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Our mission is happier and healthier animals and humans.

We put “happier” first, not “healthier”, because a life lived well and happily is preferred to a long but unhappy existence.

We measure impact primarily in increased life years and wellbeing, and secondarily in increased awareness and funds leading to optimal 100% life span and health.

Some of our impact is challenging to measure, such as rainforest purchase, although there is strong reason to believe that it is beneficial for species survival.

We prefer not to measure impact as an absolute, but as a change (delta Δ) of status before and after our intervention.

Our interventions aim for higher awareness, higher allocation of donated resources or volunteer hours, more life years and higher levels of wellbeing as well as increased species survival rate.

Impact Measurement

Measuring impact is impact in itself. Too often impact cannot be measured, and too often it is unclear how much impact is attributable to interventions, directly or indirectly.

Our impact measurement is based on facts and evidence as much as possible. If facts and evidence are insufficient, we take educated guesses regarding the estimated impact. If possible, we take into account counterfactuals, comparing, for example, option A or B against our intervention C. All our evaluations are based on available knowledge and therefore impact measurement for the past year would be readjusted in retrospective if new facts come to light.

We are looking at outputs, not inputs. Too often corporate sponsors, grant makers and donors talk about how much money was spent, instead of talking about health, social and environmental impact generated. To avoid this trap, we focus on output, which for us means life years and wellbeing of humans and animals.

Evaluating Impact Interventions

We believe that all life is priceless and has value. Every life counts, be it of a human or an animal.

In situations of life and death, of health and illness, of wellbeing and suffering, making decisions whether or not and how to intervene is very, very difficult.  Even the largest grant makers have limited resources, and decisions need to be made, sometimes in very urgent situations.

We aim to achieve the highest impact possible with the resources available. Our decision to intervene is made by comparing different options of intervention as well as taking no action at all. Where possible, we calculate the cost per impact unit to find the most efficient intervention.

We ask ourselves, for example, how much good could be achieved with a certain amount of money spent. If sufficient data is available, our evaluations might look like one of the following simplified examples:

  • Evaluating Intervention A: Assuming a $1 intervention saves one 5 year old child’s life and assuming the average lifespan of the respective population is 60 years, then a $1 intervention would add 55 life years (LY = 55) to the child’s life at the cost of $0.018 per 1 life year ($1 / 55).
  • Evaluating Intervention A vs B: Assuming an intervention A can save the life of a child with a heart disease for $500,000 in a first world hospital while an intervention B in a less developed country can save 5,000 children with vaccination that costs $100 per child, which intervention should we choose? In this example, the preferable intervention B would save 4,999 more lives. Or perhaps we should not intervene at all at this point of time, but instead choose to intervene later with a more effective approach (e.g. a solution which saves one life for $10) if there is reasonable belief that a better intervention C will become available soon?

Evaluations for Species Survival

The incredible loss of animal lives and the rate of species becoming extinct is horrifying. To evaluate possible impact of interventions, we first try to understand absolute loss and relative loss in population size over time.

For example, our closest relatives, orangutans, are sentient beings comparable to young human children, with self-awareness and clearly demonstrated intellect. Some conservationists therefore call the imminent orangutan extinction a genocide. Let’s assume the following:

  • 30,000 estimated orangutan deaths over the last 10 years (3,000 deaths per annum)
  • Average orangutan life span of 40 years, with death as a result of a natural cause (average LY = 40 per individual)
  • Average orangutan life span of 20 years, with death as a result of an unnatural cause (average LY = 20 per individual, instead of 40)

The result is 600,000 total life years lost to unnatural death causes over the last 10 years (30,000 kills x -20 LY = -600,000 LY).

The evaluation of our interventions would focus on the cost of lives saved.

Our interventions generally concentrate on smaller subsets of the target species with restricted distribution to impact a large proportion of the species’ population.

We are always keen on hearing from partners working in related fields or sponsors searching to support high-impact projects.

Please contact us to explore partnership and sponsorship opportunities.