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Higg FEM: Baselining & Data Normalization

Baselining & Normalization

What is a baseline?

In order to demonstrate improvements or reductions in environmental impact, it's important to know what your starting point is. A "baseline" is a starting point or benchmark that you can use to compare yourself against over time. For example, if your factory used 80 m3 of water per 10,000 fabric meters in 2016, you will be able to compare your performance against this amount in years to come. In this example, "80 m3 of water per 10,000 fabric meters in 2016" is an example of a normalized baseline.

Data validation is a critical first step. The data needs to be stable and reliable before setting the baseline. What is required:

  1. Using stable data: if your factory has undergone major structural changes such as acquisition or changes in product type, you should select a baseline after those changes have been completed.  
  2. Normalization: if you select a normalized baseline, it will be normalized against the production units entered into the Site Information section for annual production. For example, if you selected annual production in “meters”, your baseline will be normalized against meters.
  3. Verified data: baseline data should be accurate and verifiable. Verified energy data from Higg FEM is an acceptable source of baseline data. Baseline data verified by internal audit process is also acceptable.

The baseline year and the baseline performance level (e.g. annual energy use, emissions per unit etc.), should remain unchanged if you plan to set targets for improving your performance.

Data Normalization

Why? Your use of energy, water, or other manufacturing inputs can fluctuate due to various factors such as an increase or decline in business.  To account for fluctuations we recommend dividing consumption data by a common parameter, such as production units.  This provides for better year-over-year comparison of data and therefore more useful, and actionable analytics .

What? Normalization removes some variation in the data set in order to have a data set that is considered normal.  Consumption of energy for example is typically tracked in the unit kWh (Kilowatt-hour).  However, for data normalization a standard parameter, such as square meters of material or unit of production, is used to divide the absolute value of energy kWh.

How?  Calculate using data captured from an absolute scale (for example, kWh for electricity) and dividing it by a common and constant (standard) parameter such as units of production, number of employees, or revenue. Repeat for all data sets.  

In the Higg Index: if you select a normalized baseline, target, or reduction in the Higg Index, it will be normalized against the production units entered into the Site Information section for annual production. For example, if you selected annual production in “meters”, your normalized baseline will be normalized against meters.

Example: The electricity meter on production line A reads: 1,000 kWh it produced 100 pairs in one hour.  The normalized energy usage is 10 kWh/pair [1000kWh/100pairs= 10 kWh/pair].  Meter on production line B reads: 1,225 kWh it produced 140 pairs in one hour. The normalized energy usage is 1225/140= 8.75kWh/pair.  Therefore, when comparing production line A and B, production line B used more energy in an hour, however, when looking at the normalized data you can conclude that production line B was 12.5% more energy efficient.

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