we discuss key client details and overall work metrics, including:  

  • How many leads did we receive?  
  • Where did the leads originate from?  
  • How many leads did we convert to contracted work?  
  • What was the average job size (in dollars) for our contracted work?  
  • How close were we to meeting our lead generation goals?  
  • How close were we to meeting our contracted work goals?  

Analyzing the data from your experiment

You should be tracking how many leads you receive in a given month and what sources they originate from. For example, a few key categories might be:

  • Leads from pay-to-play sources (I.E. online services or third-party administrators)  
  • Leads that are paid for from referral partners  
  • Leads that are paid for from online means (i.e. SEO, social media, etc)  
  • Leads that are word-of-mouth (non-paid aka THE BEST KIND)

Every contractor aspires to increase their word-of-mouth leads, as these originate from customers and partners who believe in the value of their services as well as the quality of their process. As we discuss in How To Suck Less At Estimating, collecting this data and reviewing it at least once a week with your team is critical to achieving your goals. If you swore to yourself you would only open up third-party (TPA) work for certain markets as a small percentage of your overall business, it is only with data that you can objectively determine whether it has been a net positive or negative for your business.  

Data: Project manager report card

    • Goal/hypothesis: $1.2 Million for the year  
    • Weekly production pace = $23,000.00
    • Monthly close goal = $100,000.00  
    • End of month five progress check = $388,000.00  
  • How much of a delta does PM ‘A’ have?  

Making decisions using the data from your experiment  

As a business owner and/or a person in a position of leadership, your decisions and outcomes will benefit from being able to refer to your data to answer key questions:

  • How many leads did we convert to contracted work in the prior month?  
  • Are we on track for meeting our goals this month?  
  • Is Project Manager ‘A’ on track to meet their quarterly goals?  
  • Which referral source has been the most productive?  
  • Which referral sources have been the most profitable?  
  • Why has our job size average dipped so much in the month of _____?  

As it relates to our project manager productivity hypothesis, now that we are gathering some basic data, we can check month-to-month whether they are on track or off-track to meet their goals. With basic data, we can make more informed investigations into why they may be off track as well as where they could make some key changes to produce better outcomes. In the book, So, You Want To Be A Project Manager, we discuss how the management of a project is a team process. The goal should not be to weaponize the data against our team members but to utilize it in ways that help the whole organization to make progress on the vision.  

Data: Project manager remedial plan

  • End of month five progress check = $388,000.00  
  • Status = $112,000.00 off track
  • What would you do with Project Manager ‘A’ €”would you discipline them or put them on a plan of improvement?  
  • Remedial action: (1) PM ‘A’ has three projects over $30k that are pending payment over 90 days; PM ‘A’ has not been following through on the payments, focusing on the collection with assistance from accounts payable. (2) Discovered that PM ‘A’ has an issue with cabinet delays on two other projects which should have closed within this time frame as well; work on sourcing another vendor. (3) Bi-weekly meetings with the production manager to ensure new projects are set up with a proper schedule, budget, and resource allocation.  

By declaring our vision, we can set up some quantifiable metrics for success. Doing so is of great benefit to the business as well as the individuals. Our data may show that our hypothesis was wrong, but with data, we don’t have to wait until the end of the year to discover this harsh reality. With basic data, we can look at the fifth month of the year and see that we are not on track. With basic data, we can have helpful conversations about what the sources for being off-pace are and develop a plan to succeed as a team. Even basic data will increase your ability to make better decisions and achieve better outcomes for your business.  


Jon Isaacson, known as the “Intentional Restorer,” is a contractor, author, and the host of the DYOJO Podcast. Jon speaks, writes, and coaches start-up phase owners and growth-minded restoration professionals through his organization, The DYOJO. Isaacson is the author of the Be Intentional book series for restorers. Reach him at  [email protected].  

 

Jon Isaacson

Jon Isaacson, known as the “Intentional Restorer,” is a contractor, an author, and the host of the DYOJO Podcast. Jon speaks, writes, and coaches start-up phase owners and growth-minded restoration professionals through his organization, The DYOJO. Isaacson is the author of the Be Intentional book series for restorers. Reach him at [email protected].

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