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Stephen Few, a respected IT innovator, consultant, and educator has studied the art and science of visual presentation for many years. In a White Paper prepared for Cognos Corporation, he presents seven principles for the effective display of quantitative information. The first of these is presented below:
“When you wish to get your message across—any message—whether in conversation, in writing, or in a graph, irrelevant content is distracting. Don't make people wade through meaningless visual content in your display to find what really matters. It has become common today, even in business graphs, to include all sorts of nonsense, such as cute pictures in the background or the addition of a third dimension to bars, lines, and pies. Despite good intentions (if you consider attempts to entertain or impress good), visual content of this sort is something that people's eyes must scan and brains must process, without any payback, for it is meaningless.”
“Extraneous content not only wastes people's time, it makes it harder for them to get at the message.
The reverse is true as well. Don't design a display that doesn't contain everything people need to make sense of it. Include every piece of information that is part of your message—even notes to explain what might not be clear—otherwise you're communicating poorly. This principle is broken in many graphs today by adding a 3-D effect to bars, lines, data points, and pies.”
If you are new to the macro-area of business intelligence and its tools, this glossary will provide an easy to find guide to some general and specific terms associated with the subject area.
Analytics: Technology approaches that process current and historical data to enhance business management performance such as, to establish policies, assist in making predictions, and multi-level decision making, to name a few.
BI - Business Intelligence: Technology and software applications used to collect, make available, and manipulate business information for effective reporting, planning and decision-making.
BI Consumer: A user of business intelligence information and the products it produces. The terms customer and stakeholder also apply to BI and may sometimes include consumers. However, a customer of BI information commonly refers to the business component or function that pays for the BI process or product. A stakeholder is an entity that has a legitimate interest in the information or product and can include users, consumers, customers, even stockholders and any other party given access to the intelligence.
Business Consumers: Business consumers are the rank and file members of the organization's functional business area teams.
Business Intelligence Reporting: A series of software tools and applications that provide advanced management information to decision makers from broadly disparate data sources.
CRM - Customer Relationship Management: Customer relationship management (CRM) is a generic business term that describes approaches used to exploit the inherent information associated with a company's customers. This includes many classes of BI techniques involving the capture, storage and analysis of customer information.
Dashboard: Includes digital dashboard, executive dashboard, or enterprise dashboard. BI tools used by decision makers to visually monitor the state of the enterprise. The term derives from the analogy of the automobile dashboard, from which the operator (executive) can drive or operate the business.
EEA - Economic Espionage Act of 1996: A Federal statute directed to theft or misappropriation of trade secrets. The law applies to BI due to the goals and practices of BI in regards to collection and analysis of both open and limited source information and the legal and ethical considerations involved.
Executives: Executives are the key decision makers within an organization. An executive's influence spans the strategic and tactical operations of the business and they are the main drivers of most policy components.
IT- Information Technology Administrators: IT Administrators are the BI user group including, information architects, technical support, and other IT professionals that configure, deploy and support the entire BI technology suite.
KPI - Key Performance Indicators: The term used for the most important information residing in a business' varied stores of raw data. One of the principle objectives of BI is to use research and analytical techniques to identify the KPIs and easily separate them from the chaff for processing into reports and other sophisticated management products.
Managers: Managers consist of the tactical-level executers of corporate policy and are responsible for directing most functional business area activities.
Performance Management: Performance Management is a collective term for the BI/management approach also known as business performance management (BPM), corporate performance management (CPM), or enterprise performance management (EPM). The discipline encompasses systems, methodologies, metrics, processes and software technologies used to identify ways to improve overall business performance.
Performance Planning: The product of applying performance management techniques to the planning and forecasting decision area. Performance planning provides keys to establish a reliable view of the future and empirically determine appropriate courses of action.
Professional Report Authors: Professional report authors, also called ‘power users', are expert authors that are the developer's ‘users of choice' for BI software, despite representing only five percent of users.
Scorecard: Robert S. Kaplan and David Norton introduced the concept of scorecards in 1992. Basically, it is a concept for quantifying business activities and strategies, to give managers a more sophisticated view of the performance of a business. It's ultimate value to BI lies in the relationship of performance driven quantified activities and strategies to the complex analytical and reporting abilities of BI.
DM - Data Mining: The exploitation of large volumes of data for subtle trends and patterns using complex software applications.
OODA Loop - Observe, Orient, Decide, Act: A concept originated by Col. John Boyd, USAF describing the decision cycle as "Observe, Orient, Decide, Act", particularly for strategic and tactical military applications. The approach was adapted for commercial use and frequently employed as a common component of BI. When employed iteratively, an OODA Loop is said to provide competitive advantage through creating a series of responsive, planned actions directed to known criteria instead of scattered, spontaneous reactions.
Performance System: A performance management term that refers to the subset of business intelligence tools that address data access, manipulation, and reporting on the functional business unit level.
Stephen Few, a respected IT innovator, consultant, and educator has studied the art and science of visual presentation for many years. In a White Paper prepared for Cognos Corporation, he presents seven principles for the effective display of quantitative information. The sixth of these is presented below:
“Not all information is created equal. It is often the case that some information is more important to your message than other information. You can communicate this fact in a graph by making those items that are most important more visually dominant (salient). It is your job, if you wish to communicate effectively, to direct people's eyes to the most important parts of the display, so they are sure to adequately focus on them. [If t]he title of [a] graph … clearly states at least part of its purpose[, say] to highlight what happened in March. This purpose [could be] visually reinforced by making the bars in March more salient than the others, … by placing borders around them.”
Stephen Few, a respected IT innovator, consultant, and educator has studied the art and science of visual presentation for many years. In a White Paper prepared for Cognos Corporation, he presents seven principles for the effective display of quantitative information. The fifth of these is presented below:
“Values that we display in graphs are sometimes intimately related to one another and sometimes they are discrete. The way we visually display these values should make it easy to see, without effort, this distinction. […In such a] graph, lines connect values, suggesting a relationship between them that doesn't exist. [...Likewise, depicting data, such as geographic] regions North, East, South, and West are discrete, so values that measure something going on in these regions should be displayed as discrete. Connecting them with a line is misleading. Doing so forms a pattern of upwards and downwards slopes that are utterly meaningless.”
Stephen Few, a respected IT innovator, consultant, and educator has studied the art and science of visual presentation for many years. In a White Paper prepared for Cognos Corporation, he presents seven principles for the effective display of quantitative information. The fourth of these is presented below:
“Graphs are sometimes intentionally designed to deceive, to misrepresent the truth by visually encoding values in a way that does not correspond to the actual values themselves and the differences between them. Even more often, however, people unintentionally misrepresent data in this manner, simply because they don't understand this principle and how to follow it. The most common way that this occurs involves bar graphs with quantitative scales that don't begin at zero. Because the lengths of bars encode the values they represent, the full length of the bar must be displayed, beginning from zero, for the values to be encoded properly." Few refers to a graph and says "notice that actual sales in the East region appear to be twice as great as planned sales, but in fact, this is far from the truth. Actual sales are only 5 percent greater than the plan. When you use a graph to communicate, people should be able to look at the graphical representation alone to compare differences in values. If the graph doesn't support this operation, what's the point of using a graph?”
Stephen Few, a respected IT innovator, consultant, and educator has studied the art and science of visual presentation for many years. In a White Paper prepared for Cognos Corporation, he presents seven principles for the effective display of quantitative information. The third of these is presented below:
“There is an important set of visual properties that are called “preattentive attributes” of visual perception. They are preattentive in that the process of perceiving them does not involve conscious thought; it is automatic and immediate. This includes such properties as an object's length (for example, the length of bar in a bar graph), its 2-D location (for example, the position of a data point in a scatterplot), its size, its shape, its orientation, its hue, and so on. If objects in a graph vary from one another along one of these properties to a great enough degree to appear different, we see those differences immediately, without conscious effort. For example, if a single data point is orange in a scatterplot that contains 100 data points, 99 of which are black, the orange dot will stand out as different. We can use this knowledge to intentionally make particular items in a graph stand out as different or important.”
“Of the full set of preattentive attributes, a few are perceived quantitatively. By this I mean that we perceive differences between varying expressions of a visual property (for example, length, exhibited as long bars, short bars, medium-length bars, etc.) as greater than or less than one another. Apart from these preattentive attributes, those that are not perceived quantitatively are simply seen as different, such as the different hues of black, green, blue, orange, purple, and so on. Two of the preattentive attributes that are perceived quantitatively are also perceived with a fair amount of quantitative precision: length and 2-D position.”
Stephen Few, a respected IT innovator, consultant, and educator has studied the art and science of visual presentation for many years. In a White Paper prepared for Cognos Corporation, he presents seven principles for the effective display of quantitative information. The second of these is presented below:
“Because differences in visual properties, such as color, are used to communicate actual differences in the information itself, visual differences should never be used arbitrarily. When people notice visual differences, they try to discern the meaning of those differences. Don't confuse people and waste their time by including visual differences that are meaningless. Figure 5 shows a common example of how this rule is broken. What is the meaning of the different colors that appear on the bars? The answer is “nothing.” We already know what the bars represent, because they are labeled as years along the X-axis. Meaningless visual differences such as this gratuitous use of color not only cause people to search for meanings that don't exist, but in this case they clutter the graph with an eye-assaulting abundance of color.”
The spectrum of business intelligence (BI) users spans a group of professionals ranging from programmers, engineers, IT specialists, and scientists on the technical side to salespersons, marketers, accountants, economists, HR pros and operations types on the business side. Additionally, managers and executives are included, cutting across both. In some senses, the management and executive users are frequently removed from the "heat" of the BI battlefield, thus requiring special treatment due to the more generalized nature of their job descriptions.
Presenting business performance metrics to this user group is one of those cases where special treatment in often needed. Specifically, performance reporting techniques that are geared to more effective visual presentation. Stephen Few, in a White Paper prepared for the Cognos Corporation, discussed a number of interesting characteristics of effective visual displays. Graphs, he suggests, were invented to give meaning to quantitative data beyond that contained in a table of numbers.
He goes on to note that both serve a very different purpose and should be selected to present information very carefully. For example, tables are wonderful when the information to be presented requires the observer to choose values. Tables are also useful when precision in the values is required. Graphs, on the other hand, create relationships between values through the discerning of size, shape, or color. As such, there is no substitute for a properly designed graph when communication of trending, patterns, or exceptions is desired.
Stephen Few, a respected IT innovator, consultant, and educator has studied the art and science of visual presentation for many years. In a White Paper prepared for Cognos Corporation, he presents seven principles for the effective display of quantitative information. The seventh of these is presented below:
“When a person examines information on a computer screen or the page of a printed report, a limited amount of the information can be held in short-term memory if comparisons must be made to information on another computer screen or page. Information that is never attended to never gets stored in short-term memory, and even if several chunks of information are attended to, only around four will be remembered when the person moves from one display to the next. This makes comparisons difficult. You can augment people's short-term memory, however, by placing everything that needs to be compared within eye span, so it is readily available for rapid swapping in and out of short-term memory as it is being processed. A popular example is a dashboard that has been properly designed to display everything within eye span on a single screen that people must monitor for rapid processing and comprehension.