#### Discover more from Election Data Analyzer (EDA) Newsletter

Part 1 of this 2 part series is located here.

The objective of this article is to develop a cost model based on the data in 29 contracts which include 26 counties, 3 states from 4 different election machine vendors. The model is ONLY focused on those items listed in the contracts. The ACTUAL total cost of the elections is greater than just the contract costs of course.

## Assumptions

Any models accuracy is dependent on assumptions and those are listed below. To be clear the model presented here isn’t going to be accurate to 2 decimal places (LOL). I am concerned with costs of millions, tens of millions, hundreds of millions or billions.

#### Assumption 1

All 1,047 line items in the study were grouped into two categories.

One Time Fees

Reoccurring Fees

One time fees include hardware purchase, implementation support, project management and other misc hardware and software that would be purchased one time and used for the entire life cycle of 11 years. The 11 year life cycle is described in more detail in Part 1.

Reoccurring fees are predominantly those pertaining to warranty and software licensing. This was calculated for Year 2 for each jurisdiction and then an inflation factor of 3% was applied for years 2-11.

#### Assumption 2

I will assume an 11 year life cycle for the equipment before it needs to be replaced. This was detailed in Part 1. This means that “One Time Fees” are accrued in Year 1 and “Reoccurring Fees” are accrued from Year 2 - Year 11.

#### Assumption 3

The weighted average of the 29 jurisdictions “One Time Fee” and “Reoccurring Fees” are calculated as a way to calculate a cost model that can be scaled for the entire US. This is presented in tabular format below.

#### Assumption 4

For the sake of the model, let’s assume a baseline US total registration of 220MM.

## Analysis

This table is sorted from largest to smallest in terms of registrants.

The % Registrants determines the weighting of the contracts values for the model. For example, State 1 accounts for ~ 43% of the model costs because 43% of all registrants in the study are from State 1. The “One Time” column is the initial purchase price of hardware, software and other misc services. The “Year 2” column is the value of any warranty or software licensing listed in the contract. Some jurisdictions did not purchase a warranty or software licenses and I dealt with that at face value.

The columns above were ultimately used to calculate a weighted average of “One Time” costs and “Year 2” costs. The yearly costs were then ASSUMED to continue for another 10 years even though in some cases, the jurisdiction only purchased, say 8 years worth of warranty coverage. For the sake of the model, I assume some cost of ownership needs to be incurred for the entire period.

The next table accounts for reoccurring costs and inflation at 3% on a per Registrant basis.

The cumulative cost of the initial investment and the reoccurring costs on a simple weighted average basis is $20.39. This is the entire point of this simplified model. In other words, it takes $20.39 per registrant on average to purchase and maintain these systems for 11 years based on the assumptions of this model.

Scaling this for the entire United States this would lead to this calculation

220,000,000 x $20.39 = $4,485,800,000 every 11 years.

Maybe the REAL number is 3 Billion or maybe it is 6 Billion, but it certainly is not 800MM or 10Billion every 11 years.

## Final Editorial Comments

Think of it, ~ 4 Billion tax dollars are spent, then some of that comes back from the vendors to the politicians in terms of political donations. The rest goes to for-profit companies, some of whom have foreign ownership.

We then repeat this cycle every 11 years, or so, when the technology reaches end of life.

How about instead keeping these tax dollars in our local communities and employing PEOPLE to count the votes instead of using “black boxes”?

How much would each person be paid to count the votes? Ahhh, that will have to wait for another article perhaps.

Please share this if you have made it this far or leave a comment below.

Thanks