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#Unique0 personne en discute

I have a table of SLA measures for tasks in a Sales Quoting Team that's structured like this:

 

+----------------------------------------------------------------------------------...

 

VendorA---------------------------------------+VendorB----------------------------+...

----------------------------------------------|-----------------------------------|...

TaskID   1131  1132  1132  1133  1134   1135  |                                   |

Type     Quote Quote Quote Order Advice Quote |    (Same Structure as VendorA)    |

Minutes  32    17    45    55    65     12    |                                   |

+---------------------------------------------+-----------------------------------+...

 

The basic rules are that:

 

1) Each TaskID has one activity type only, although there may be several TASK steps (as in 1132 above)

2) I need to sum the minutes for each of the unique TASK IDs for each vendor

3) Each Type of TASK has an SLA measure (eg: Quotes are in SLA if all steps done in 60 minutes total)

4) Comparison of (2) and (3) tells me how many TASKIDs were in SLA

 

The transformation i'm trying to end up with is the above to:

 

+VendorA-----------------------------------------------+VendorB-----

 

a) countd(TaskID)                                      |

b) #Unique TASKIDs that met SLA                        | (Same for VendorB)

c) Subtract Met SLA from Total to give Missed SLA      |

d) Calculate Percentage Met SLA divided by Unique Tasks|

-------------------------------------------------------+------------

 

These then get thrown up onto a graph

 

So the above table would yield (for Vendor A) Countd(TaskIDs) of 5, Unique Tasks that met SLA of 4 (only TaskID 1132 went over it's SLA measure), Missed = 1 and SLA achieve = 4/5 = 80%.

 

I have (a), (c) and (d) working correctly. However, (b) is quite a nightmare. Started off marking TASKS with a 1 for in SLA or 0 for outside. I can do a window_sum to correctly mark each TaskID with the total minutes that TASK is summed to consume in that pane (as a Task Type only maps to one SLA measure, I just do a MIN to aggregate the SLA time allowed on that side of the comparison), but if I count the result, TaskID 1132 gets counted twice (as there are two instances - two substeps in the same TASK - of it).

 

So, I try to have the SLA comparison spin out the TaskID if it's in SLA, or a null if not, and then do a Window_Sum(COUNTD()) to give the correct number of unique TaskIDs that achieve SLA for that vendor. However, Tableau then disallows entry of the calculation, on the grounds that it can't handle IF statements in a Calculated Field (which I need to assess whether the TASK is in SLA or not) that can throw nulls.

 

Any ideas how to squeeze logic in and report the correct numbers?

5 réponses
  1. 17 juin 2012, 21:54

    How about the attached?

     

    (side note, I have no idea how recursion would play a role in this)

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We have a standard dashboard that shows the key business dimensions of any profitable business; to make more profit, you sell more products, to more people, more often and at higher margin (increased sell price and/or lower cost). One of the graphs I generate to this end is the average number of unique part numbers customers buy, so we can measure our success over time of customers buying a increasing range of products from us.

 

I have an extract that contains a list of sales transactions, including customer id (number), part number ordered and an invoice date. I'm trying to work out the average number of unique part numbers sold to each buying customer in each year.

 

I've originally done #unique parts divided by #unique customer ids, but this is clearly wrong; if I did it properly, I should never see less than one unique part number sold a buying customer on average. That said, I can't work out how to get Tableau to spit out the correct aggregation to show the correct average. Any ideas that could get my on my way?

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