Startup decision making: Avoiding the composition fallacy

By: Phillip Bogdanovich

In business, and especially in business operations, feelings should be last on the list of considerations affecting an outcome or decision. For most people, this is easier said than done. We interact with our landscape through a lens that we’ve spent a lifetime building, and it’s tremendously difficult (sometimes impossible) to step beyond ourselves and be objective. Business can get emotional. There are egos and politics (and money) at play.

Objectivity is critical, however, because the solution you want or feel strongly about may not be the best one for the business. Let’s say you’re assembling a team for a special project. You want to make sure a certain manager is part of that team. She is smart, well-regarded, and a personal favorite of yours because of another project you worked on together. Being the right choice for the previous team must mean she’s right for this team as well.

This kind of thinking is called the Composition Fallacy: If the parts of the whole look good, the whole must be good. This thinking is lazy. It stops at first impressions and fails to take into account the system in its entirety. Your personal feeling about this manager has no bearing on whether she is the best fit for the project. Instead of focusing on your experience with her, you should be evaluating how she will work with others on the team, her expertise relative to the project requirements, the impact on the business as a whole if you ask her to devote time to this project, and so on. You should be objectively evaluating the matrix of variables associated with your decision.

The good news is that the more aware you are of your own perspective, the more actively you can combat the Composition Fallacy. The more you ask yourself, “Am I being honest or am I being sensitive? Am I seeing this outcome because it’s real or because I want to see it?,” the better you will become at problem-solving and growing your business.

I’ve had years (and plenty of problems) to develop a system for making decisions and evaluating the success of my solutions. I identify the problem, break it down into components, and turn those components into numbers I can manipulate and measure. This simple framework can be applied problems of any size and complexity. If you’re feeling stuck (or you think “the feels” might be getting the best of you), walk through these steps.
Write it down.
Start by defining your problem. It’s OK for it to change over time. You might start with “I want greener grass in my backyard,” do some research, and refine your problem to “I need to decrease the pH balance of my yard to allow for greener grass.” For the purposes of this post, let’s use this common business scenario:

I have outgrown my office space and I still need to hire more people. How large of a space should I move into?

Break it down.
The problem of too little office space does not exist in a vacuum. Many factors contribute to the cost of an office and how your business should adjust to be able to shoulder the expense of a larger one. Before you can make any decisions, you need to identify what those factors are. Define the universe of your problem.

In this scenario, we need to look at our current revenue and burn versus our projected revenue and burn in a larger office with several new employees. What size office will offer enough space for our projected employee count (and room to grow), but not so much space that we find ourselves underwater on rent? What is our cost and revenue per square foot?

• Minimum square footage needed per employee
• Number of employees (including new hires)
• Average cost (pay/salary) per employee
• Labor-related monthly burn per square foot
• Non-labor-related monthly burn per square foot
• Monthly revenue (total and per sales rep)

Assign value.
Figure out what goes into calculating each of your contributing factors, and assign measurable value—a percentage, a number, or even something as simple as a binary “present / not present”—wherever you can.

  • Current monthly burn rate $60,000
  • Current monthly revenue $70,000
  • Current sales staff 2
  • Current non-sales staff 10
  • Average monthly cost (pay/salary) per sales agent $5,000
  • Average monthly cost for non-sales employees $3,000
  • Current square footage 2,000
  • Current monthly rent $4,000
  • Hiring plan 1 additional sales rep and 2 additional non-sales staff
  • Minimum square footage needed per sales agent 50
  • Current monthly labor burn $40,000 or $20 per sqft
  • Current monthly non-labor burn $20,000 or $10 per sqft
  • Monthly labor burn per square foot in larger office with new hires Depends on square footage of new office
  • Monthly non-labor burn per square foot in larger office with new hires Depends on square footage of new office

Identify the levers.
Identify which values in your list can be adjusted to positively affect your outcomes and help you move towards a solution to your problem. Then determine which of these can be moved the least to create the biggest impact. Research who else has solved a similar problem efficiently, and how they did it. It’s not unusual for cost to be a significant driver, offering the greatest movement for the least amount of change.

In this scenario, we do our research and learn that when companies like us evaluate moving, the most successful ones allocate 20% of their cash to rent. If we have $10,000 of available free cash per month ($70,000 revenue minus $60,000 burn) we should allocate $2,000 for rent increase. Assuming we find a new office with the same cost per square foot as our current office ($2.00), that $2,000 will get us 1,000 in extra square footage, more than enough to support our staffing needs. Now all we need to do is look at properties on the market and plug numbers into our matrix.
Pull the levers.
Evaluate your options with an open mind to see how the values you identified interact with one another and which combinations lead to the most desirable outcome for you. You might be choosing between a more expensive office in a sexier zip code, a cheaper but barely-big-enough office, and an office that just “felt” right when you walked in. If you plug the variables for each of those into your matrix, you will arrive at the best choice—regardless of how you feel about it. It’s your job to do what’s best for the business, and now you have numbers to tell you what that is.

In this scenario, a new office with 3,000 square feet for $6,000 a month turns out to be the best choice:

  • New monthly burn with 3 new employees plus non-labor cost per square foot increase $87,000 (approx. within 3%)
  • New monthly revenue (based on $35,000 average monthly revenue per sales rep) $105,000
  • Net new revenue $18,000
  • Change in net revenue with larger office and 3 new employees +$8,000
  • Change in efficiency +3%

Surprise yourself.
The matrix we just built shows that by investing $2,000 in space and making the hires we had planned, we would increase operating efficiency by 3% and net profitability by $8,000—a 4X return on investment. Instead of choosing an office because it “felt” right, we were able to break a complex, potentially emotional problem down into components we could manipulate and understand.

Startups can’t run on feelings. Hope is not a strategy. Luck should not be part of any business plan. Fortunately, objectivity is a skill that grows with practice like any other. So be dynamic, be objective, and build a matrix.

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