Lead time error and production lead time error calculation in IO module

[former_member696146]

Hello Experts,

Please help me with my queries :

a) My understanding is that with IO module of SAP IBP,forecast error CV calculation is possible. Do we also have an option of IBP system arriving at lead time error CV and production lead time error CV automatically ? Or is this required that the user has to calculate separately(manually,outside of IBP system) and the same to be fed as an input to the optimization run manually ?

b)If not currently available, is there any plan in near future to implement this functionality in the system.

Thanks,

Praveen

[lev_degtyarov · Accepted solution]

Hello Praveen,

Of course actual lead time and lead time variability can be calculated in IBP.

You need to load orders history and good receiving data from source system (e,g, S4) in IBP for that. Than add calculation formulas

for PLEADTIME and PLEADTIMEVARIABILITY.

See example below

Regards,

Lev

[former_member696146 · Accepted solution]

Hello Lev,

Thank you for the wonderful suggestion and a detailed reply. It gives a in-depth know-how on the procedure as how the lead time error CV can be calculated with IBP system. Most of the approach is quite clear except for the last step where I need few clarifications :

• a)Calculated PO lead time (days) Final –Is this the result of removing some outlier records which in-turn brings down the average lead time from say 95 to 80 ( second line of last screenshot) ?

• b)My understanding on the calculations of the PO lead time CV is as follows :
• Step 1 : Std deviation = [PO lead time individual records (Actual) -Calculated PO lead time (days)]

• Step 2 : Calculate individual variance number =square of standard deviation numbers

• Step 3 : Calculate Average of the previously arrived variance number

• Step 4 : Arrive at actual standard deviation by using the formula = Sqrt(Variance number)

• Step 5 : PO lead time CV is calculated with a formula CV =Std deviation / Calculated PO lead time (days)

• Please confirm on my understanding.
• c)Also in the last webinar (for IO) under product road map overview for V2011-Planned Q4 2020 the following topic is also documented :

• “Adaptive master data: Consume lead time and lead time variability (prod, trans, vendor) from SAP S/4HANA”

Does this mean that the lead time variability is also being developed and being released in the upcoming version. Do you have any idea on the same ?

Can you please help me clarify my query ?Thanks once again for your efforts and sincerely appreciate the same.

BR,
Praveen

[lev_degtyarov · Accepted solution]

Hello,

Praveen, see my comments below in bold

• a)Calculated PO lead time (days) Final –Is this the result of removing some outlier records which in-turn brings down the average lead time from say 95 to 80 ( second line of last screenshot) ? Yes, this is the final results that consider outliers and also minimum number of order items (10 in my example). For the 2nd record in last snapshot I have history only for 6 order lines => not enough statistics => could not reliable => go with default values.

• b)My understanding on the calculations of the PO lead time CV is as follows :
• u can do as follows:
• step 1. Actual LT for each individual record = individual record GR date - individual record Create Date
  
• step 2. Average Actual LT for each Product-Source-LocTo = avg (Actual LT for individual record)
  
• step 3. Std dev for each Product-Source-LocTo = SQRT (sum([Actual LT for each individual record - Average Actual LT for each Product-Source-LocTo ] ^2)/(n-1))
  

• step4. Actual LT CV = Std dev for each Product-Source-LocTo / Average Actual LT for each Product-Source-LocTo
• c)Also in the last webinar (for IO) under product road map overview for V2011-Planned Q4 2020 the following topic is also documented :

• “Adaptive master data: Consume lead time and lead time variability (prod, trans, vendor) from SAP S/4HANA”

Does this mean that the lead time variability is also being developed and being released in the upcoming version. Do you have any idea on the same ? Didn't heard about it. I suggest this can be master data calculated by Supply Chain Consulting Notes (Lead Time Monitor). This is an enchancemant note that can be installed on top of S/4 or ECC

Regards,

Lev

[former_member696146 · Accepted solution]

Hello Lev,

Thank you once again for the wonderful and patient explanation.Appreciate the same.

BR,

Praveen

[former_member718481 · Accepted solution]

Hi Lev,

This was great information and very informative! I apologize in advanced if I am not using the right channel, but I just had a quick question.

In the past, there was a knowledge document in PowerPoint format which outlined each step for configuring the lead time and lead time variability calculations in SAP IBP. I believe the author of this particular knowledge document was atul.bhandari.pgh where he walked through the steps for creating Stock Transfer Orders MD & Production/Purchase Orders MD, calculating lead time and variability through calculations, and then tying those calculation back into the standard key figures to be considered by the IO algorithms. I've been searching for this very rich content for some time now, but I cannot find it anywhere.

Do you know the document I am referring to? I believe the deck is titled "Calculating Lead Time and Lead Time CV in IBP" or something similar. If so, do you mind sharing it?

Best Regards,

Shiv

[former_member34 · Accepted solution]

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[lingaiahvanam]

Hi,

You are right forecast error CV is possible.

Key figure PLEADTIMEVARIABILITY - Production Lead Time Error CV and TLEADTIMEVARIABILITY - Transportation Lead Time Error CV consider static value from the attribute.

Best Regards,

Lingaiah

[former_member696146]

Hi Lingaiah,

Thank you for your response.Is there any possibility in near future, that the lead time error CV calculation is designed on similar lines to that of forecast error CV calculation(program calculating the error automatically). This would help me in communicating the same with the customer.

Thanks,

Praveen