The Importance of OTM Post-Implementation Measurement Systems

Transcription

1 Power & Water The Importance of OTM Post-Implementation Measurement Systems GE Power & Water OTM Functional Team Dave Phillips Jonathan Coley Rebecca Hoffman KPIT Joe Macri Imagination at work Imagination at work

2 Abstract This presentation will focus on the measurement systems created by the GE Power & Water OTM functional team as they migrated from their legacy TMS into OTM. Subject matter will include sample metrics showing comparisons of TMS transactional volume, categorization and analysis of support metrics, EDI analytics and automated planning measurements. The functional team will also discuss why these measurements were implemented and how they were developed. 2

3 Agenda Go-Live as the beginning of the journey Transportation Management System (TMS) migration monitoring Support ticket analysis Electronic data interface (EDI) analytics Productivity monitoring 3

4 Go-Live as the beginning of the journey

5 Why pick this topic Most SIG topics dealt with implementation or application run time topics. Few have broached the subject of measuring to achieve success once live. Select OTM Select SI Provision KICK OFF REQUIREMENTS DESIGN BUILD TEST TRANSITION GO-LIVE TYPICAL SIG TOPIC RANGE 5

6 Metrics evolution Some early metrics were system performance oriented Agents, SQL, Reports and SOA Initial Go Live Pre 12 KPIT projects roll out February 14 Migration to Mavenwire October 14 This, however, did not account for user adoption over the legacy system, user support issues, veracity of data from 3 rd party sources June 12 KPIT Support Assessment April 14 KPIT OTM and SOA managed services 6

7 Metrics development objectives Knowledge base to find the right data Example, EDI 997 is often thought of as transmission success However, this is acceptance to a trading partner s translator, not target application Thorough and effective addressing of issues true fix, not just a Band-Aid Example, using an agent to fix a process issue in OTM when the data which caused the problem comes from a flaw in an integration 7

8 Transportation Management System(TMS) migration monitoring

9 Why no FTI Need to join data from both OTM and legacy system Require transactional reporting daily and weekly Technical expertise Oracle PL/SQL Flexibility and consistency Leverage standard well-tuned code Replicated DB in hosted environment 9

10 Percent TMS transactional volume Total percentage Transportation Management (TMS) usage Fiscal week Merge legacy and OTM into single dataset Define use cases by billing code Keep platform flexible and nimble Percentage legacy Percentage OTM 10

11 TMS transactional volume Total Transportation Management (TMS) usage by volume Fiscal week View impact of new integrations Business-specific factors driving leakage Legacy OTM 11

12 Percent TMS transactional volume Business-specific OTM migration leakage by mode and region Fiscal week Detail report included for root cause analysis Identify router or supplier non-compliance Determine new use cases driving non-compliance Percentage legacy Percentage OTM 12

13 Support Ticket Analysis

14 OTM ticket volume normalized by weekly shipment volume without admin 7.0% 6.0% 5.0% 4.0% 3.0% 2.0% 1.0% 0.0% 27_15 26_15 25_15 24_15 23_15 22_15 21_15 20_15 19_15 18_15 17_15 16_15 15_15 14_15 13_15 12_15 11_15 10_15 09_15 08_15 07_15 06_15 05_15 04_15 03_15 02_15 01_15 Normalized wo Admin Fiscal week Linear (Normalized wo Admin) Monitor stable operations despite new integrations or functionality 14

15 Pareto running 5 week ticket volume categories Drive root cause analysis, categorization and FMEA Deep dive into sub-category level Keep support costs level despite increasing volume and complexity 15

16 Electronic Data Interface (EDI) Analytics

17 EDI metrics Establish EDI connectivity Define success measurement 95% Event Update 24 hour Event Span 98% Transmission Success Identify data sources OTM for Tender offer/event Updates FPC for match file details Middle-ware visibility? Does received (997) really mean success? Monitor metrics constantly IF IT DOESN T GET MEASURED, IT DOESN T GET DONE 17

18 EDI metrics Pickup and delivery event compliance-good performance Compare I_TRANSACTION tender offer to I_TRANSACTION shipment status to produce metrics 18

19 EDI metrics Pickup and delivery event compliance-downward trending Monitor constantly for trends 19

20 EDI metrics Pickup and delivery event compliance-span measurement Span is an indicator of data quality 20

21 EDI metrics Pickup and delivery event compliance-span measurement Carrier A Carrier B Carrier C Carrier D Carrier E Carrier F Carrier G Carrier H Carrier I Carrier J Carrier K Carrier L Carrier M Carrier N Span is an indicator of data quality 21

22 Freight payment matching Comparing OTM match file publications to FPC shipment matches If it doesn t get measured, it doesn t get done 22

23 Productivity Monitoring

24 Percentage planned Total percent planned Automation vs. manual Fiscal week No rate Easily view overall % automation vs. manual Shifts in levels are easily detected Planning failed Auto planned 24

25 Percentage planned Total percent planned Automation vs. manual Fiscal week No rate Legitimate exception Planning failed Auto planned Clearly view opportunities falling outside of autoplan Trends can quickly be root-caused Accurate operations cost estimates 25

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