With the construction of the impact model and KPI setting completed, it’s time to move on to the actual evaluation and quantification. In cases where manual work is involved, there may be a major step for KPI data collection after this, but we’ll skip that here. The main focus at this stage is defining the various KPIs and relations we’ve defined earlier to proceed with quantification. Defining relations essentially becomes the primary task. Here are the key essentials:

## 1．Arithmetic Adjustments

In terms of arithmetic adjustments, the following elements may be necessary, similar to general estimations:

#### Unit Adjustments

When the units of input and output represent the same concept but have different scales, adjustments are made to harmonize them (e.g., changing from thousands to billions).

#### Granularity Adjustments

When the units of input and output represent the same concept but have different granularity (e.g., per unit, per capita), adjustments are made to align them (e.g., adjusting between primary energy and final energy).

#### Ratio Adjustments

When the output represents a comprehensive concept relative to the input, adjustments are made to determine the appropriate ratio.

## 2．Basic Adjustment and Estimation Methods

In the quantification of impact, basic elements similar to general estimations include the following:

#### Time (Effort) and Impact (Financial) Adjustments

Adjusting financial impacts by multiplying by time-based rates. For example, standard wage statistics from the “Labor Force Survey” provided by the Ministry of Health, Labour and Welfare can be used to calculate time-based rates.

#### Unit Quantity (e.g., Number of People, Number of Cases, Number of Items) and Financial Adjustments

Adjusting financial impacts by multiplying them by unit prices, such as per person, per case, or per item. In consumer-related businesses, unit prices may be readily available, but in B2B settings, this information might not be as accessible. In such cases, historical data, industry averages, or logical judgments based on typical industry standards can be used.

#### Impact per Unit

Estimating the impact by multiplying the effect per input by the quantity of input. For impact estimation, you can utilize information from the company itself, commonly accepted data, logically calculable figures, or reports from government working groups and research companies that are considered reliable.

## 3．Key Estimation Patterns

There are several essential estimation patterns when assessing effects or impacts. They include:

#### Assuming Improvement in Indicators Due to Scale Increase/Decrease

Measurement of the effects is based on the assumption that efficiency per unit of Input 1 improves at a certain level due to factors like scaling up or outsourcing. Examples of certain levels include comparing productivity between small and large businesses or the efficiency of small and large-scale healthcare facilities.

#### Assuming Specific Indicators Maintain Current Levels or Achieve Past Levels

The effects are recognized by assuming that the target indicators maintain their current levels or achieve the idealized past levels, such as cost control, where the target indicator doesn’t exceed its current level or a past level.

#### Applying Known Ratios or Values

For cost ratios or similar financial metrics, even when specific information isn’t available for a particular company or case, known standards for certain scales can be applied or adjusted for differences from the actual evaluation subject.

#### Calculating Average Ratios or Values from Multiple Samples

In cases where not all information is clear, multiple samples are taken from individual cases, and the average level of their effects is established and applied.

#### Assuming Convergence to an Appropriate or Average Level

It’s assumed that a specific indicator converges to what is generally considered appropriate or logically reasonable over time. However, this assumption is more applicable when the specific indicator is relatively controllable and tends to naturally move in that direction.

#### Applying the Impact of the Element’s Absence (Difference in Situations)

Recognizing how the absence of the evaluated activity would impact the situation and applying the difference.

#### Setting a Certain Ratio through Segmentation

In cases where applying a specific indicator uniformly isn’t appropriate, a specific segment where the indicator can be applied is identified to improve accuracy, and the composition ratio is multiplied.

#### Applying the Difference from Industry Averages or General Standards

When dealing with a specific indicator, recognizing how the evaluated subject outperforms or underperforms industry averages and applying the difference.

## 4．Points to Pay Special Attention To

To ensure the validity of estimation and quantification, it’s important to review the logic of estimation from various perspectives, especially in cases where there might be leaps in the estimation. Consider the following viewpoints:

#### Temporal Considerations

- Is there a possibility that effects significantly increase or decrease over time?
- Are there cases where initial and running effects differ, or where results differ across the entire lifecycle of a product or service?
- Are the concepts of stock and flow being correctly applied, and is continuity being considered adequately? For example, using flow in situations where stock is more appropriate can lead to misleading and exaggerated impact claims.

#### Segmentation Considerations

- Is it appropriate to apply some uniform ratio or value when there is diversity in the data? Is weighted averaging necessary?
- Are segment ratios or operating rates being applied accurately?

#### Numerical Application Considerations

- n cases where calculations are based on previous year estimates or when using basic statistics embedded within the calculations (population, number of households, GDP, market size forecasts, etc.), it’s important to ensure their accuracy and alignment in terms of time series data.
- Especially when using numbers for the entire supply chain, make sure they are consistent at the same granularity (e.g., ex-factory price, wholesale price, end-user price) to avoid discrepancies.

## 5．Verification of the Final Estimation Results

To enhance the validity of the estimation results, you can consider the following aspects:

- Consistency across multiple pathways of estimation falls within a certain range.
- Comparison with industry standards or general norms reveals that the results fall within a certain range.
- The results approximate the levels disclosed as outcomes by companies, etc.