In this article, we will be talking about the 5 Dimensions of Impact as formulated by the Impact Management Project. Impact Management Project is a forum for building global consensus on how to measure and manage impacts. And these 5 dimensions have been built in consensus with over 2,000 organizations from all over the world.
What are the 5 Dimensions of Impact?
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Any work that you do with your organization, any intervention, any CSR project creates some impact. Of course, the intention is always to create positive impacts, but in real life despite the best intentions sometimes we end up creating negative impacts. To clearly understand what kind of impacts you have created on people, on the planet, there are 5 key dimensions that you need to understand & evaluate your performance on.
The 5 dimensions of impact are really the building blocks of any intervention or a project that aims to create an impact on people & planet. And ideally, you should be putting your impact measurement framework over this.
You should be thinking about 5 dimensions of impact from the very beginning of your project. But in case you are already in between a project, you can still use this framework to make your impact report much stronger & valid.
Now, let’s deep dive into the 5 Dimensions of Impact.
1. The first dimension is WHAT?
This dimension helps you understand two main things:
- Firstly, what outcome is your project or intervention creating?
- And secondly, how important is that outcome to the stakeholders?
For example, if you are running an awareness campaign to help infants living in rural areas get proper medical attention & vaccination. Then, your outcome that you need to measure might be % decrease in infant mortality rate.
This is a very clear case of creating positive & intended outcomes. But it is possible that you created negative outcomes or unintended outcomes.
As a part of this first dimension, you also need to measure & evaluate these outcomes. Another layer of this first dimension is if it met the needs of your stakeholders. For example, your donors, your team members, and even your beneficiaries. You need to evaluate how important that outcome is to your stakeholders. For example, you might have decreased the infant mortality rate in a village by 3%, but still hundreds of infants die in a year & maybe your stakeholders, in this case, the parents living in these villages feel that this 3% decrease is not enough.
The third layer is that if the outcomes you are creating are considered important by the stakeholders when compared with other outcomes.
This data should ideally be calculated by asking the question to the stakeholders or if it’s environment-related, then you might need to check scientific research.
The fourth & last layer of this dimension is if your outcome relates or contributes to international standards & goals like the sustainable development goals, and how much? It could be just one goal or more than one. But this aspect is really really important to understand the true effectiveness of your outcome. Our current example would relate to SD goal no. 3: Health & wellbeing.
2. The second dimension is WHO?
This second dimension covers who are the stakeholders that you created these outcomes for. The main objective of this dimension is to be able to identify stakeholders who need the most help & resources, and also who will experience the highest degree of change & impact.
In order to do that, IMP suggests identifying your stakeholders by also understanding how underserved they are in comparison to another group of stakeholders. There are 4 data categories that you can measure to understand this second dimension.
The first data category is what type of stakeholder are you affecting? Is it a certain section of the community? As in our example, it was the infants & their parents who are financially underprivileged and lack awareness about health-related issues. This category also encourages organizations to look at all the multiple stakeholders you might affect – intentionally or unintentionally.
For example, in this case, it is possible you also affect the medical professionals working with you on this project.
The second data category is where your stakeholders are located. Now it was possible that you could have gone to a community living in North Jakarta v/s a community living in a small village in Java. The community living in North Jakarta already has some other resources available thanks to a better medical system or some other NGOs working in the same area. Whereas this other village has not received any external help yet. So who would you rather try to affect & allocate your resources to?
The area could be as broad as a city or very targeted, but this dimension can help you in many ways. One of them is understanding the cultural nuances of that area and adapting your intervention accordingly or understanding the environmental conditions of that geographical area can also help you design better interventions.
The third data category under this dimension is baselining. This data helps you understand what was the outcome that your stakeholder groups were experiencing before your project or intervention started. This is the data which will help you understand how underserved or well-served your stakeholders are, it gives you a clear picture on which you can set up your goals & then measure & benchmark your performance.
In our hypothetical example, we can say that with baselining we found out that only 10% of new born children were receiving proper vaccination, so the intervention set the goal of taking this figure to at least 50% in one year. And then after a year, the intervention assessed its performance and found out that they could reach a figure of 45%.
It’s also very important that you have the same baselining indicator as the outcome indicator for your project.
The last data category under this dimension of who is – understanding the socio-graphic & behavioral data about your stakeholders.
For example, trying to understand what is the reason that the parents are not getting their kids proper vaccines. You might find out that while there is one group which doesn’t have enough awareness, there is a second group which is aware but does not have enough money to get the vaccines. This will enable you to design your interventions in a way that you can solve for their specific needs.
An important thing to keep in mind here is to evaluate what particular socio-graphic or behavioral data you are going to measure, which will help you the most.
3. The third dimension is HOW MUCH?
This 3rd dimension of impact helps you to understand the significance of the outcome you created with your projects or interventions. The main goal of measuring how much is to be able to understand exactly how much did the outcome actually help your stakeholders.
There are 3 data categories under How Much: Scale, Depth & Duration.
Let’s dig deeper into these data categories now:
Scale: This data category helps you understand how many people experienced the outcome you created. For example, for our recent project, Peduli Pangan soup kitchens were set up that distributed hot meals to financially underprivileged people affected by Covid-19 pandemic. I would just like to clarify that the Peduli Pangan program is still running so this is not the full scale. But we are just using it as an example here.
One of the outcomes we are measuring is the number of people receiving hot meals. In its first phase, 4 kitchens were set up and 8,000 people received food & experienced this outcome. This helped us understand the scale of our project, so far.
Scale data can help you understand if your intervention is meeting the needs of the problem & also help you reset your targets, if needed. The calculation of scale is also pretty straightforward, for example in our case study, the volunteers who distribute the food make a note on the distribution form for each meal given. So this form acts as a data source for us and the data value is 8,000 individuals.
While this data can act as a comparable figure between different projects. Just on its own, this data category is not enough to tell you the real impact created. You need to go a few steps further & also measure the depth & the duration.
That brings us to the second data category – Depth
Depth helps you understand to what extent or degree the change or value created was experienced by the stakeholders. This could be social change or environmental. It is calculated by comparing the outcome created with the baseline. It can be done in two ways – checking the absolute figure or checking the relative change. Ideally, you should be calculating both the figures as it can provide much more comprehensive data.
For example, in the case study we discussed, we baselined that before the Peduli Pangan program, most of our stakeholders were getting only 2 meals a day but with the program, they could get 3 meals a day. This baseline of 2 meals can help us understand the depth. So the relative indicator can be calculated by dividing the outcome by baseline, which will be 3 divided by 2 so they are receiving 1.5 times more or 150% more food in comparison. And the absolute figure will be very simple to calculate, simply subtract the baseline from the outcome, so they are getting one meal more.
Measuring this data category can help you also design more targeted interventions and segment your stakeholder according to the result.
The third & the last data category is the duration. It is the period during which the stakeholders receive the outcome. Ideally, you want your positive outcome to last for as long as possible and negative for as little. This data pushes you to think about the sustainability of your outcome & also think about how you can plan it for short-term, medium-term & long-term.
There are 3 main aspects to keep in mind while calculating the duration: Outcomes have different durations, there might be some which will last for years for example outcome of a health awareness campaign for proper vaccination will last for years whereas some might be very short term. Secondly, the outcome of some interventions will be realized immediately, for example, for the Peduli Pangan program, the outcome is immediate whereas outcomes of other interventions might take more time to realize. Lastly, some effects of outcomes will be felt for long after the intervention is over.
Duration can be measured firsthand, but recording data from the beginning till the end of your intervention or even after it directly by interviewing your stakeholders. Or if cost is an issue, then you can look at other data available and use that.
You also have to realize while measuring this dimension that one is not always better than the other. For example, some interventions might be designed in a way that it benefits fewer people in scale but for longer duration whereas another affects more people but for a lesser duration. It really depends on the problem you are trying to solve and your resources.
4. The 4th dimension of impact is Contribution
I feel this is one of the most important dimensions to measure & is also very humbling. It helps you understand that did your intervention contribute to the outcome and what would have been the outcome if your intervention was not executed. It is important to realize that our interventions play out in the real world with many different players. So to understand your exact role in creating an outcome you need to evaluate what would have happened in its absence.
This will help you understand what outcomes would have been created anyway – with or without you.
This is very important because if you find out that if the extent to which you contributed to creating an outcome is minimal, then you can decide to invest your resources elsewhere.
The two data categories under this dimension are: Depth counterfactual & duration counterfactual. The word counterfactual here means in absence of this intervention.
In depth data category, you evaluate that how much outcome would have been created anyway without your intervention. This is not the same as calculating the depth in the How Much dimension. While calculating this you take into account other factors at play.
It can be calculated by interviewing stakeholders, taking stakeholder feedback to understand the other factors at play like other NGO programs or government agencies.
Another way to calculate depth counterfactual is market research, digging deep into secondary research, observing stakeholders can give you a rough idea. It is, however, much better to combine market research with stakeholders feedback.
The third way is evidence-based research which would use control groups or experimental groups to understand the effectiveness of your intervention & project. However, this method can be quite cost-intensive but bring you the best results. In control groups, you would randomly assign two groups and compare the outcome between the group which received the intervention resources and the one which did not.
The second data category, duration helps you understand your contribution to the duration for which the outcome was experienced. To understand this, you need to understand how long the outcome would have been experienced without your intervention. This can help you understand the sustainability of your project and enable you to make the right decisions about your resource allocation. For example, if an organization realizes that its contribution to the duration to which the outcome is experienced is not for long enough as compared to other organizations or initiatives, then you can decide to either allocate your resources to some other projects or change our strategy.
Now, it’s finally time to discuss the last dimension of impact. Stay focused guys..hahaa…we know it is a relatively long podcast but we are almost at the end.
5. So the last dimension of the impact is Risk.
This helps us evaluate & understand what challenges you might face in creating the desired outcome. This can help you understand the risk and find ways to mitigate it. There are 3 main data categories that can help you here:
The first one is the type of risk. IMP has listed 9 types of risk that any impact creating organization might face, there is evidence risk or execution risk. Execution risk means that if the activities planned are not executed the way they were planned. Or evidence risk means if there is a lack of data available to measure impact. We will list all the 9 risks in the script of the podcast for you to peruse at your own leisure.
The second data category mentions how to understand the risk level. That if this risk actually happens, then what might be the severity of consequences. High or low or medium.
In order to assess the risk, organizations need to do it constantly at different stages of the project. And consider two main things:
- The likelihood that the risk will happen
- And the consequences, if it happens
This can allow you to map your risk levels and then look for ways to mitigate it. So adopting a more proactive approach.
OK, guys! These are your 5 dimensions of impact. A bit complex but very very important elements of impact measurement & management. If you have any questions, please feel free to contact us via email, at firstname.lastname@example.org.
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