After aggregating indicators within and across workspaces, you can refine your calculations by adding weights or adjustments to your contributing indicators.
Weighting
The contributing indicators for an aggregated indicator can be weighted in TolaData. This allows the effect of each indicator to be adjusted according to their respective importance or proportional value toward the overall total.
To explain how weighting is done in TolaData, let’s look at a use case.
An organisation wants to measure the overall approval rating across two of its workspaces based on how many participants in each workspace said they approved of the services they received. Each workspace has an indicator to track the % approval by participants. We can see each of these indicators below.
% approvals in workspace A
% approvals in workspace B
In this example, the workspaces have different numbers of beneficiaries. Workspace A reached 6000 beneficiaries whilst workspace B reached 2000.
Let’s look at this example without weighting. If workspace A has a 50% approval rating that means 3000 of its 6000 participants approved of the services. If workspace B has an 80% approval rating that means 1600 of its 2000 participants approved. If you just aggregate the approval ratings without weighting you would take the average of 50% and 80% = 65%. But that result would be saying that overall 65% of 8000 approved, ie 5200 participants. But we know the actual number that was approved was only 4600 of the 8000.
To get an accurate overall result, workspace A should have a bigger mathematical weight when it comes to calculating the aggregated value as it reaches more beneficiaries.
For the result to be representative, we must weight each result according to the relative proportion of total beneficiaries it represents. For workspace A this relative proportion is 6000/8000 = 75%. For workspace B the relative proportion is 2000/8000 = 25%.
We use these relative proportions or weights in the aggregated indicator on the contributing indicator tab. The first step is to add each workspace indicator to our aggregated indicator as seen below. If you are unsure how to create aggregated indicators in TolaData, see our guide here.
After you have added your contributing indicators to your aggregated indicator, ensure that the aggregation formula in the ‘manage indicators’ section is set to any of the calculation formulas except ‘average’ as you will not be able to add weights for an average.
After confirming your aggregation formula, select the ‘weights and adjustments’ toggle. You can now enter the weights you calculated for each contributing indicator.
You can see a breakdown of the calculation being performed underneath the box.
Your updated aggregated total will now display against your target. The blue bar will indicate the percentage achieved. The aggregated target will display in the box to the left-hand side.
Adjusting
Alongside weighting indicators, you can also adjust the values of contributing indicators to correct for known over or under-reporting, or double counting. Double counting causes an inflation of programme results. To read more about double counting, check out our blog post.
To explain how adjusting indicators works in TolaData, let us look at a use case.
An organisation wants to count the total number of participants it has across two workspaces. Each workspace has an indicator counting the number of participants. Below we can see each of these contributing indicators in the aggregated indicator.
However, as the workspaces are operating in the same region, it is understood that some participants are receiving services from both workspaces. The estimated number of participants who are part of both workspaces is 10%. If we just sum the total number of participants from each workspace together we will count this 10% twice. To avoid double-counting these participants we can adjust one of the contributing indicators by – 10% to reduce its value by the number of participants who are already counted within the other indicator
To do this, select the ‘Managing Indicators’ button and then select the ‘weights and adjustments’ toggle.
In the adjustment field of one of the indicators, enter -10 to reduce the aggregated value by 10%.
NOTE: If you do not enter a weighted value, the weight will remain at 100%. After you save your adjusted value, the calculation will appear below the indicators.
In the contributing Indicators page you can see the new actual value after the adjustment has been applied. The blue bar will indicate the percentage achieved. The aggregated target will display in the box.
You can add both weights and adjustments to contributing indicators within the same calculation allowing you and your organisation to perform more accurate calculations of your overall results.
Tip: adjustments correct for double counting you already know about. To have TolaData detect duplicated values automatically, see Duplication Tracking and Aggregation Policies.
