Generic business models and standardised processes. Discussion by Lars Thygesen

Transcription

1 Generic business models and standardised processes Discussion by Lars Thygesen

2 Key points Driving forces Business model Reorganising The role of Metadata Use of international standards Acceptance What can we steal (learn) from each other? 2

3 The Norwegian case A pragmatic approach based on our quality work, strategies and international trends Standardisation of processes Modular approach: allowing stepwise implementation Looks familiar: why not steal? 3

4 The Dutch case Very ambitious masterplan Covering everything! Inspiration for all of us Less familiar can we still learn? Is it a cathedral? 4

5 Driving forces Increasing efficiency all organisations not new: all times Reduction of administrative burden isn t there any concrete goal? e.g. in Denmark -25% Intensive reuse of data: Nordbotten: The archive-statistical method 5

6 Who should be driving business redesign? IT people or business? reduction of IT cost mentioned as driver effort is used on calling familiar things something else and less understandable, e.g. steady states BAD, SAD and MAD are pretty weird acronyms! 6

7 7 Business models & principles

8 8 Business models & principles

9 Business models & principles Business architecture data collection shifts from primary to secondary complications because of heavy reuse & interdependencies IT architecture few products (but not so few ) COTS (commercial off-the-shelf) software first choice Considering other NSOs solutions? METIS, MSIS? METIS life cycle model? Can we still borrow from you? 9

10 The Dutch model Five types of steady states: the input base the micro base the stat base the output base the post-output base how different from old model? 10

11 Implementing the business model Reuse & adapt old developments Develop missing parts Major missing parts will be put to the market to be built according to specifications by an outside partner what about using other NSIs? European awarding rules very bureaucratic and cause additional delays Can we do anything about that? preferred statistical methods are documented elementary business functions This sounds similar to the UK BPR project ? 11

12 Organisation Towards functional organisation Risk of sub-optimisation? data collection orders specify the size of a survey, collection modes, nonresponse rates allowed, and the time frame can t it be a matter of balancing price and result? data collection service is a dumb service without knowledge of the content Is this wise? Isn t knowledge a good thing? 12

13 Metadata key roles Metadata driving processes not much is said about this Metadata informing users: 13

14 Metadata informing users Norway s metadata system recognised as exemplary Guiding architectural principle: no statistical data without metadata conceptual metadata structural metadata managerial metadata A model is developed for conceptual metadata for both micro-data and aggregate data This must be interesting! Is it in line with METIS? SDMX Content Oriented Guidelines? 14

15 International standards (1) Statistical Data and Metadata exchange (SDMX) Preferred standard for statistics (UNSC 2009) exchange, sharing, combining, interface to tools metadata guidelines For internal use, data are stored in a format that is standardized as much as possible (preferably open standards) No mentioning of SDMX? Shouldn t SDMX play key role in all reengineering projects? 15

16 International standards (2) The METIS business process model Very general and accepted Facilitates sharing of modules and solutions Shouldn t METIS be used as well? 16

17 Acceptance: α & Ω Machiavelli The Prince Statisticians... I m different! Managing change & people Keeping ownership A huge challenge to leadership 17

18 The fundamental questions How much is really new? Stick to international standards? Sharing and stealing no new wheels Standardisation & change: involvement & ownership 18

19 The End!