HWA-Observability over Splunk: Generating Business Metrics: Inventory Planning

In this Blog , we will look at how important Business Metrics can be generated over a Flow within HWA which can then be analysed over Splunk through Attractive Dashboards and meaningful insights can be derived from them.

Inventory Planning Case Study :
A Detailed Blog has been already written on the Flow itself earlier :
https://www.workloadautomation-community.com/blogs/case-study-inventory-management-with-workload-automation
 
We are now looking at how to generate some important Business Metrics out of the Flow and pass them along to Splunk for better visualization and derive Important Business Insights from the same.

Here is a brief summary of the Flow :

A typical Material Requirements Planning Flow of a Company could comprise of jobs which would perform the following with goal being to be as closed to a balanced plant as possible :

1. MRP Jobs which would compute the Materials requirement for each Inventory Item for processing this week’s orders : In this case , we are considering Angle Brackets , Machine oil , Polish , MS-Sheets
2. A Set of Current Inventory Jobs which would compute the Current Inventory Level of each inventory Item : Angle Brackets , Machine oil , Polish , MS-Sheets .
3. A Set of Extraction jobs which would parse out the joblogs of these jobs and extract the inventory levels for both MRP and Current Inventory.
4. A Set of Variable Passing Jobs which would pass the variables for Machine Oil , Polish , MS-Sheets , Angle Brackets etc for each MRP Level as well as Current Inventory Level.
5. A Set of Comparison jobs would compare the Current Inventory Level with MRP Inventory Level for each Inventory item : Angle Brackets , Machine Oil , Polish , MS-Sheets.
6. If the Inventory level is low to process this week’s orders , a Procurement Order is placed on a portal with all known vendors.
7. If the Inventory Level is high to process this week’s orders , a Sales order is placed on a Portal likewise.

Metrics Derived :
Some Important Metrics are derived from the Flow :

Inventory Turnover Ratio 

Ideally a value between 2 and 4 is set to be ideal .

Below Metrics were generated from our Flow :

ITR_MSSHEET=COGS_MSSHEET/AVG_INV_MSSHEET=4.46
ITR_POLISH=COGS_POLISH/AVG_INV_POLISH=0.72
ITR_ABRACK=COGS_ABRACK/AVG_INV_ABRACK=2.63
ITR_MACHOIL=COGS_MACHOIL/AVG_INV_MACHOIL=9.02
​
Sell-through Rate :
Sell-Through Rate measures the amount of inventory you've sold in a month versus the amount of inventory shipped to you from a manufacturer. Sell-through rate is an important retail sales metric that allows you to monitor the efficiency of your supply-chain.
Below metrics were generated from our Flow :
 
SELLTHROUGH_MSSHEET=(INVSOLD_MSSHEET/INVRECVD_MSSHEET)*100=73%
SELLTHROUGH_POLISH=(INVSOLD_POLISH/INVRECVD_POLISH)*100=78%
SELLTHROUGH_ABRACK=(INVSOLD_ABRACK/INVRECVD_ABRACK)*100=46%
SELLTHROUGH_MACHOIL=(INVSOLD_MACHOIL/INVRECD_MACHOIL)*100=94%
 
Inventory Days :

The Metrics generated from our Flow are as below :
INV_DAYS_MSSHEET=(AVG_INV_MSSHEET/(COGS_MSSHEET/7))*7=10.97
INV_DAYS_POLISH=(AVG_INV_POLISH/(COGS_POLISH/7))*7=9.59
INV_DAYS_ABRACK=(AVG_INV_ABRACK/(COGS_ABRACK/7))*7=18.59
INV_DAYS_MACHOIL=(AVG_INV_MACHOIL/(COGS_MACHOIL/7))*7=5.43
 
Cost of Goods Sold :
Cost of goods sold (COGS) refers to the direct costs of producing the goods sold by a company. This amount includes the cost of the materials and labor
directly used to create the good. It excludes indirect expenses, such as distribution costs and sales force costs.
Below metrics are generated from the ERP System of the company , retrieved through a HWA SAP Job or HWA Oracle EBusiness Suite Job :
 
COGS_MSSHEET=$125000
COGS_POLISH=$23000
COGS_ABRACK=$20000
COGS_MACHOIL=$27000
 
Integration with Splunk :
We can integrate Splunk readily with HWA v10.1 as we are now generating WA Merge logs in JSON Format ,so we can readily ingest into Splunk and also any additional Metrics generated in joblogs can be sent as a curl payload through a Job as follows :
/bin/curl "https://10.14.82.155:8088//services/collector" -H "Authorization: Splunk d7ced0c4-7709-4ccc-a192-e90b223fec35" --insecure -d '{"sourcetype":"manual","event":{
"COGS_MSSHEET":"125000",
"COGS_POLISH":"23000",
"COGS_ABRACK":"20000",
"COGS_MACHOIL":"27000",
"ITR_MSSHEET":"4.46",
"ITR_POLISH":"0.72",
"ITR_ABRACK":"2.63",
"ITR_MACHOIL":"9.02",
"INV_DAYS_MSSHEET":"10.97",
"INV_DAYS_POLISH":"9.59",
"INV_DAYS_ABRACK":"18.59",
"INV_DAYS_MACHOIL":"5.43",
"SELLTHROUGH_MSSHEET":"73",
"SELLTHROUGH_POLISH":"78",
"SELLTHROUGH_ABRACK":"46",
"SELLTHROUGH_MACHOIL":"94",
}}'
 
/bin/curl "https://10.14.82.155:8088//services/collector" -H "Authorization: Splunk d7ced0c4-7709-4ccc-a192-e90b223fec35" --insecure -d '{"sourcetype":"manual","event":{
"CURR_MACHOIL":"2993",
"CURR_ABRACK":"7589",
"CURR_MSSHEET":"27991",
"CURR_POLISH":"31541",
"MRP_ABRACK":"21617",
"MRP_MACHOIL":"27012",
"MRP_MSSHEET":"16544",
"MRP_POLISH":"12698",
}}'
 
The Payload ingested into Splunk can be used to create attractive Dashboards in Splunk as follows :

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Author's Bio

​​Sriram V, ​Senior Technical Lead
​
I have been working with Workload Automation for the last 14 years , have had a chance to work with 100+ Customers from various industries as an Implementer , SME , India SME in IBM before also getting a chance to directly work on the Product Support Side as a DevOps Engineer on IBM SaaS Offering of the Product ,also had a stint with Lab Services Team developing Conversion Utilities to move from Competition,  have been working as a Technical Advisor on the Product lately on the Tech Sales Side.