Impact on people

Many organisations will aim to improve people's lives. This leads to an important question of how we can understand and better analyse impact being created (e.g. if we want to compare two strategic choices or two investment options). The Impact Management Project provides a useful framework to break down impact on people into five dimensions.

Here is a template based on IMP which may help you to assess your impact on people.

What changes occur to people's lives?

Not all outcomes are equal. At a high level this intuitively feels right but getting into the details demonstrates this is really hard. For example, what is more impactful, treating anxiety or helping someone to buy their first home faster? Despite this complexity it's worth thinking about what outcomes are being targeted and which are more impactful. Sometimes the choice can be obvious. Taking cost as a proxy for impact, for every $1 spent on vaccines, ~$60 of healthcare costs are saved down the line (and that is pre-pandemic).

Who is experiencing the changes?

A given change in outcomes, say a reduction in weight of 5kgs, has different impact depending on who experiences is. Sticking with our weight loss example, for someone who is clinically obese, this is a good thing. For someone who is healthy, it's neither here nor there. For someone experiencing an eating disorder this is negative. Therefore, it's important to think of a product's user groups and their underlying needs to establish how much impact a product is having.

How much change occurs?

This is a function of three levers: how many people (500 vs. 5 million); how deep the change is (5% improvement vs. 50%); how long the change is sustained (5 days vs. 5 months). More impactful products will reach a greater number of people, move the needle further, and create lasting change.

How additional is the change?

In other words, how unique is the change. For something to be truly impactful it needs to grow the impact pie rather than displace previously occurring impact. For example, imagine an existing product to improve mental health. Then, a new product offering exactly the same benefits becomes available for $5 a month cheaper. The additionality of the new proposition is to save users $5 a month, rather than creating positive outcomes on mental health (those would have been achieved anyway through the existing product).

How risky is the change?

As with any desired future outcome, risks modify the likelihood that those outcomes are achieved. IMP lists nine impact risks including execution risk (e.g. inability to build product), alignment risk (e.g. mission drift) and stakeholder risk (e.g. users using the product different to how it was envisaged).

Impact can therefore be thought of as a kind of multiplication of these factors (modified by risk):

Impact = what additional changes occur X who they additionally occur to X [how many additional people X how deep the additional change is and how long it is additionally maintained]

All else equal, any improvement in any of these drivers will increase the amount of impact created. The difficulty is, that trade-offs almost certainly exist. For example, it’s easy to imagine high scale, low depth products or low scale, high depth products but difficult to imagine high scale, high depth products. These trade-offs trigger some of the challenging questions that the impact sector is wrestling with: where to prioritise and why.

Trying to break these trade-off frontiers is an exciting area for innovation in impact. For example, research has shown that technology enabled interventions can be effective for treating anxiety and depression. There is even some evidence (see section on anxiety) that the outcome improvements are on par with traditional outpatient care. This would mean that, by using technology, far more patients would be able to access the same degree of positive change. In other words, the what stays the same but the how much is dramatically increased. Of course, things are never that simple as one can imagine that the who might suffer in this instance (assuming that smart-phone enabled technology is less likely to reach those in greatest financial/health need).