The Nature of Systems

1. The Nature of Systems

2. Overview • Define AIS • Define System • Examine parts of Living Systems • Examine reasons NOT to automate • Examine Different System Types • Examine General Systems Theory

3. But First..... • Why are we here? • What changes do you foresee in Accounting in the near-future? • Have you heard about Twitter? • Have you heard about Twitter Annotations • it's a system for almost any metadata to be connected to any Twitter message when it's published. Inside every Tweet is now a space where you could put or find anything, including links out to further instructions or larger bodies of information.

4. Twitter and DJIA “can societies experience mood states that affect their collective decision making? By extension is the public mood correlated or even predictive of economic indicators? Here we investigate whether measurements of collective mood states derived from large-scale Twitter feeds are correlated to the value of the Dow Jones Industrial Average (DJIA) over time.” “Our results indicate that the accuracy of DJIA predictions can be significantly improved by the inclusion of specific public mood dimensions but not others. We find an accuracy of 87.6% in predicting the daily up and down changes in the closing values of the DJIA and a reduction of the Mean Average Percentage Error by more than 6%.” Indiana University's research team Johan Bollen, Huina Mao, and Xiao-Jun Zeng's

5. WHAT IS AN AIS? • An AIS is a system that collects, records, stores, and processes data to produce information for decision makers. • It can: • Use advanced technology; or • Be a simple paper-and-pencil system; or • Be something in between. • Technology is simply a tool to create, maintain, or improve a system.

6. WHAT IS AN AIS? • The functions of an AIS is to: • Collect and store data about events, resources, and agents. • Transform that data into information that management and external users can use to make decisions about events, resources, and agents. • Provide adequate controls to ensure that the entity’s resources (including data) are: • Available when needed • Accurate and reliable

7. So then What is a System? • A system is: • A set of interrelated components • That interact • To achieve a goal • The AIS goal is?

8. These are all Systems Manual Living Automated ERP Machine-Human

9. The reproducer;The boundary;The ingestor;The distributor;The converter; The producer;The matter-energy storage subsystem;The extruder, The motor;The supporter;The input transducer;The internal transducer, The channel and net;The decoder;The associator;The memory;The decider, The encoder;The output transducer Living System Sub-systems • James Miller’s Living Systems (1978) describes 19 sub-systems all “living” systems have • Living = biological (people) and groups of biological (organizations)

10. Miller’s Sub-Systems • Distributor • Moves external inputs or internal outputs around system • Converter • Changes inputs based on needs of sub-system • Producer • Takes inputs and creates new forms to be used by system • To grow, repair, replace or provide energy to system • Matter-Energy Storage • Reproducer • Create replicas of itself • Boundary • Holds system together • Keeps environment out • Entrance/Exit for • Matter-Energy • Information • Ingestor • Brings matter-energy into system from environment

11. Miller’s Sub-Systems • Input Transducer • Brings Information input into the system • Changes information to form suitable for transmission • Internal Transducer • Collects information/Changes form from internal sub-systems • Channel and Net • Route(s) which information take in the system • Extruder • Outputs from the system • Products • Waste • Motor • Movement • Supporter • Maintains relationships among sub-systems

12. Miller’s Sub-Systems • Decider • Receiver of information • Transmitter of information • Used to Control System • Encoder • Takes private information from sub-systems and translates into public information for use by external systems • Output Transducer • Takes public information and transmits it to external systems • Decoder • Translates information to a private form used by internal sub-systems • Associator • 1st Stage of Learning • Creates relationships between information • Memory • 2nd Stage of Learning • Stores information to be used later

13. Should All Systems be Automated? • No • Cost • it may be cheaper to continue carrying out the system functions and storing the system’s information manually. • Security • if the information system is maintaining sensitive, confidential data, the user may not feel that an automated system is sufficiently secure. • The user may want the ability to keep the information physically protected and locked up. Timely disappearance: Metal nanoparticles that clump together and change color under ultraviolet light are used as an ink to create images. In visible light, the clumps break apart and the image fades away in nine hours. Credit: Rafal Klajn

14. Types of Systems • On-line • Real-time • Decision Support • Expert Systems • Knowledge Based Systems

15. Automated Manual System • Four Sub-processes • Business Event Occurs • Recorded on Source Document • Record Business Event • Batch Processed and Input by data-entry clerk • Event Data Store (Sales, Purchases, etc.) • Data Store = Table • Update Master Data • Generate Output

16. Automated Equivalent to a Manual System

17. Online Transaction Entry (OLTE) • Entering business events at time and place the business event occurs • Computer input device used to enter data at source at time of business event • Merging Step 1 & 2 of Automated Manual System • Input/Source document is eliminated • Price data is retrieved from the system • Source documents are printed by the system • Event information in accumulated on tape or disk

18. Online Transaction Entry (Batch)

19. Online Real-time (OLRT) • Three Sub-processes • Business event occurs and is recorded • Transactions saved • Update Master data • Immediate mode • Generate Reports and Support Queries • Reports periodically or on an as needed basis • Support queries to generate unique reports for key decisions on demand

20. Online real-time processing

21. Real Time System • Not the same as Online Real-Time • Controls an environment by receiving data, processing them, and returning the results sufficiently quickly to affect the environment at that time • Require concurrent processing of multiple inputs. • Interacts with both people and an environment that is generally autonomous and often hostile.

22. XBRL XBRL-GL? IBM InfoSphere (Stream Computing) • InfoSphere Streams... ingest, filter, analyze, and correlate potentially massive volumes of continuous data streams. • InfoSphere Streams supports high volume, structured & unstructured streaming data sources • images, audio, voice, VoIP, video, TV, financial news, radio, police scanners, web traffic, email, chat, GPS data, financial transaction data, satellite data, sensors, badge swipes, etc.

23. InfoSphere Example

24. What is Stream Computing? • IBM Video

25. Stream Computing • Stream computing is a new paradigm. • In “traditional” processing, one can think of running queries against relatively static data • for instance - List all personnel residing within 50 miles of New Orleans • With stream computing, one can execute a process similar to a “continuous query” • get continuous, updated results as location information from GPS data is refreshed over time. • In the first case, questions are asked of static data, in the second case, data is continuously evaluated by static questions.

26. Stream Computing

27. Decision Support Systems • Computer system that • Supports • business and organizational decision-making activities (Wikipedia) • Key Features • Provides decision alternatives • Based on model • Human makes final choice

28. Expert Systems • Attempts to mimic the decision making steps of an Expert • If-Then-Else Rules • Output is Decision • Ability to Explain Choice • Ability to Explain non-chosen Options

29. Knowledge Based Systems • Two Basic Types • Threaded Discussion Boards • Database of Information/Knowledge • Database of SME’s • Purpose • Don’t re-invent the Wheel • Ease the process of finding an expert

30. Hierarchical view of Systems • Operational/Transactions • Decision Support • Strategic Planning

31. General Systems Theory • The more specialized a system is, the less able it is to adapt to different circumstances. • The larger a system is, the more of its resources that must be devoted to its everyday maintenance. • Systems are always part of larger systems, and they can always be partitioned into smaller systems. • Systems grow (5-10%/year) • what might this mean for XBRL elements including extensions to it by individual corporate filers. • Currently ~14,000 standard element names • The interactions between components of a system are often complex and subtle. • a change in system component A can cause a change in B, which can “ripple” into component C. • he change in C can cause a “feedback” effect on the original component A • XBRL may eliminate the negative aspects of this ripple effect

32. Why Study Systems? • We will work with systems • We will design systems • We will Model systems