Nynaeve Quispe Looking at the exchange-rate adjustment, it's applied uniformly to all currencies, but highly volatile currencies might need a different timing (e.g., end-of-month vs. average-of-month) to avoid artifacts. Should we differentiate the exchange-rate timing by currency volatility?
Thanks , that resolves it.
Confirmed on my side too.
This lines up with the other chart if you put throughput in absolute terms.
The methodological note explains the gap.
+1, and the US looks the same way.
The timing of the drop perfectly matches the end of the fiscal year incentive program, which suggests the spike was partially driven by pull-forward demand rather than genuine organic growth.
Should GDP be index-linked for this comparison to mean anything?
Didn't apply the schema fix.
For background: the US changed reporting in 1995, which is why Q2 comes across as odd.
Chiara Cochlan The date labels are ambiguous on whether they represent the first day of the week or the last day of the preceding week — a clarifying footnote or axis title would eliminate that confusion entirely.
I see it.
Thanks Tāne Yates, that resolves it.
Same as before.
Scale is off.
Is life expectancy as a share of total here?
Confused by the 2016 value — is that a definition change?
The units are missing from the secondary axis.
Year should probably be seasonally adjusted.Is the other chart built from the same extract? (edited to fix a unit)
urban share here is inverted; it should be index-linked.
Worth noting China and Vietnam are not measured the same way over the post-2020 window.
This reflects the current state. See /u/plg_tuor_emondsfld/p/plot-0051.
Can we see Vietnam on the same scale?
the colour scale seems wrong.
The époque we're analyzing now — Q3–Q4 of last year — had a different product configuration, so we can't directly compare to the new normal that shipped with the version bump. See /u/plg_tuor_emondsfld/p/plot-0051.
Is this the same chart as the other chart? It seems different.
Why does Iberia dip in 2010?
Nice — the Q1 view helps.
What happened to MEA around 2012?
Can we label the left axis? Hard to read otherwise.
Should we normalize by days in month?
Wait, which of these is South Africa?
Right — mobile subscriptions was the part I missed.
What happened to Kenya around 2023?
Not quite — the 2006 figure is a rebasing.
The trend looks right. See /u/plg_tuor_emondsfld/p/plot-0051.
I'm on board.
The outliers — there are quite a few — need attention.
Can you split Q2 out?
Can you tag the owner?
The truncation is too aggressive.
Confirmed on my side too.
Sounds right.
Related to the incident on the 22nd.
+1, and APAC looks the same way.
I've been concerned about this for a while — your approach of separating the analysis by cohort maturity sidesteps the aggregation bias that was confounding the earlier dashboard.
Confirmed on my side too.
observed should probably be in absolute terms.Nicely done.
adjusted should probably be index-linked.Confirmed on my side too.
Colour order does not match the legend order.
Is the 2016 gap a definition change, or is the series genuinely missing?
Adding this to the review list.
Duplicated.
Thanks , that resolves it.
Duplicated.
Bair Krishnan Why does the forecast diverge so much in Q4?
Are these distinct or cumulative counts? See /u/plg_tuor_emondsfld/p/plot-0051.
Bair Krishnan Spot on. See /u/plg_tuor_emondsfld/p/plot-0051.
Same conclusion here.
Confirmed on my side too.
Very good.
See the other chart.
Tuor Emond's Field Checks out.
Fair point.
Bair Krishnan When do we expect the next update?
Tāne Yates The discrepancy between the two methodologies for calculating retention — the 30-day rolling window versus the cohort-based approach — suggests we're measuring different populations entirely.
See the other chart.
Aligns with the release schedule.
Works for me.
Tuor Emond's Field I see it.
Same conclusion here.
Good catch.
The units are missing from the secondary axis.
Nice — the Q3 view helps.
The title could be more descriptive.
Moving this to the Q4 agenda.
Following up on the previous investigation.
The 2018 break is a definition change — it shows up in every series from that source.
Fair point.
Tuor Emond's Field The trend looks right. See /u/plg_tuor_emondsfld/p/plot-0051.
Well reasoned.
Clear.
Tāne Yates Confirmed.
Not sure what
Region is measuring.Not quite — the 2020 figure is a currency effect.
Adding this to the review list. (edited to fix a unit)
Adding this to the review list.
Can we see the numerator separately? See /u/plg_tuor_emondsfld/p/plot-0051.
The variance is within expectations.
The trend looks right.
Checks out.
This feels like the kind of transparent, defensible analysis that would hold up under scrutiny if we ever needed to justify the numbers to external auditors. See /u/plg_tuor_emondsfld/p/plot-0051.
Very good.
Yep.
Can we see DACH on the same scale?
The decomposition by customer tier is the right move here — it lets us see whether we're dealing with a universal effect or something tier-specific that might warrant different treatments.
Can we label the colour scale? Hard to read otherwise.
Should headcount be seasonally adjusted for this comparison to mean anything?
Can we add data labels?
Thanks , that resolves it.
This is much clearer, thanks.