Why Timeframe Consistency (Monthly, Quarterly, YTD) Matters When Exporting CSI Data

Two rooftops can each report a CSI score of 88 and still not be comparable, if one number reflects the current month and the other reflects year-to-date. Time frame mismatches like this are easy to miss and quietly undermine every comparison a dealer group tries to make across its rooftops and brands.

The Time Frames Dealer Groups Typically See

Most OEM portals let you view a rooftop’s score across a handful of standard windows: current month, previous month, a rolling three-month average, and year-to-date. Each tells a different story. Current month is the most immediate but most volatile, especially at lower-volume stores. Rolling three-month smooths out single-month noise. Year-to-date shows the broader trend but reacts slowly to a recent problem. None of these is the “right” time frame on its own, they answer different questions.

Why Mismatched Time Frames Create Bad Comparisons

When one rooftop’s export reflects a rolling three-month average and another reflects only the current month, a side-by-side comparison is comparing two different things while looking like a fair comparison. A store having a rough current month can look far worse than a store with the same underlying performance viewed on a three-month average, or the reverse. Without consistent time frames across every export, leadership ends up making decisions, and sometimes flagging or praising managers, based on a distortion rather than an actual performance gap.

Why This Matters for OEM Incentives

Many OEM bonus and incentive programs are calculated on rolling averages over a specific window, not a single month’s snapshot. If a dealer group is internally reviewing current-month numbers while the incentive program is actually tracking a rolling three-month figure, leadership can be reacting to the wrong signal, either missing a real risk to a payout or reacting to a dip that the OEM’s own calculation will smooth out.

The Manual Export Problem

This inconsistency usually isn’t a data quality issue, it’s a byproduct of how the data gets pulled. Every OEM portal defaults to its own time frame view, and when someone is manually logging into a different portal for each brand, it’s easy to end up with a rolling average for one brand and a current-month snapshot for another simply because that’s what happened to be on screen during the pull. The inconsistency gets built in at the point of export, before anyone even starts comparing rooftops.

How ASAP Standardizes Time Frames Across Every Export

Oxlo’s Automated Score Aggregation Program (ASAP) pulls CSI and every other score type consistently across current month, previous month, rolling three-month, and year-to-date, for every brand, on the same schedule. That means when a regional director compares two rooftops, they’re looking at the same window for both, every time, without having to double-check which time frame each brand’s portal happened to default to.

Get Every Rooftop on the Same Time Frame

Contact Oxlo to see how ASAP standardizes time frames across every brand and rooftop in your export.

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