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Interactive Data Views

Interactive Data Views

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Interactive Data Views

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  1. Interactive Data Views Day 40 December 4, 2009

  2. Announcements • No quiz 8 • Return quiz 7 • Return xbrl assignments • Graduate student presentations and papers

  3. Interactive Data Views Process of allowing users to select presentation format and type of information they find as most relevant Allows users to disaggregate financial statement information and select only the information they view as most relevant. Some allow users to perform selected calculations

  4. Interactive Data Views May help decision makers overcome information overload by reducing large data sets into simple visuals Shifts cognitive load to the human perceptual system through graphics

  5. Visualization Tools Early use in genetics and biology Business applications lag the sciences by as much as 10 years (West 1995) Today, used in marketing efforts (Lurie and Mason 2007) Beginning to see usage in external financial reporting – maybe internal reporting

  6. IDV Examples • SEC web site • Executive Compensation • Interactive Financial Reports • http://viewerprototype1.com/viewer • Financial Explorer • http://209.234.225.154/viewer/home/ • Corporate web sites • Stock price information • http://www.ford.com/about-ford/investor-relations/investment-information/stock-chart • Enumerate - financial and non-financial information • http:///www.enumerate.com • http://production.investis.com/bp2/ia/annualdata2007/

  7. SEC Executive Compensation Viewer

  8. SEC Interactive Financial Reports

  9. SEC Interactive Financial Reports

  10. SEC Financial Explorer IBM

  11. SEC Financial Explorer Pfizer

  12. Corporate Website – Stock information Ford

  13. Corporate Web site – Financial and non-financial information

  14. Corporate Web site – Financial and non-financial information

  15. Key Terms Visual representation Selection, transformation, and presentation of data (including spatial, abstract, physical, or textual) in a visual format that facilitates exploration and understanding (Lurie and Mason 2007) Visualization tools Intermediate step in converting data into insight Data characteristics such as dimensionality, scale (categorical, ordinal, and metric) and cardinality (binary vs massively categorical variables) affect which tools are appropriate.

  16. Key Terms Visualization techniques Using color, size, shape, texture, orientation, and brightness to portray some dimensions; distortions approaches to highlight some data while providing context; graphic portrayals of hierarchical and network relationship, and interactivity

  17. Data transformations Potentially affect the ultimate insights derived from the data The problem visual representations may allow users to see patterns and outliers easier, make certain information more salient and other information less salient, and show detailed information on specific alternatives (i.e. improve decision quality) however, visual representation may accentuate biases in decision making and lower performance by increasing attention to particular attributes or less diagnostic information

  18. Implications of IDVs for Decision Making • Task • Characteristics • Directed vs exploratory • Task type • Complexity • context Decision Making Frame • Decision Making Processes & Outcomes • Information acquisition • Search strategy • Time spent on decision • accuracy • Interactive • Data • Visualization • Characteristics • Interactivity • Information selection/navigation • visual representation • Decision Maker Characteristics • expertise • Experience • Cognitive style • Memory

  19. Characteristics of Interactive Data Views We focus on two characteristics of interactive data views that are likely to affect decision makers Visual perspective Can representation be manipulated by the user (i.e., its interactivity)? Does the representation allow users to display an overview of large number of data points and/or a more focused detail information on particular data points of interest? Information content Vividness Evaluability Framing

  20. Visual Perspective Interactivity Since users can restructure the information environment through interactivity, they may create a better match between task and decision environment which should improve decision quality and/or reduce effort required (Eick and Wills 1995) Restructuring can lead to more compensatory decision making but is contingent on effort involved (Coupey 1994) Suggest that decision makers using interactive visualization tools will be more likely to consider multiple factors than users with traditional report

  21. Visual Perspective Depth of Field Provide contextual overview vs detailed information Affects how information is accessed and evaluated Money.com MarketMap = investors view market, industry, and individual stock performance simultaneously By increasing accessibility of contextual information, Makermap may increase decision makers’ use of category relative to alternative-specific information i.e. use industry and market performance in stock selection than when using traditional line graphs of price changes for a single stock Changes in depth of field may lead to overconfidence or underconfidence

  22. Information Context Vividness (salience or availability of particular information) More vivid visual information is more likely to be acquired and processed before less vivid visual information (Jarvenpaa 1990) May come at cost as increased focus on graphic information may ignore other relevant information (Glazer et al. 1992) Evaluability (ease with which information can be compared) Decision makers are more likely to notice changes, recognize outliers, and see patterns more quickly Leads to increased acquisition, weighting, and processing of information Whether graphic or textual presentations are superior depends on fit between alternative representation and nature of task Graphics – detect trends, compare patterns, interpolate values Textual – retrieve specific data values Framing (how a given representation changes the reference point or scale against which information is evaluated) Can aggravate biases; losses

  23. Task Characteristics Complexity Impact of visual representation is more likely to be significant when decision makers are using IDVs to complete complex tasks Context Need to match visual representation method with task complexity (cognitive fit theory)

  24. User Characteristics Expertise Expert decision makers may not be as likely to allow visual representations to bias the decision making process Memory Impact of visual representation on memory may impact decision making Preferences The degree to which decision makers hold established preferences may impact how changes in visual representation affect the decision making process

  25. Summary Implications for General Decision Making Visualization has potential to offer decision makers ways to improve efficiencies reduce costs gain new insights make data more accessible increase satisfaction At same time, visualization may accentuate biases in decision making

  26. Questions to consider If you were a corporate controller, what are the advantages of displaying financial information in IDVs? What are the disadvantages?

  27. Questions to consider If you were an investor, what are the advantages of viewing financial information in IDVs? What are the disadvantages?

  28. Questions to consider If you were an external auditor, what are the issues you need to address if your client displays financial information in IDVs?

  29. Implications for Financial Statement Preparers Rendering issues Do you present audited or unaudited information? Materiality at data level

  30. Implications for Financial Statement Auditors Is audited information presented? How do users determine if information is audited? i.e., disclaimer or presence of audit report? Materiality at data level

  31. Implications for Financial Statement Users Provides data in preferred format (i.e., table, graph, or both) Allows user to view only the data user determine is relevant Facilitates comparison between companies between periods between divisions / products May accentuate biases; highlight less relevant information

  32. Conclusions Interactive data views –tool preparers to communicate financial information and for users to acquire and evaluate financial information May have both positive and negative consequences to decision making Any questions?