Do not start creating a report or presentation without a clear vision of what to achieve with it. The least goal is to inform about an interesting detection. A higher goal is to make the reader (audience) understand a problem by explaining it. The ultimate goal is to get a decision on a suggestion provided and to cause corresponding actions.

A good report (presentation) will try to answer the questions of the readers (audience). So it is important to know the target audience (e.g. their function, position, network, knowledge, experience, attitude, behavior, worries, cultural background) and their goals, preferences, and expectations.  Do they only want to get informed about interesting detections, or are they looking for an explanation to a problem? Are they willing to make decisions and to act accordingly? Who might object to the message and why?

Mapping the situation means compiling and presenting the related facts. Be sure to cover all relevant aspects and obtain a general consensus concerning the facts. In general, this means not yet describing the given problem but presenting facts and goals already known to the reader or audience. It is advisable to begin with a positive and generally accepted description of the situation in order to prevent early contradictions.

After mapping the situation, introduce the challenge or complication, affecting the reader or the audience. It should make everyone aware of an interesting, critical, or even dangerous problem.

A good introduction raises the relevant question from the perspective of the recipient of how to solve the complication in the described situation. The question at the beginning of each report or presentation then leads to the message, i.e. the answer to the question.

Messages in reports and presentations can detect, evaluate, explain, warn, complain, threaten, excuse, suggest, or recommend something interesting. Make sure to deliver these messages in a complete sentence in order to be understood.

Today, many messages in business reporting are pure detections. Since detections are statements that can be checked whether they are true or false, they should be formulated as precisely as possible.

Explaining the reasons for a detection (explanation) or even deriving a suggestion on how to solve the problem or at least on how to further proceed can add value.

This figure on the left shows a classification of messages with examples from the business environment.
(Source: Hichert, R. and Kornwachs, K.)

Every report, every presentation, and every single page or exhibit can be summed up with a clear overall message. This message usually comes first and is proven afterwards. For the readers or the audience it is more difficult to follow the storyline if the message comes at the end.

Be cautious applying this rule in presentations (not in reports) with bad, unexpected, or unpleasant messages (e.g. layoffs) or in a cultural environment, where directness is considered impolite.

Substantiate the message in order to prove the message by facts and figures. If possible, a presentation slide should itself explain or prove the speaker’s message and not – as very often seen in practice – be explained by the speaker. This can be done by spoken sentences possibly supported by charts, tables, and pictures.

The more unambiguous the language, the clearer the message. Only precise words will be understood. Speaking about “relevant” or “significant” (in common speech, not as a statistical term) content leads to misinterpretations and misunderstandings. Speaking about facts and figures will prevent them.

Visually highlight messages in the communication objects presented – namely in charts, tables, graphs, and pictures. This facilitates comprehension and reduces the time needed to understand complex situations. In most cases, it should be possible to highlight the important parts of the content by underlining the most important facts or emphasizing interesting details. Objects and pages without highlighting indicators tend to be a statistic rather than a report.

Naming sources for the material presented increases the credibility. Projected slides can omit them but written reports and handouts must include them.

Use comments in written reports and handouts to add explanations, conclusions, and similar statements. Projected slides in presentations rarely need any comments because the comments are given by the speaker.

Number comments related to specific parts of a page (e.g. words, numbers, or visualization elements) and link them to the respective parts. Post numbered comments in text boxes on free areas of a page. General comments concerning the whole page are not numbered. Post them as a footnote at the bottom of a page.

Avoid the phrase “Thank you for your attention” at the end of a presentation. Instead, presenters should briefly sum up their message one last time – in one sentence, if possible. At the conclusion of a successful presentation, the audience will be thanking the presenters for the information. Repeating the message from the beginning of a presentation at the end helps the audience check the quality of the storyline and brings the presentation full circle. In reports, on the other hand, such repetition is not necessary as the reader can quickly browse back to the respective summary at the beginning.

Conclude reports and presentations with proposals for decisions to be taken and an explanation of their consequences. This is the real objective of a presentation: Convince the audience of both the message and the suggested steps to be taken next.

Items in a group should be of the same type, i.e. consistent. Consistent items can be different types of cars, houses, traffic signs, or – as shown in Figure ST 1.1, on the right hand side – different national flags representing the corresponding nations. The left hand side of this figure includes other types of items besides national flags, destroying the consistency.

A list of statements will be easier to understand if all statements are of the same type. The right hand side of Figure ST 1.2 shows four suggestions. By contrast, on the left-hand side of this figure the third statement is a detection, not a suggestion.

Structure all phrases – especially in listed arrangements – in a grammatically consistent manner to facilitate quicker understanding. The right hand side of Figure ST 1.3 shows a group of four consistent suggestions, an imperative verb paired with a noun. By contrast, on the left hand side of this figure the second suggestion uses verbal substantive instead of an imperative.

Visualizations such as symbols and pictures that are uniform in respect to their layouts, colors, forms, fonts, etc. – especially in listed arrangements – facilitate faster and easier comprehension.

Structure reports and presentations in such a way that the parts, chapters, sections, and paragraphs do not overlap. They should not cover the same aspects.

In Figure ST 2.1, on the left hand side, the following chapters of a project description overlap:

• expenses and costs
• schedule, steps, milestones, and calendar
• objective, results, and achievements

At first glance, the six terms on the right hand side of this figure have no overlap in their logical structure. Of course, a relationship exists between the cost, the results, and the schedule of a project, but in regards to the content of the chapters this is not an overlap.

Structure a group of business measures in lists or calculations in a way they do not overlap, i.e. business measures on one hierarchical level should be disjoint or mutually exclusive.

Looking at Figure ST 2.2, on the left hand side, the following business measures overlap

• material costs and costs of goods sold
• depreciation and fixed costs

The calculation scheme on the right hand side has been cleaned up.

The elements of the structure dimensions used in reports and presentations should not overlap, i.e. the elements of a structure dimension should be disjoint or mutually exclusive.

Looking at Figure ST 2.3 on the left hand side, the regions Norway, Sweden, Denmark, and Finland overlap with Scandinavia.

If some important arguments relating to a specific question are left out, the given answer will not be convincing.

Looking at Figure ST 3.1 on the left hand side the option “old products, new location” is missing.

The elements of structures presented in charts and tables should also be exhaustive, in other words, adding up to one hundred percent.

In many practical applications of this kind, adding a remainder element (“rest of…”) helps to conform to this rule.

Exhibiting deductive reasoning (logical flow) for a given message aids in building hierarchical structures. Logical flows always answer the question “why” following the key message. They begin with a statement (all men are mortal), continue with a comment (Socrates is a man), and resolve with a conclusion (Socrates is mortal) culminating in the message (Socrates will die).

Deductive reasoning can be best applied in controversial discussions for arguing and demonstrating need for action. However, it forces the readers or the audience to reproduce the deduction and the whole argumentation can collapse if any statements are questionable.

Exhibiting inductive reasoning (logical group) for a given message aids in understanding hierarchical structures. Logical groups are homogenous, non-overlapping, and collectively exhaustive arguments culminating in a message. This results in a powerful argumentation that satisfies the addressees need for an easily comprehensible logical structure.

For easier understanding, underscore the logical structure of reports and presentations with visual aids (e.g. outlines, dashboards, summaries). Figure ST 5.1 illustrates this rule showing binder tabs on the right hand side.

Design tables in such a manner that their hierarchical structure can be recognized in both the columns as well as the rows.

The right hand side of Figure ST 5.2 shows three hierarchical levels of rows in a table. The base level shows cities, the first summary shows regions, and the second summary shows the country.

Notes are also easier to understand when their structure is shown clearly (see Figure ST 5.3).

A chart is a graphical object, in which visualization elements such as columns, bars, and lines represent data.

This section discusses the types, layout, and examples of single charts. Overlay charts and multiple charts are discussed in the CONDENSE rules CO 4 “Add elements” and CO 5 “Add objects”.

The most important groups of business charts are those showing development over time (charts with horizontal category axes), those showing structural relationships (charts with vertical category axes), and those showing x‑y charts, scatter plots, and bubble charts (charts with two value axes), see Figure EX 1.1.

Other chart types are of lesser interest in business communication and will be treated in a later version of the standards.

Looking at charts with horizontal and vertical category axes, the chart selection matrix displayed in the figure on the left aids in selecting the right chart type for time series and structure analyses.

In the following sections, the correct usage of charts with horizontal category axes, charts with vertical category axes, and charts with two value axes is discussed in greater detail.

A table is a communication object in which data is arranged in two dimensions, i.e. (vertical) columns and (horizontal) rows. The row header (row name) describes the content of a row, the column header (column name) the content of a column. The data are positioned at the intersections of rows and columns called table cells.

“One-dimensional tables” (tables with one or more columns but without row headers) are called lists and are not covered here.

Table types are defined by a set of columns and a set of rows in order to fulfill specific analytic and/or reporting purposes.

Pie and ring charts are circular charts dividing some total into sectors of relative proportion, but there are better ways to illustrate the numerical proportions of segments, e.g. bar charts or charts with stacked columns, see Figure EX 2.1.

Pie charts allow for one-dimensional analyses only, and therefore seldom convey revealing insights. However, some useful applications for pie charts exist, for example when market sizes and/or market shares for one period need to be allocated to certain regions on a map (see the CHECK rule CH 3.3 “Avoid misleading colored areas in maps”). As opposed to column or bar charts, pie charts can be positioned on a specific point on a map.

Often found as part of a so-called dashboard, speedometers are probably one of the most useless visualizations out there. They take up way too much space and have often confusing color coding and scaling. In general, bar charts showing the respective structures or columns charts showing the respective development over time are better choices, see Figure EX 2.2.

So-called radar charts (also called net charts or spider charts) are frequently used for evaluating purposes. Having no advantage over bar charts and having, actually, many weaknesses, use them only for two-dimensional analyses (e.g. comparing young-old with rich-poor). Willard C. Brinton wrote almost 100 years ago[1]: “This type of chart should be banished to the scrap heap. Charts on rectangular ruling are easier to draw and easier to understand.”

Of course, if the circular arrangement has meaning (such as the compass direction), this kind of chart can be very valuable, but these types of analysis are not typical in business reporting.

Funnel charts are misleading when the size of the area displayed does not correspond to the respective numerical values – an issue applying also to other artificial chart forms (e.g. spheres) in which the length, area, or volume do not correspond to the numerical values.

[1] Brinton, Willard C.: Graphic Methods for Presenting Facts, 1914(!), page 80

A chart with more than three or four intersecting lines (“spaghetti chart”) can be more confusing than several smaller charts with one line each placed next to one another (small multiples), particularly when evaluating the shape or the trend of the lines, see Figure EX 2.4.

However, when needing to compare exactly the height of data points of several lines, spaghetti charts cannot be avoided.

“Traffic lights” with green, red, and yellow areas are a popular form of visualization but contain little information per area used. However, they can be used for analyses showing “yes or no” decisions or situations similar to real traffic lights. In all other cases replace them with more suitable means of (analog) representation such as bar charts, see Figure EX 2.5.

Due to the time constraints usually involved with presentations, conceptual graphs prove less suitable than charts, photos, maps, etc. For a one-hour presentation, do not use more than three or four conceptual representations. Do this only if they are absolutely essential for comprehension. The audience will understand charts and pictures (photos, drawings, etc.) better and faster, see Figure EX 3.1.

Avoid all forms of text slides in presentations. Texts should either be recited or written in a handout. A few exceptions to this rule are specific texts being discussed such as definitions, quotes, etc. In general, all forms of lists (bullet points) should appear only in the written handout, not projected on the screen. True, if someone sees and hears something simultaneously, he remembers it better than when he just hears it, but bear in mind texts are not considered something merely to be seen – they must be read and understood, see Figure EX 3.2.

Scenarios such as “plan” and “previous year” are the most common references for comparison purposes. Add them whenever available. Use a standardized scenario notation for faster comprehension, see Figure EX 4.1.

Having added scenarios for comparison purposes, the visualization of variances makes it easier to evaluate the situation. Use a standardized notation of variances for faster comprehension, see Figure EX 4.2.

The presentation of the assumptions or basic data upon which a business analysis is based, results not only in better understanding, but also makes it more convincing. A good choice is the display of calculated measures in a tree structure, see Figure EX 5.1 (see also the CONDENSE rule CO 5.2 “Show related charts on one page”).

With the help of clusters in two-dimensional and three-dimensional forms, large amounts of data very often can provide interesting and new insights, see Figure EX 5.2.

When comparing several data series, correlations are often sought in order to better understand the interrelations. Suitable rankings and comparisons can facilitate the understanding of patterns, see Figure EX 5.3.

Layout concepts often contain elements that lack meaning but merely conform to corporate design or personal taste. Avoid all these elements, see Figure SI 1.1.

Numbers and labels are easiest to read when depicted in black on a white background. Any type of background color or pattern makes something harder to read, see Figure SI 1.2.

Animated PowerPoint slides are not useful if the animation has no meaning and does not support the message, see Figure SI 1.3. They merely distract and confuse. Only the “appear” function is recommended to be used for the gradual development of a slide.

In general, borders, shades, and pseudo-3D convey no meaning and make comprehension more difficult. Shades and pseudo-3D might even give a false visual impression. Avoid them because they do not add value, see Figure SI 2.1.

If colors serve merely decorative purpose in one instance, using them for meaning in another instance (e.g. for highlighting) becomes difficult. Therefore use colors only if they convey meaning, see Figure SI 2.2.

A normal typeface and clear fonts increase legibility. Save bold and cursive fonts for making distinctions, see Figure SI 2.3.

Using integrated data labels can make value axes, tick marks, and gridlines superfluous, see Figure SI 3.1. Gridlines, however, can be useful in charts with missing reference points as might be the case in charts with many data series and data points, or in small charts (e.g. small multiples).

Omit all avoidable elements to make tables more straightforward. Avoid vertical lines by right-aligning numerical values and the corresponding column headers, see Figure SI 3.2.

Extra words such as “sum” and “total” are redundant because they add no value to the meaning of the term they accompany. No difference exists between “Europe” and “Sum of Europe”. Extra words make it harder to read text elements, see Figure SI 4.1.

Terms such as “chart analysis”, “development”, or “comment” are redundant because they name something already shown, see Figure SI 4.2. Other obvious terms in charts and tables are “table”, “statistics”, “report”, “visualization”, “structure”, or “trend”.

Repeated words in legends, axis labels, row headers, etc. such as “division” in “division A”, “division B”, etc. or “2017” in “Q1 2017”, “Q2 2017”, etc. should be avoided, see Figure SI 4.3. Omitting repeated words usually increases the degree of legibility.

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Labels of small values are often hard to position and rarely contribute to the comprehension of the message. Therefore they can be avoided in most cases, see Figure SI 5.1. However, add them when special reference is made to them. If it is necessary to label these small values or small visualization elements, assisting lines might be necessary.

Numbers with more than three digits in charts and four digits in tables are hard to read; moreover, such precision is seldom necessary to understand the message, see Figure SI 5.2.

Omit labels for data points that do not represent extreme values or values of special importance, see Figure SI 5.3.

In general, avoid oversize fonts. They needlessly waste space, see Figure CO 1.1.

Small elements increase clarity. Large-scale symbols and highlights are not more suitable than smaller symbols and highlights, see Figure CO 1.2.

The size of charts and tables in reports and presentations should not be as large as possible, rather as small as possible – yet only so small so that the objects and all its details and labels can be read easily. This provides room for more information and therefore better understanding of the context, see Figure CO 1.3.

The page layout is often dominated by corporate design standards not made for high information density but for attractive design, sacrificing valuable space to layout elements such as extra wide page margins, see Figure CO 2.1.

Reduce empty space to increase information density. This applies not only to the page layout (see Figure CO 2.1) but also to the layout of report objects such as charts and tables (see Figure CO 2.2).

Displaying more data points does not jeopardize the comprehension of numerical data. For example, a monthly statistic of staff numbers over twelve months in a year would be understood just as quickly as for the same data series with twelve months for each of the last three years – in other words, a total of 36 data points instead of twelve. Usually, interesting relationships are only detected with an increased number of elements in a data series (see Figure CO 3.1).

A very useful way to increase information density is to show more than two dimensions of a business situation. A chart with only one dimension (such as in a pie chart), visualizes only mundane things easily stated in a simple sentence. Already charts with two dimensions can yield very interesting relationships – yet those charts with three and more dimensions yield structures leading to completely new insights (see Figure CO 3.2).

In an overlay chart, two or more basic charts overlap. These overlapping charts always use the same category axis.

Overlay charts can facilitate comprehension such as in the combination of the development of sales (a series of columns) and the return on sales in percent (a line). However, this approach can only be used for a few chart combinations, see Figure CO 4.1.

Overlay charts frequently use different value axes. A column chart representing a measure (e.g. sales) combined with a line chart representing another measure (e.g. employees) is a typical example (see figure on the left).

Sometimes, the same value axis is used as well. A column chart representing a measure (e.g. sales) combined with a line chart representing the same measure (e.g. industry average) is a typical example for such an overlay chart (see figure on the left).

Column or bar charts with integrated variances (variances displayed within the columns or bars) are other typical example for overlay charts using the same value axis (see the last two figures on the left).

Compared to two-tier charts, this presentation of two data series uses much less space. The disadvantages, though, are twofold: First, it is difficult to label the data of both the primary and secondary chart. Second, the development over time (horizontal axis) respectively the structure (vertical axis) of the primary chart is difficult to see.

Suggestion: If there is enough space, use multi-tier charts instead.

Use multi-tier charts to increase information density by adding additional tiers to the same category axis for analyses on the same basic data. Multi-tier charts are most frequently used for displaying variances along with the basic values, see Figure CO 4.2.

In a two-tier chart, a secondary chart is shifted in parallel to the category axis of the primary chart. For horizontal charts the secondary chart appears above the primary chart, for vertical charts the secondary chart appears to the right of the primary chart.

In both cases, the category axes of the primary charts are reduplicated in the secondary charts, usually having a different semantic scenario design.

Both the primary and the secondary charts have their own value axes. Value axes showing the same currency or the same physical unit should be scaled identically.

In a three-tier chart a third chart appears above a horizontal or to the right of a vertical two-tier chart. In special cases, more than three tiers can be combined.

Improve the interpretation of a primary chart showing grouped bars for actual and plan data by adding variances. In the second and third figure on the left a secondary chart with absolute variances and a tertiary pin chart with relative variances are combined.

An extended chart, arranges additional charts next to the primary chart by virtually extending the category axis. This way of increasing information density often is used when displaying context information such as market averages or competitor figures, see Figure CO 4.3.

For horizontal charts, additional charts appear to the left or right of the primary chart, for vertical charts, above or below. In both cases, position the category axes of the additional charts on a virtual extension of the category axes of the primary chart.

In an extended chart, use the same value axis for both the primary and the additional charts.

Improve the interpretation of a primary chart by adding extended charts showing the same values from a different perspective. In the figure on the left, a secondary grouped column chart at the right hand side shows the monthly average.

Increase the information density of tables by using chart elements, see Figure CO 4.4. Bars, warning dots, sparklines, and traffic lights are the predominant chart element types in tables.

Both the density of information and the level of comprehension increase when explanations are embedded into charts and tables (this applies to written reports and handouts only). When the explanation refers directly to the visual presentation in question, it helps to establish a connection and speeds up comprehension, see Figure CO 4.5.

Substantially improve the comprehension of complex relationships by displaying charts of the same type and the same scale on the same page. These charts are called small multiples, see Figure CO 5.1.

Typical applications are charts with different countries, products, or projects placed next to each other. Of course, there is an upper limit to the number of charts on one page, depending mainly on the page- and font-size used.

Showing small multiples is a good way to compare a set of up to around 25 charts. Instead of exceeding this number on one page, a new chart called “Others” containing the accumulation of all other elements could be a solution.

As mentioned in the chapter “CHECK – Ensure visual integrity”, all small multiples must use the identical scale.

Working with small multiples can be difficult if certain charts show significantly bigger values than others. Using a different scale for a chart with bigger values is not a feasible option, increase the size of this chart instead, see figure on the left.

Different from small multiples, related charts cover different topics (different measures) on one page. They mostly use different scales, too. This arrangement of charts on one page is sometimes called multi-charts. But the term multi-charts fails to underline the fact that these charts must have a useful relationship. It does not make sense to arrange several, completely unrelated charts on one page.

This approach offers high data density and a higher level of comparability – but it can be a demanding visual and technical challenge as a uniform notation concept, clear terms, and an understandable scaling prove even more important (see Figure CO 5.2).

Consistent scaling of multi-charts can be difficult. Sometimes different scales for the same unit or measure are inevitable. In this case, clearly indicate the use of a different scale by an appropriate mean, e.g. scaling indicators.

Ratio trees are multi-charts showing root causes. Use ratio trees to prove or explain a specific issue. Pointing out the assumptions and root causes of variances or temporal evolvements improves understanding and is more convincing, too. In general, the ratio is broken down into its components (mostly from left to right). Thus individual charts, preferably identical size, are arranged in a tree shape structure.

Consistent scaling of ratio trees can be difficult. Sometimes different scales for the same unit or measure are inevitable. In this case, clearly indicate the use of a different scale by an appropriate mean, e.g. scaling indicators.

A typical example of a page showing a ratio tree is the “Return on asset” tree, see figure on the left.

Combining charts and tables on a page is not to be confused with the integration of chart elements in tables.

Chart-table combinations cover situations where a separate chart is added to a page with a table or vice versa. In general, such a combination is very useful if both objects display supplementary data. Tables simply listing the numbers of a chart are superfluous in most cases (see also the UNIFY rule UN 2.3 “Unify the position of legends and labels”).

Embedding illuminating charts and tables in the text of a written report helps the reader understanding the message.

Always position charts and tables in close proximity to the phrase carrying the message, which the chart or table supports.

Text pages should contain a title element like other pages. Also use a title – and, if possible, a message – for every chart and table embedded in a text page.

Charts with value axes not starting at zero (“cut” axes) are not “wrong” in and of themselves, but the message to be visually conveyed then does not correspond to the numerical values upon which the chart is based. Therefore, value axes should generally start at zero, see Figure CH 1.1.

One exception to this rule exists: charts with indexed data (e.g. if the value for the index period is set to 100%) with only small variances from 100%. Here “zooming in” on the variances could be of greater value than indicating the absolute values (starting at zero). In this case, position the category labels at the 100% line in order to avoid misinterpretations.

Avoid logarithmic scales because they do not allow the visual comparison of values, see Figure CH 1.2. In business, very few applications for logarithmic axes exist (e.g. comparing growth rates of different stocks in percent).

If the categories represent ordered classes of elements (e.g. age classes) as used for the visualization of distributions in histograms, use class sizes of identical width (e.g. ten years). Otherwise, true visual comparability is impossible, see Figure CH 1.3.

Similar to “cut” axes, clipped visualization elements such as broken columns make visual comparisons impossible, see Figure CH 2.1.

Creative visualization elements can be used to compare extreme values, e.g., displaying data in two-dimensional or even three-dimensional visualization elements allows the comparison of values differing by orders of magnitude, see Figure CH 2.2.

This rule must be clearly separated from the rules of section CH 3 “Avoid misleading representations” where area and volume visualizations are used improperly.

Using two-dimensional representations (areas of circles, icons, or emblems) for the visualization of data is only valid, if the size of these areas corresponds to the underlying values. The visual perception will be misleading if the diameters of circles or the heights of icons represent the values, see Figure CH 3.1.

Similar to areas, the visual perception will be misleading, if the (one-dimensional) diameters or the (two-dimensional) areas of three-dimensional visualization elements (spheres, cubes, etc.) represent the values, see Figure CH 3.2. Even if their volumes represent the values, it is hard to perceive them properly. Prefer linear comparisons instead.

Different colored areas can be helpful to visualize the precipitation per square meter or the population density. However, do not use colored areas for the visualization of non-area-related figures such as market shares or return on sales. Position columns or bars of identical scale in maps instead. By the way, pie charts also work well here (an exception to the EXPRESS rule EX 2.1 “Replace pie…” because they can be placed precisely at one point, like a city (see Figure CH 3.3).

If presenting more than one chart of the same unit on one page, use the identical scale for these charts, see Figure CH 4.1. In extreme situations identical scales might not be desirable. In these exceptional cases the use of scaling indicators (see CH 4.3 and UN 5.2) can be helpful.

Using identical scales in multiple charts can be demanding if the values in the charts differ by orders of magnitude. A good solution is adapting the chart size to the given data, see Figure CH 4.2.

There are several ways to overcome challenging scaling problems. Scaling indicators, such as scaling lines and scaling areas indicating the same numerical height (typically a power of 10) in all charts are helpful to assist in comparing multiple charts (of the same unit) with different scales, see Figure CH 4.3.

IBCS suggest a semantic design for scaling lines and scaling areas, see SUCCESS rule UN 5.2 “Unify scaling indicators”.

Certain values that are very big in comparison to other values are called outliers. If an outlier is not important for business, e.g. a big relative variance of a small value, then it is not appropriate to scale the whole chart to this outlier. Therefore, use outlier indicators for unimportant outliers, see Figure CH 4.4.

IBCS suggest a semantic design for outlier indicators, see SUCCESS rule UN 5.3 “Unify outlier indicators”.

Another way to assist in scaling problems is to use “magnifying glasses” for zooming in on a part of a chart with a bigger scale. Use an appropriate visualization element to mark the part of a chart to be zoomed in and to link it to a second chart displaying the zoomed part on a bigger scale.

Making inflation effects transparent helps avoid misinterpretations of time series visualizations, see Figure CH 5.1.

Similar to inflation effects, the adjustment of currency effects can help to avoid misinterpretations, see Figure CH 5.2.

The standardization of terms and abbreviations in reports and presentations is achieved by using an unambiguous language (see SAY rule SA 4.1 “Speak with precise words“) and by unifying the usage of terms (glossary).

Unify, compile and explain all terms and abbreviations used in reports and presentations in a clearly arranged glossary including abbreviations and definitions, see Figure UN 1.1.

A glossary with terms and abbreviations in more than one language might be necessary in order to avoid different translations.

Often the names of business measures are too long for charts and tables. Use abbreviations instead. It might be a good solution to define short abbreviations (e.g. to A/R for Accounts Receivable be used in table column headers) and long abbreviations (e.g. Acc. Receiv. to be used in table row headers).

Unified terms and abbreviations for the notation of scenarios and time periods are covered in the respective sections.

The uniform use of formats for numbers, units and dates will enhance legibility, see Figure UN 1.2.

The message the author intends to convey to the reader or audience is best recognized, if the position and the layout of the message is always the same, see Figure UN 2.1.

The notation of messages should be two text lines at the top of a report or presentation page, either a) above the title (see figure on the left) or b) right of the title. Position b) is not structured as clearly as position a) but it helps saving valuable vertical space especially on pages in landscape format.

The wording, structuring and meaning of messages is not discussed here rather in the IBCS part on “SAY”.

Titles identify the content of pages and their objects in its entirety, omitting nothing necessary to understand the content, see Figure UN 2.2. In contrast to messages, titles do not contain any evaluating aspects, such as interpretations, conclusions, or propositions.

If there is more than one object on a page, use page titles for entire pages, slides, or screens and sub titles for different objects on a page.

A standardized notation of legends and labels will improve legibility and speed up comprehension of charts, see Figure UN 2.3.

Mainly in static reports, comments detail other elements (e.g. definitions of data series) and objects such as charts and tables. Sometimes comments also refer to complete pages.

The level of comprehension increases when comments refer directly to the visual representation. Therefore, comments on an object (e.g. chart) are integrated into that object when possible. Comment elements should be linked to the content of tables, charts, etc. through comment references (see also SAY rule SA 4.4 “Name sources and link comments”), see figure on the left.

Footnotes, a special type of comments, provide general explanations, explanations of abbreviations, and information that increases the credibility of the content such as the sources or the dates of retrieval and printing. They can be omitted from slides projected on the wall, but must be included in written material.

Position footnotes at the bottom of a page, see figure on the left.

Business measures such as sales, profit, margin, etc. describe, report, and calculate business situations. A standardized notation will help to comprehend the specific characteristics of measures, e.g. whether they are basic measures or calculated ratios of measures, whether they represent value or volume figures, flow or stock figures, or whether they have a positive or negative impact, see Figure UN 3.1.

The visualization of business measures is presented here. Their definition, generally given in accounting manuals or similar documentation, is not discussed here. For the unified wording of business measures and their abbreviations see the UNIFY rule UN 1.1 “Unify terms and abbreviations”.

Scenarios (also called data categories, data types, or versions) represent different layers of a business model. Typical scenarios are “Actual”, “Previous year”, “Plan”, “Budget”, and “Forecast”. In special cases benchmarks such as competitor data or market averages are also called scenarios.

Often comparisons and variances between different scenarios are presented to provide business insights.

There are two basic types of scenarios:

• Actual scenarios refer to measured data about things that already happened in present or past time periods. These data might not be perfectly correct because of difficulties with systems, unclear definitions, and false data acquisition – but they are as correct as possible. The terms we use most often for scenarios of this type are ‘Actual’ and ‘Previous year’.
• Planned scenarios refer to fictitious (not materialized) data. The terms we use most often for scenarios of this type are ‘Plan’ and ‘Budget’.

In-between those two basic scenario types there is a third one:

• Forecasted scenarios refer to expected data which are strictly speaking fictitious but already taking into account measured data. A typical example forexpected data is the sales forecast based on the measured order entry. Forecasted scenarios represent a higher level of certainty than scenarios with planned data but are not completely materialized yet. The term we use most often for scenarios of this type is ‘Forecast’.

When analyzing charts and tables, it is very important to quickly recognize whether you look at measured, expected, or fictitious data. Readers of IBCS compliant reports can visually recognize these scenario types by looking at the area fill of a visualization element without having to read the labels. Typical chart visualization elements such as bars, columns, line chart markers, scenario triangles, etc. carry the semantic scenario notation.

In charts presenting variances, their axes carry the semantic scenario notation in order to show the respective reference scenario (see UN 4.1).

In charts with stacked columns, stacked areas, and charts with multiple lines or areas, the application of this semantic scenario notation can become a challenge. In these cases, applying the semantic notation to the axis instead of the columns etc. is a valid option.

Using standard notations for time periods (for flow measures) and points of time (for stock measures) is important as they are frequently applied to all forms of business communication. This requires standard notations for the visual direction of time, time period and points of time abbreviations and – in charts with horizontal time axes – category widths, see Figure UN 3.3.

Structure dimensions are all dimensions that are not measures, scenarios, or time periods. In many cases, the following structure dimensions are used: regions, organization units, products, customers, channels, and accounts.

Display structures always in vertical direction. Use custom symbols if it is helpful to differentiate structure dimensions, see Figure UN 3.4.

Analyze scenarios by comparing them and by calculating their absolute and relative variances. Notation standards for scenario analyses cover the labelling of variances and the semantic design of chart elements such as columns, bars, and axes, see Figure UN 4.1.

Notation for time series analyses covers year-to-date analyses, moving analyses, and temporal indexing, see Figure UN 4.2.

Notation for structure analyses covers averaging, ranking, selecting, indexing, and normalizing.

Adjustment analyses can offer insight into root causes as they adjust values by neutralizing special effects. In general, adjustment analyses are used in conjunction with scenario analyses. Here the values of one scenario are recalculated with correction factors from another scenario: e.g., adjust AC sales for currency effects by re-measuring them with the PY exchange rates.

Typical adjustment analyses deal with currency, inflation, and seasonal effects.

A future version of IBCS may create a visualization concept for adjustment analyses.

The message to be conveyed should be highlighted on the respective page by appropriate visual means. Highlighting elements enhance the meaning and importance of other elements. Use highlighting elements for assisting purposes, for visualizing differences and trends, for underlining values, for indicating a reference, or for linking comments, see Figure UN 5.1.

Proper scaling is very important for the creation of meaningful charts. Several semantic scaling indicators exist to deal with in challenging scaling problems. Use scaling lines and scaling areas (scaling bars) if necessary, see Figure UN 5.2.

A future version of IBCS may suggest additional visualization concepts for scaling.

Sometimes values (mostly relative variances) can be very big in comparison to other values. If such an outlier is not important for business, e.g. a big relative variance of a small value, do not scale the whole chart to this outlier rather visualize unimportant outliers with outlier indicators.

Omit the pin head and add outlier triangles pointing in the direction of growth, see Figure UN 5.3.