How to Get the Most From myVIE in the First 90 Days
The first 90 days with VIE are not a waiting period. The analytics engine is actively building the individual baseline for each monitored transformer — learning the relationship between load, voltage, ambient temperature, and vibration signature for each specific unit. That baseline is what every subsequent alert is measured against. Getting it right during this window matters for everything that follows.
Week One to Two: Get Familiar With the Data
Before the initial health report review with your VIE application engineer, spend time in myVIE looking at the incoming data without interpreting it as alerts. The goal in this period is pattern recognition, not action.
Notice what each transformer's metrics look like under different load conditions. Notice how the vibration signature changes at different times of day, at different ambient temperatures, and at different loading levels. The variation you see is normal. It is what the analytics engine is using to separate condition-driven changes from load-driven changes.
If you see a metric value that looks high or unusual, do not act on it immediately. Note it and bring it to the initial health report review. The analytics engine has context you cannot see in a snapshot view.
Week Three to Four: The Initial Health Report Review
VIE's application engineers will schedule the initial health report review once the baseline is sufficiently established. This is the most important meeting in the first 90 days.
The review covers: what the baseline values are for each metric on each transformer, whether any metrics flagged during the baseline period and what they indicate, how to read the health report going forward, and how to configure alert thresholds for your specific fleet.
Come to this meeting with your observations from weeks one and two. If you noticed something that looked unusual, raise it. If you know something about a specific transformer that the data might reflect — a recent through-fault on its circuit, a history of elevated loading, a repair that was completed before VIE was installed — share it. That context changes how the baseline is interpreted.
After the review, VIE's application engineers configure the alert thresholds based on what the baseline has shown and what your team identified as the appropriate response protocol.
Months One to Three: Build the Institutional Record
The first 90 days are when the habit of capturing field observations in myVIE needs to be established. Once that habit is in place, it persists. If it is not established in the first 90 days, it typically does not get established later.
Every time a technician visits a monitored transformer during this period — for any reason — record the observation in myVIE as a note on the asset. Found a cooling fin blocked? Note it. Saw evidence of oil seepage? Note it. Heard unusual noise from the unit? Note it. The note is timestamped and attached to the asset record alongside the metric data from the same period.
When a lab result comes back for an oil sample, enter it alongside the VIE oil health metric trend for the period when the sample was taken. The comparison between what VIE was showing and what the lab confirmed is the kind of calibration data that makes the monitoring program more useful over time.
Months Two to Three: Verify the Alert Configuration
After the thresholds are set and the first few weeks of monitoring are running against them, check whether the alert configuration is producing the right volume and type of alerts.
Too many alerts means the thresholds are too sensitive — the team will begin ignoring them. Too few alerts, or alerts that arrive late relative to when the metric trend was clearly moving, means the thresholds are too conservative. Adjust with your VIE application engineer.
The goal is a configuration where yellow alerts prompt a scheduled test, red alerts prompt an expedited inspection, and stable assets generate no alert noise. Getting to that configuration is an iterative process. The first 90 days are when the iteration happens most productively, because the baseline data is fresh and the application engineers are most actively engaged with your deployment.