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Range & Fluctuation Metrics

A simple score from 0 to 100% to align your team around how often you're meeting your ideal environmental levels.

Conserv cloud is a free, cloud-based environmental monitoring tool. You can create an account at https://app.conserv.io.

The challenge

Preservation metrics should help us answer the simple question "How are we doing?" — read more in our article "Understanding Preservation Metrics".

Take the example of the common temperature and relative humidity chart so common in environmental monitoring reports.

Screenshot 2020-10-09 at 11.08.36 AM - Edited (1)

It takes a lot of calories and words to explain to your colleagues how you're doing based on the above chart.

What if instead of the typical chart you could tell your team, "Most months we meet our RH goal 99% of the time, and this month we met our RH goal 94% of the time?"

With an immediate sense of "How we're doing?" your team can then focus on the causes of good/bad performance and what you can do to improve the collection environment.

Range and fluctuation calculations for temperature, RH, and illuminance

% in range

The calculation of the % of time your readings are within range is very straightforward. We count all of your readings for the period you determine that are within the levels you've set (which show up as green bands for temperature and relative humidity on your Analytics graphs) and divide by the total number of readings for the period.

% in range formula

# of readings within your set levels / total # of readings for your period chosen * 100%

You can also get an immediate rough visual estimate of your % in range calculation by looking at how much of your line falls within the green bands of your graph.

A word of caution: Your % in range will be affected by any sensor that is not reading every 15 minutes. Whether you have a sensor that reports less often, or imported data from a sensor from a different brand with a longer reading frequency, the formula will weigh those readings differently and affect your % in range.

Illuminance % in range is also calculated using this formula, although it cannot be visualised on the graphs at the moment.

% in flux

The % fluctuation calculation is a little bit more complex because we add a rolling 24-hour variable. The logic for what % of the time the readings are within the maximum allowed 24h-fluctuation set by the user is the following:

For every reading within the time period the user requests, the software looks at all the readings 12 hours before and 12 hours after. Within that 24h period, it subtracts the maximum reading it finds minus the minimum reading it finds.

This difference will be either under or over the maximum fluctuation the user has set (which can be found in the level profile settings). If the difference is below the target set by the user, it marks the reading as within specification.

If not, it marks it as outside specification. Once it has that in/out specification defined for every individual reading in the chosen time period, it divides all the within specification readings over the total number of readings for the period.

% in flux (fluctuation) formula

# of within specification readings / total # of readings for your period chosen * 100%

To get a visual of what this % in flux looks like, you will need to go to do two things in your sensor graph in the Analyze tab. Please note these instructions apply to the old version of Analytics only:

  1. In the Date Range section, choose Aggregate by Daily.
  2. In the Additional section below that, check the box that says Show 24H Fluctuation.

These two actions will make a histogram appear below your graph. The histogram will show a thin line for your target maximum fluctuation. Each bar will show what the maximum difference between the max and min readings have been for that 24-hour period. The more bar area you have under the line, the higher your % in flux number will be.

Illuminance does not currently use a % in flux calculation as cumulative exposure in total lux hours is more important than fluctuation.

Getting range and fluctuations working for you

In this section, we're focusing on relative humidity as an example. Range and fluctuation metrics are also available for temperature and illuminance.

Setting levels

Range and fluctuation metrics rely on the levels you've set for your collection spaces. Looking at the graph below, you can see we've made it easy to visualize your levels.

Screenshot 2020-10-11 at 8.00.26 AM - Edited

In this example, we have an RH range level between 40-60% and an RH fluctuation target of less than 10% per day.

For guidance on setting the right relative humidity levels, start with our article "Setting relative humidity (RH) levels for your collection".

A quick glance at the relative humidity KPIs on the right (red circles) shows that you’ve been staying within your target levels 94% of the time in both cases:

Screenshot 2020-10-11 at 9.11.51 AM - Edited

Note that the colors for readings are consistent across the application - Red is always RH, blue is temperature, green is illuminance, etc.

Making observations

Think of observations as the way you tell the story of your collection - for others and for your future self. Whenever your readings are outside of the ideal environmental levels you can make annotations to help diagnose the challenge.

Screenshot 2020-10-11 at 9.05.48 AM - Edited

When you combine readings, levels, metrics, and observations you have a powerful set of tools to understand and improve your collection environment.


Important: Some users have noted that if they take the average of the % in range that they see in each of their individual sensor graphs and compare it to the Space number in their Space Performance Report, that the numbers are not the same.

This is because the calculation in the Space Performance Report is not an average of your individual sensor calculations. Instead, it takes into account every single data point - this includes any non-Conserv sensor data that you may have manually uploaded to the software.

What's next

By using KPIs, collections professionals can get their teams aligned on "how are we doing", and begin to lead the conversation on what needs to be done to improve the collection environment.

The primary purpose of good metrics is not just to answer questions; Good metrics also help your organization ask better questions to address the root cause of problems.