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I would like to analyze the service level of the delivery capability from a table. Unfortunately, I can't get the correct result with this formula (list attached)
=if(ShippingDateConfirmed <> '01.01.2016',sum{<CreatedDateTimeMonth={">=$(=max(CreatedDateTimeMonth)-2)<=$(=Max(CreatedDateTimeMonth))"}>}If([ShippingDateRequested] >= [ShippingDateConfirmed],1,0)))
/
count({<CreatedDateTimeMonth={">=$(=max(CreatedDateTimeMonth)-2)<=$(=Max(CreatedDateTimeMonth))"}>}OrderId)
Servicelevel Total | 58,6% | ||||
Servicelevel 6 Mo | 72,9% | ||||
Servicelevel 3 Mo | 84,4% | ||||
OrderId | Created Date | CreatedDateTimeMonth | ShippingDateRequested | ShippingDateConfirmed | Service |
AUF255385 | 25.10.2024 | Okt. | 30.10.2024 | 30.10.2024 | 1,00 |
AUF255311 | 22.10.2024 | Okt. | 24.10.2024 | 24.10.2024 | 1,00 |
AUF255260 | 18.10.2024 | Okt. | 31.10.2024 | 31.10.2024 | 1,00 |
AUF255104 | 09.10.2024 | Okt. | 11.10.2024 | 11.10.2024 | 1,00 |
AUF255087 | 09.10.2024 | Okt. | 31.10.2024 | 31.10.2024 | 1,00 |
AUF255093 | 08.10.2024 | Okt. | 08.10.2024 | 08.10.2024 | 1,00 |
AUF255099 | 08.10.2024 | Okt. | 10.10.2024 | 10.10.2024 | 1,00 |
AUF255086 | 07.10.2024 | Okt. | 08.10.2024 | 08.10.2024 | 1,00 |
AUF255062 | 04.10.2024 | Okt. | 09.10.2024 | 09.10.2024 | 1,00 |
AUF255060 | 04.10.2024 | Okt. | 08.11.2024 | 08.11.2024 | 1,00 |
AUF255011 | 02.10.2024 | Okt. | 03.10.2024 | 03.10.2024 | 1,00 |
AUF255019 | 02.10.2024 | Okt. | 03.10.2024 | 03.10.2024 | 1,00 |
AUF255015 | 02.10.2024 | Okt. | 08.10.2024 | 08.10.2024 | 1,00 |
AUF254996 | 01.10.2024 | Okt. | 03.10.2024 | 03.10.2024 | 1,00 |
AUF254998 | 01.10.2024 | Okt. | 03.10.2024 | 03.10.2024 | 1,00 |
AUF254942 | 26.09.2024 | Sep. | 10.10.2024 | 16.10.2024 | - |
AUF254929 | 25.09.2024 | Sep. | 23.10.2024 | 29.10.2024 | - |
AUF254872 | 23.09.2024 | Sep. | 24.09.2024 | 24.09.2024 | 1,00 |
AUF254873 | 23.09.2024 | Sep. | 24.09.2024 | 24.09.2024 | 1,00 |
AUF254853 | 20.09.2024 | Sep. | 26.09.2024 | 26.09.2024 | 1,00 |
AUF254859 | 20.09.2024 | Sep. | 18.10.2024 | 31.10.2024 | - |
AUF254839 | 19.09.2024 | Sep. | 23.09.2024 | 23.09.2024 | 1,00 |
AUF254824 | 18.09.2024 | Sep. | 20.09.2024 | 20.09.2024 | 1,00 |
AUF254596 | 05.09.2024 | Sep. | 12.09.2024 | 12.09.2024 | 1,00 |
AUF254543 | 02.09.2024 | Sep. | 10.09.2024 | 10.09.2024 | 1,00 |
AUF254523 | 30.08.2024 | Aug. | 04.09.2024 | 04.09.2024 | 1,00 |
AUF254501 | 29.08.2024 | Aug. | 05.09.2024 | 26.09.2024 | - |
AUF254310 | 13.08.2024 | Aug. | 20.08.2024 | 20.08.2024 | 1,00 |
AUF254282 | 12.08.2024 | Aug. | 14.08.2024 | 14.08.2024 | 1,00 |
AUF254267 | 09.08.2024 | Aug. | 13.08.2024 | 13.08.2024 | 1,00 |
AUF254207 | 06.08.2024 | Aug. | 14.08.2024 | 14.08.2024 | 1,00 |
AUF254194 | 05.08.2024 | Aug. | 08.08.2024 | 29.08.2024 | - |
AUF254037 | 23.07.2024 | Juli | 23.07.2024 | 23.07.2024 | 1,00 |
AUF254046 | 23.07.2024 | Juli | 31.07.2024 | 31.07.2024 | 1,00 |
AUF253884 | 11.07.2024 | Juli | 18.07.2024 | 18.07.2024 | 1,00 |
AUF253821 | 08.07.2024 | Juli | 09.07.2024 | 09.07.2024 | 1,00 |
AUF253815 | 08.07.2024 | Juli | 10.07.2024 | 10.07.2024 | 1,00 |
AUF253584 | 24.06.2024 | Juni | 27.06.2024 | 25.07.2024 | - |
AUF253547 | 20.06.2024 | Juni | 21.06.2024 | 28.06.2024 | - |
AUF253553 | 20.06.2024 | Juni | 16.07.2024 | 16.07.2024 | 1,00 |
AUF253304 | 05.06.2024 | Juni | 06.06.2024 | 27.06.2024 | - |
AUF253291 | 04.06.2024 | Juni | 06.06.2024 | 04.07.2024 | - |
AUF253166 | 27.05.2024 | Mai | 04.06.2024 | 04.06.2024 | 1,00 |
AUF253116 | 23.05.2024 | Mai | 28.05.2024 | 28.05.2025 | - |
AUF248055 | 14.05.2024 | Mai | 17.05.2024 | 03.06.2024 | - |
AUF252912 | 10.05.2024 | Mai | 14.05.2024 | 14.05.2024 | 1,00 |
AUF252916 | 10.05.2024 | Mai | 14.05.2024 | 31.05.2024 | - |
AUF252924 | 10.05.2024 | Mai | 23.05.2024 | 06.06.2024 | - |
AUF252786 | 29.04.2024 | Apr. | 03.05.2024 | 03.05.2024 | 1,00 |
AUF252778 | 29.04.2024 | Apr. | 07.05.2024 | 07.05.2024 | 1,00 |
AUF252653 | 19.04.2024 | Apr. | 23.04.2024 | 23.04.2024 | 1,00 |
AUF252603 | 17.04.2024 | Apr. | 23.04.2024 | 31.05.2024 | - |
AUF252570 | 16.04.2024 | Apr. | 23.04.2024 | 23.04.2024 | 1,00 |
AUF252419 | 08.04.2024 | Apr. | 10.04.2024 | 10.04.2024 | 1,00 |
AUF252414 | 05.04.2024 | Apr. | 09.04.2024 | 09.04.2024 | 1,00 |
AUF252401 | 04.04.2024 | Apr. | 11.04.2024 | 11.04.2024 | 1,00 |
AUF252351 | 02.04.2024 | Apr. | 03.04.2024 | 03.04.2024 | 1,00 |
AUF252220 | 25.03.2024 | März | 28.03.2024 | 28.03.2024 | 1,00 |
AUF252217 | 25.03.2024 | März | 04.04.2024 | 05.04.2024 | - |
AUF252216 | 25.03.2024 | März | 28.03.2024 | 25.04.2024 | - |
AUF252199 | 22.03.2024 | März | 30.04.2024 | 30.04.2024 | 1,00 |
AUF252174 | 21.03.2024 | März | 26.03.2024 | 26.03.2024 | 1,00 |
AUF252148 | 20.03.2024 | März | 21.03.2024 | 21.03.2024 | 1,00 |
AUF252104 | 18.03.2024 | März | 21.03.2024 | 28.03.2024 | - |
AUF252075 | 14.03.2024 | März | 18.03.2024 | 18.03.2024 | 1,00 |
AUF251996 | 11.03.2024 | März | 13.03.2024 | 13.03.2024 | 1,00 |
AUF252002 | 11.03.2024 | März | 13.03.2024 | 13.03.2024 | 1,00 |
AUF251878 | 04.03.2024 | März | 08.03.2024 | 08.03.2024 | 1,00 |
AUF251866 | 01.03.2024 | März | 04.03.2024 | 04.03.2024 | 1,00 |
AUF251843 | 29.02.2024 | Feb. | 26.03.2024 | 26.03.2024 | 1,00 |
AUF251791 | 26.02.2024 | Feb. | 29.02.2024 | 29.03.2024 | - |
AUF251674 | 20.02.2024 | Feb. | 21.02.2024 | 21.02.2024 | 1,00 |
AUF251610 | 15.02.2024 | Feb. | 21.02.2024 | 21.02.2024 | 1,00 |
AUF251603 | 14.02.2024 | Feb. | 19.02.2024 | 19.02.2024 | 1,00 |
AUF251513 | 09.02.2024 | Feb. | 13.02.2024 | 13.02.2024 | 1,00 |
AUF251479 | 07.02.2024 | Feb. | 08.02.2024 | 29.02.2024 | - |
AUF251416 | 05.02.2024 | Feb. | 08.02.2024 | 09.02.2024 | - |
AUF251418 | 05.02.2024 | Feb. | 11.03.2024 | 11.03.2024 | 1,00 |
AUF251235 | 24.01.2024 | Jan. | 31.01.2024 | 01.02.2024 | - |
AUF251241 | 24.01.2024 | Jan. | 01.02.2024 | 01.02.2024 | 1,00 |
AUF251195 | 23.01.2024 | Jan. | 20.03.2024 | 24.01.2024 | 1,00 |
AUF251176 | 22.01.2024 | Jan. | 24.01.2024 | 24.01.2024 | 1,00 |
AUF251097 | 16.01.2024 | Jan. | 18.01.2024 | 18.01.2024 | 1,00 |
AUF251033 | 11.01.2024 | Jan. | 16.01.2024 | 16.01.2024 | 1,00 |
Hi @maschi77 ,
That is great! Thank you.
Ok, usually, the KPIs have the "pure" version of the expressions and the same expression on the context of a chart with dimensions and other measures reacts to those dimensions AND measures.
You can try these exercises:
1. Copy the table chart you have, exclude all the dimensions and check the results (you should have only the measures).
2, Copy the original chart again, this time create one extra copy for each measure but leave the dimensions and only one Measure per chart (you will have four new charts). Check the results.
Also, check if you don't have the dimensions checked to exclude null values. This may be impacting your values.
So, this is a diagnostic phase you are doing to try to identify the problem. Next we can think about how to solve them.
Please let us know the results!
Regards,
Mark Costa
Read more at Data Voyagers - datavoyagers.net
Follow me on my LinkedIn | Know IPC Global at ipc-global.com
To avoid misinterpetations...
correct --> Excel 😉
wrong --> Qlik Sense
I can't find the reason. can someone give me a helpful tip?🙏🏻
Hi @maschi77 ,
My solution is a mix of Load Script and Measure Expression changes.
I always recommend changing the Load Script to reduce the complexity of the chart measures.
I did some data treatment because your data format was different from mine but the important thing here is that Qlik must interpret your Date fields as Date field values, not as text.
Ok, so following the Load Script:
Orders:
LOAD
*,
If(ShippingDateConfirmed <> MakeDate(2016,1,1),1,0) AS ShippingDateConfirmedFlag,
If(ShippingDateRequested >= ShippingDateConfirmed,1,0) AS ShippingCounter
;
LOAD
OrderId,
Date#("Created Date",'dd.mm.yyyy') AS "Created Date",
CreatedDateTimeMonth,
Date#(ShippingDateRequested,'dd.mm.yyyy') AS ShippingDateRequested,
Date#(ShippingDateConfirmed,'dd.mm.yyyy') AS ShippingDateConfirmed,
If(Match(Service,'1,00'),1,0) AS Service
FROM
[lib://DataFiles/Orders.xlsx]
(ooxml, embedded labels, table is Sheet1)
;
And this is the new Measure:
{<ShippingDateConfirmedFlag = {1}, [Created Date] = {">=$(=Date(AddMonths(Max([Created Date]),-2),'DD.MM.YYYY'))<=$(=Date(Max([Created Date]),'DD.MM.YYYY'))"}>}Sum(ShippingCounter)/Count(OrderId)
Note that you don't need to repeat the Set Analysis Expression for every Aggregation if you write it outside them.
Regards,
Mark Costa
Read more at Data Voyagers - datavoyagers.net
Follow me on my LinkedIn | Know IPC Global at ipc-global.com
Hi @marksouzacosta ,
I have implemented your idea and it works perfectly in the table diagram. Thank you very much for your suggested solution, you are a hero!!!
Unfortunately, the results from the table chart can't be transferred to KPIs.
I have already tried different aggregation variants without success. Perhaps there is a tip here too 😉 ?
Formula (Service 3Mo) Diagramm and KPI:
{<ShippingDateConfirmedFlag = {1}, CreatedDateTimeDate =
{">=$(=Date(AddMonths(Max(CreatedDateTimeDate),-3),'DD.MM.YYYY'))<=$(=Date(Max(CreatedDateTimeDate),'DD.MM.YYYY'))"}>}
Sum(ShippingCounter)/Count(Auftrag)
Sript:
LOAD ..........
ShippingDateConfirmedMonth,
ShippingDateConfirmedWeek,
ShippingDateRequested,
ShippingDateConfirmed,
CreatedDateTimeDate,
If(ShippingDateConfirmed <> Makedate(1900,1,1),1,0) as ShippingDateConfirmedFlag,
If(ShippingDateConfirmed = Makedate(1900,1,1),1,0) as ShippingDateConfirmedFlag0,
If(ShippingDateRequested >= ShippingDateConfirmed,1,0) as ShippingCounter,
if(ShippingDateConfirmed = Makedate(1900,1,1) and (CreatedDateTimeDate - today(1))<-2,1,0) as tolateconfirmed
From lib://$(QVDPath_Schema)/SalesLine.qvd (qvd);
(Data format is already formatted in DWH)
Regards
Hi @maschi77 ,
That is great! Thank you.
Ok, usually, the KPIs have the "pure" version of the expressions and the same expression on the context of a chart with dimensions and other measures reacts to those dimensions AND measures.
You can try these exercises:
1. Copy the table chart you have, exclude all the dimensions and check the results (you should have only the measures).
2, Copy the original chart again, this time create one extra copy for each measure but leave the dimensions and only one Measure per chart (you will have four new charts). Check the results.
Also, check if you don't have the dimensions checked to exclude null values. This may be impacting your values.
So, this is a diagnostic phase you are doing to try to identify the problem. Next we can think about how to solve them.
Please let us know the results!
Regards,
Mark Costa
Read more at Data Voyagers - datavoyagers.net
Follow me on my LinkedIn | Know IPC Global at ipc-global.com
Superb !!! Neat clear solution.