IFIP 8.3 task force

1. IFIP 8.3 task force Learning from case studies in decision making & decision support 5th April 2007, UCC

2. “Putting the P back into ERP” • Does ERP help managers do their work • Who gets the benefit, HQ or site? • Writing the case studies (finding the thread) • Finding the dependent variable (IS, Org, DM) • Framework to model the gap between reality and ERP • Learning from case studies on decision support?

3. Research questions • Is there a gap between ERP & reality? • Significance of gap for mgt decisions? • How should this gap be managed?

4. The cases

5. 2 in depth cases with embedded units of analysis (site and HQ)

6. Field data can be sliced & diced

7. For Mfg, # observations is still high

8. Case findings • Data • Organisation and applications • Key management decisions, role of ERP

9. Data • BI layer on top of ERP introduces data replication reporting latency • Data handling (ETL) re-introduces data integrity and timeliness issues • Metadata in BI tools redundant with respect to ERP • Decision support required by managers is aggregate operational data • BI tools are used to “bridge the gap” between operational systems and reality. • BI = glue connecting operational systems to the real world • BI becomes critical to the organisation, and skills are rare

10. Virtualisation • Virtualisation: capturing & storing data relating to changes in the physical environment in an information system • A measure of the degree to which information systems can reflect business reality • Pre-supposes a structure (database), as data captured is related to a logical entity

11. Turning raw data into information = value-adding process

12. iValue Chain example * Capture at source eg. match physical goods received to a stock item in the system

13. Integration at a data level • The level of “inter-connectedness” of IS • # relationships in the database • Reduces the risk of redundancy in system • Ensures integrity • Can boost system performance

14. Integration at a process level • Logical steps can be linked and triggered • Output from step 1 = input for step 2 • Automation of administrative processes • Flow of work through departments not reliant on human intervention

15. Integration introduces latency

16. Integration ≠ data integrity • Data integrity means closing the gap between reality and it’s virtual mirror • Golden data: right first time & all the time • One version of the truth • If business changes, rules need to change

17. But ERP cannot be changed • Bureaucracy around change management • In any case, the answer is no • Business often asked to change process • Investigative skills have been centralised • Data integrity is now de-centralised • So gap inevitably widens, requiring > BI

18. Writing the case studies • The horizontal story • Making sense by theme • The vertical story • Finding interdependence

19. Findings • Data integrity and investigative power • Technical latency • Planning versus actual data • Coping with changing business models • The widening functionality gap • Use of BI tools to bridge the “gap”

20. How managers do their work • What is happening? Actual • What should be happening? Plan • What therefore would happen if? What-if? • Adjust plan and/or change actual Manage

21. Where do managers get their info? • What is happening? ERP + BI • What should be happening? Manual • What therefore would happen if? ? • View of actual data is improved …

22. But business models evolve • High margin to high volume • Hardware to software & service • Manufacturing becomes logistics • Gap opens between ERP & reality

23. The zipper

24. IS for management Physical Virtual Actual Plan

25. Framework to model the gap Decision layer ------------------ Reporting layer (pivots, broadcast rules, …) ----------------------------------------------- Consolidation logic and reconciliation (meta data) ----------------------------------------------- Interface layer (from planning systems) ---------------------------------------------------------- Extraction layer (which tables, when, where, …) ---------------------------------- Transaction layer (ERP)

26. Themes • ERP no different than any other TPS • Change Management bureaucracy • Goal focus driving behaviour • Hard vs. Soft goals • Latency

27. GSK local “wins” – Jun 2005 • Data integrity • Management accounting • Trust in data? • But: no ability to change anything! • Diffusion of knowledge: JF • PS. Both JF and his boss now left!

28. Post Go Live • The technical support offsite is atrocious. We are very very disappointed with that. … • Since the core team moved away, and since the next wave started for SAP implementation, they lost interest

29. Research on decisions difficult • Managerial decision making is fast • Characterised by deadlines • Difficult to prioritise in terms of importance • Use “the best available information” • Defining role of IS in DS is tricky

30. Solution: focus on goals • Unit of analysis is goal, not decision • Managers define the goals, not researcher • If it’s a goal, it must be important • Measure IS role in goal achievement • But does it work?

31. Post-ERP process improvement

32. Why no role for ERP team or IS? • Don’t have the skills? • Don’t have the enthusiasm? • … • Neither company seems to be capitalising on ERP learning experience

33. Out

34. Post go-live example • “There was an awful lot of resources thrown at go-live, most of those resources were gone after go-live. Trying to get something fixed, it wouldn’t happen.” • “In order to actually utilize it in a way that actually improves our lot, took, is still taking, quite a long time, and if you can’t do it yourself, it’s even worse, because you can’t get IS available, at times to do the work.“

35. GSK local “wins” – Apr 2004 • More efficient Sales and Distribution processes • Management of bulk solvent • MRP for material spares • Better procurement process • Simplified labelling • Real-time view of stock levels

36. Ownership - Apr 2004 • Information • Answer many reporting requirements = Excel • Data • Single instance, remote server • Requirement for local data warehouse • 8 new people in full-time data maintenance • Process • No more fasttrack orders! • Changes to template for local needs difficult • Subject to changes made on behalf of other sites

37. Findings • Goal setting in MNC’s seems to be increasingly cross functional • Goal setting in MNC’s seems to be increasingly quantitative “Load and chase” mentality • Integration implicit in ERP systems is cross functional • Impact of this integration on transaction processing is explicit • Impact of this integration on decision making is not explicit • ERP processes notoriously inflexible • Respondents vary in understanding of role of ERP administrative processes

38. Impact on management decision making? • Jury’s out for operational performance • Many functions maintain local DW’s for decision support • Data volumes become a performance issue • Questions could be refined: • How well does ERP support the measurement of basic operational goals / metrics (revenue, capacity, inventory, billings, bookings, backlog, …) • Can an off-line decision making model that requires actual figures be accurate if not integrated with ERP? • At what point does the mixture of on-line and off-line manual systems become unreliable?

39. Outcomes • Framework for assessing the value and impact of “integration” across business functions • Decision process orientation in analysing managerial requirements (not transactional / data oriented) • (Management by Objective) MBO strategies to include education on decision making processes and tools for their achievement • Creation of technostructure