dataviz/docs/09-unify.md

# UNIFY – Apply semantic notation

UNIFY covers all aspects of applying semantic notation in reports and presentations.

_Applying semantic notation_ means that reports and presentations follow this
governing principle: _Similar content should be visualized in a similar manner;_ what looks the same should also mean the same. On the flip side: If the content is
not the same, it should not look the same.

In many specialized disciplines such as engineering, music, and architecture,
_semantic notation standards_ are a matter of course. The world of business
communication lacks such notation standards, one of the main reasons management reports
are sometimes hard to understand. For example, no common agreement on the meaning of
various style elements such as titles, line markers, axes, highlighting indicators, etc.
used in business charts exists yet.

This chapter covers semantic rules for all important and frequently recurring aspects of
meaning in the context of business communication, such as terminology (e.g. words,
abbreviations, number formats), descriptions (e.g. messages, titles, legends),
dimensions (e.g. measures, scenarios, time periods), analyses (e.g. comparisons and
variances), and indicators for highlighting, scaling and other purposes.

1. [Unify terminology](#un-1-unify-terminology)
2. [Unify descriptions](#un-2-unify-descriptions)
3. [Unify dimensions](#un-3-unify-dimensions)
4. [Unify analyses](#un-4-unify-analyses)
5. [Unify indicators](#un-5-unify-indicators)

## UN 1 Unify terminology

_Terms_ are the non-visual part of business communication. Unified
_terms and abbreviations_ as well as unified formats for _numbers,
units and dates_ accelerate understanding.

## UN 1.1 Unify terms and abbreviations

![Figure UN 1.1: Unify terms and abbreviations](img/un-1.1.png)

The standardization of terms and abbreviations in reports and presentations is achieved by using an unambiguous language (see SA 4.2 “[Speak with precise words](01-say.md#sa-42-use-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.

## UN 1.2 Unify numbers, units, and dates

![Figure UN 1.2: Unify numbers, units, and dates](img/un-1.2.png)

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

**Numbers**

Different languages and countries use different _number
formats_, e.g. 1.234.567,00 (D); 1,234,567.00 (USA);
1’234’567,00 or 1’234’567.00 (CH).

It is important to unify the number formats in all reports and
presentations. The _International System of Units (SI)_
as described in “ISO 80000-1” recommends the following notation:

-   Thousand delimiter: 1 234 (blank space)
-   Decimal sign: 1,23 or 1.23 (SI allows both versions)

Do not use long numbers in order to avoid distraction and to concentrate on the essentials, see also SI 5.2 “[Avoid long numbers](05-simplify.md#si-52-avoid-long-numbers)”. Use _currency prefixes_ and _metric prefixes_ to limit the number of digits to a maximum of three in charts and four in tables.

The most common formats for _negative values_ are “-123” and “(123)”. Use the same format for all negative values.

_Positive values_ do not have a plus sign, unless they
represent variances.

**Currencies**

Use the standard _currency abbreviations_ based on [ISO 4217](http://en.wikipedia.org/wiki/ISO_4217). ISO 4217 provides a set of currency abbreviations using three-letter acronyms such as EUR, CHF, USD, and GBP. The use of special currency symbols such as €, $, and ₤ is not recommended if a report includes many different currencies.

Use “metric prefixes” in combination with the currency units for
monetary values expressed in thousands or millions. Use lower
case characters to differentiate the prefixes from the currency
abbreviations and use single digit metric prefixes to save
space, such as “k” for thousand, “m” for million and “b” for
billion. The following shows the correct use of currency metric
prefixes with EUR:

1 bEUR = 1 000 mEUR = 1 000 000 kEUR = 1 000 000 000 EUR

(The metric prefixes for physical units are “M” for “millions”
and “G” for “billions”. Nevertheless, this guide suggests using “m” and
“b” for currency metric prefixes, as “mEUR” and “bEUR” which is
easier to understand than MEUR and GEUR.)

**Physical units**

For _physical units_ use the [International System of Units (SI)](http://en.wikipedia.org/wiki/International_System_of_Units) such as kg, t, m, km, etc.

In the case of non-monetary values expressed in thousands or millions, use [metric prefixes](http://en.wikipedia.org/wiki/Metric_prefixes) suggested by the _International System of Units_ such as “G” for billion, “M” for million, and “k” for thousand.

**Dates**

_Dates_ are best displayed using [ISO 8601](http://en.wikipedia.org/wiki/Iso_date), an international standard covering the exchange of date and time-related data: YYYY-MM-DD, e.g. “2015-12-31”.

Other significant notation principles regarding time-related aspects will be dealt in UN 3.3 “[Unify time periods](09-unify.md#un-33-unify-time-periods-and-points-of-time)”.

## UN 2 Unify descriptions

_Descriptions_ are textual elements that describe the visual elements in
reports and presentations facilitating comprehension. The following suggests
unified layouts for every kind of _descriptions_.

## UN 2.1 Unify messages

![Figure UN 2.1: Unify messages](img/un-2.1.png)

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.

![Figure UN 2.1-1: Message text line](img/un-2.1-1.png)

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.

## UN 2.2 Unify titles and subtitles

![Figure UN 2.2: Unify titles and subtitles](img/un-2.2.png)

_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.

**Page titles**

*Page titles* identify the content of a page. In
general, three lines suffice to completely describe the content
of a page:

**Title line 1: Reporting unit**

Element(s) of a structure
dimension representing the object of the report,
typically a legal entity, an organization unit, a line
of business, a project, etc. or combinations thereof,
e.g.

-   ABC Corporation
-   ABC Corporation and its main competitors
-   ABC Corporation, European division
-   ABC Corporation, European division, Project B

Add filter information if the elements are not
exhaustive, e.g.

-   International Chocolate Corporation, top ten clients
-   International Chocolate Corporation, divisions with
    negative EBIT in 2016

If title line 1 becomes too long its content can be split
into two lines, e.g.

```
International Chocolate Corporation, European division
Top ten clients
```

**Title line 2: Business measure(s)**

Element(s) of the measure dimension such as sales, profit, and shipment. Business measures are measured either in currency units (e.g. EUR, USD) or in physical units (e.g. #, kg, t). Use metric prefixes (e.g. k, m, b) where appropriate. Measures are written in bold font, their units are written in regular font. Examples are:

-   **Net sales** in mEUR
-   **Net sales** in mEUR, **margin** in %
-   **Headcount** in #

Use a suiting name for a _set of measures_, if
more than two measures have to be presented on one page.
Examples are:

-   **Income statement** in kEUR
-   **ROI tree** in mEUR
-   **Balanced scorecard**
-   **Product market portfolio**

Use footnotes
if parts of the measures are redundant or if parts of
the measures are of minor importance for understanding.
Examples are:

-   **Net sales** in mEUR (without intercompany sales) – simpler: **Net sales\*** in mEUR
-   **Operating margin** in mEUR (non-IFRS) – simpler: **Operating margin\*** in mEUR

_Additional information_ about the way presenting
the content can help to understand better the respective
page. They might concern structure
dimensions, e.g.

-   **Profit** in mUSD, by products
-   **Net sales** in kEUR, by products and by countries

or they might be analytical annotations, e.g.

-   **Net sales** in mEUR and **profit**in mEUR, sorted by net sales (↓)
-   **Full time equivalents** in #, indexed (2012 = 100%)
-   **Gross margin** in kUSD, top ten

or even combinations of structure dimensions and
analytical annotations, e.g.

-   **Net sales** in mEUR, by countries, sorted by net sales (↓)
-   **Full time equivalents** in #, by offices, indexed (2012 = 100%)

If title line 2 becomes too long its content can be split
into two lines, e.g.:

```
**Full time equivalents** in #, by offices
Indexed (2012 = 100%)
```

```
**Net sales** in mEUR, by countries
Sorted by net sales (↓)
```

**Title line 3: Time period(s) scenario(s), and variance(s)**

![Figure UN 2.2-1: Title lines](img/un-2.2-1.png)

Element(s) of the time dimension (e.g. years, months), of the _scenario_ dimension (e.g. actual, plan), and variances (e.g. ΔPL, ΔPL%) if necessary.

In general, elements of the *time* dimension (e.g. 2016, 2016-Q1) are necessary for understanding. Elements of the *scenario* dimension (e.g. AC, PL, FC) and *variances* are added if they help to understand the page content faster. If only actual values are presented, the attribute AC can be omitted.

Display the time element first if both time and scenario
elements are shown in title line 3.

Use “&” (ampersand sign) when title elements together
make up a time series, e.g. “AC&PL” (without blanks)
if the first 8 months of a year present AC values and
the last 4 months present PL values.

Use “and” when different elements are presented for all
time periods, e.g. “AC and PY” if all 12 months of a
year present both AC and PY values.

Examples of alternative arrangements in *title line 3* are:

-   2017-Q1
-   2016-03..2017-02
-   2017 AC and PL
-   2017 AC&FC and PY
-   2016 AC, 2017..2021 PL, or: 2014..21 AC&PL, or: 2014..21
-   2016 AC and PL and ΔPL, or: 2016 AC and PL, or: 2016

Keep it clear and easy to understand – too many elements tend to be confusing. In many cases the information depicted in column headers of tables and legends of data series in charts are sufficient and give better and quicker insight than long texts in _title line 3_. In any case, rules for abbreviating time periods and dates as well as the rules for abbreviating scenarios and variances must be followed.

In general, position *page titles* at
the very upper left corner of a page, directly
underneath the message (if a message exists). Alternatively, position them at the same
height as the message if there is not enough space –
preferably on the left hand side of the message.

Here are some typical examples of _page titles_:

```
Chocolate Corp.
**Gross profit** in mUSD
2016
```

```
Construction Inc., Division EMEA
**Net sales** in mEUR, **profit margin** in %
\_2016-Q3 (AC, PL)
```

```
Beverage Corporation
**Product market portfolio**
2015 and 2016
```

```
Milk & Cheese Corp.
**Shipments** in t, by product, by country
2016-W01..10
```

**Subtitles**

![Figure UN 2.2-2: Subtitles](img/un-2.2-2.png)

_Subtitles_ identify either page segments or objects (e.g.
charts and tables) within a page with multiple objects. They
complement the identification information already given in the
page title. Subtitles display identifiers that differ from
object to object on a page. Put identifiers that are identical
for all objects of a page in the page title and not in the
subtitles.

In most cases, one line is sufficient for subtitles because
different elements of only one dimension have to be identified.
Typical examples are:

```
**Revenue**in mEUR
Apples
2014..2016
```

```
**Sales**in SKU
Pears
2016-Q1..Q4
```

```
**Avg. price** in EUR/SKU
Oranges
2016-10..12
```

_Subtitles_ are positioned above the respective objects
(charts, tables, etc.) which they identify – either centered or
left-aligned.

**Titles on screen pages**

Unlike titles on printed pages, the layout of titles on screen
pages can depend on the device (responsive design). For small
devices in landscape format e.g. writing the three title lines
in one line separated by a “|” (pipe sign) is a valid solution.

Titles on screen pages can also mutually interfere with
interactive navigation objects such as drop-down boxes for
selection and check boxes for filtering. These navigation
objects can contain redundant title information, but they cannot
replace the title or parts of it. Hide these navigation objects
when they are not in use or when the screen page is being
printed.

## UN 2.3 Unify the position of legends and labels

![Figure UN 2.3: Unify the position of legends and labels](img/un-2.3.png)

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

**Legends**

_Legends_ (also called “_data series labels_”) identify data series.

If possible, integrate legends into charts, not positioned
externally. Write legends horizontally for better legibility.

Legends for single column charts and single bar charts are best integrated into the title.

![Figure UN 2.3-1: Legends of a stacked column chart](img/un-2.3-1.png)

In stacked column charts, position legends either to the left of the leftmost column or to the right of the rightmost column.

![Figure UN 2.3-2: Legends of a stacked bar chart](img/un-2.3-2.png)

Center legends of stacked bar charts above the top bar.

![Figure UN 2.3-3: Legend with assisting line](img/un-2.3-3.png)

_Assisting lines_ can help to assign the legends to the correct _visualization elements_. In grouped column charts and grouped bar charts, assisting lines can also help to assign the legends to the correct _visualization elements_.

![Figure UN 2.3-4: Legends of a line chart](img/un-2.3-4.png)

In line charts, position legends either to the right of the line end or close to the course of the line.

![Figure UN 2.3-5: Legends in a chart with two value axes](img/un-2.3-5.png)

For charts with two value axes, externally positioned legends next to symbols can be a good choice. When helpful, integrate these legends into the chart by positioning them next to typical points or bubbles.

**Labels**

_Labels_ (more precise: _data labels_) assign the
data values to the respective visualization elements.

Omit labels of small visualization elements, use labels with not more than three digits, and avoid unnecessary and distracting labels (see also the SIMPLIFY rules SI 5 “[Avoid distracting details](05-simplify.md#si-5-avoid-distracting-details)”).

Write labels horizontally for better legibility.

Position labels next to their visualization elements. If this is
not possible, use lines connecting the labels to the correct
visualization elements.

![Figure UN 2.3-6: Labels in a column chart](img/un-2.3-6.png)

In charts with horizontal category axes, position labels above or below the visualization elements, see the first and second figure. In stacked columns, either center labels in the data points (if the data points are large enough) or position them outside of the data points.

![Figure UN 2.3-7: Labels in a line chart](img/un-2.3-7.png)

![Figure UN 2.3-8: Labels in a chart with vertical category axis](img/un-2.3-8.png)

In charts with vertical category axes, position labels right or left of the visualization elements. In stacked bars, either center labels in the data points (if the data points are large enough) or position them outside of the data points.

![Figure UN 2.3-9: Labels in a chart with two value axes](img/un-2.3-9.png)

In charts with two value axes, position labels next to the visualization elements (above or below, right or left). Large bubble visualization elements labels can also have centered labels.

## UN 2.4 Unify comments

![Figure UN 2.4-1: Unify comments](img/un-2.4-1.png)

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.

## UN 2.5 Unify footnotes

![Figure UN 2.5-1: Unify footnotes](img/un-2.5-1.png)

_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.

## UN 3 Unify dimensions

Data in reports and presentations can be viewed from various perspectives called
_dimensions_. For example, all business measures, such as sales, profit,
margin, etc., constitute a measure dimension, all months, quarters, years, etc.,
a time dimension.

Identifying dimensions via uniform visualization will help to understand reports
and presentations.

This section suggests visualization standards for measures, scenarios, time
periods, and structure dimensions.

## UN 3.1 Unify measures

![Figure UN 3.1: Unify measures](img/un-3.1.png)

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.

**Basic measures and ratios**

_Basic measures_ such as “export sales” are directly
derived from business processes. _Ratios_ such as “return
on sales” are quotients of two basic measures.

**Basic measures**

Basic measures have either _currency units_ (e.g.
EUR) or _physical units_ (e.g. kg). They are
neither shares of something (percentages) nor quotients
of two measures.

![Figure UN 3.1-1: Monthly basic measures in a column chart](img/un-3.1-1.png)

Use 2/3 of the category width for the column width in _column charts_ and the bar width in _bar charts_ to visualize basic measures.

![Figure UN 3.1-2: Monthly basic measures in a line chart](img/un-3.1-2.png)

Use thick lines for representing basic measures in _line charts_.

**Ratios**

*Ratios* are quotients of two basic measures
such as “return on sales”. In practice, few denominators
exist: “Sales”, “units sold”, “headcount”, and “capital”
constitute the majority of all business ratios.

If both the enumerator and denominator have the same unit
the resulting ratio has no unit. It is expressed in
_percent_ (e.g. “profit in % of sales”).

In addition, if both enumerator and denominator have the
same basic measure (e.g. “headcount”), it is called a
_share_(e.g. “gender share”).

![Figure UN 3.1-3: Monthly ratios in a column chart](img/un-3.1-3.png)

The width of both bars and columns representing _ratios_ is 1/3 of the category width, i.e. 50% of the width of bars and columns representing _basic measures_.

![Figure UN 3.1-4: Monthly ratios in a line chart](img/un-3.1-4.png)

Represent ratios in _line charts_ with thin lines
(50% of thick lines).

**Value and volume**

_Value_ measures such as “profit” and “capital” have currency units. _Volume_ measures such as “shipment” and “headcount” have physical units.

**Flow and stock**

_Flow_ measures like “net sales” relate to a certain _time period_ such as months or years. _Stock_ measures like “inventory” relate to a certain _fixed date_, such as December 31st of 2015 (at midnight).

**Positive, negative, and neutral impact**

An increase of a *positive measure* such as “profit” or “sales” positively impacts the organization’s result.

An increase of a *negative measure* such as “cost” or “waste” negatively impacts the organization’s result.

An increase of *neutral measures* such as “market size” or “investment” has no direct impact to the organization’s result.

## UN 3.2 Unify scenarios

![Figure UN 3.2: Unify scenarios](img/un-3.2.png)

_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 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](09-unify.md#un-41-unify-scenario-analyses)).

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.

**Actual scenarios: measured data**

![Figure UN 3.2-1: Visualization of measured data](img/un-3.2-1.png)

Scenarios with measured data are identified by a solid dark (e.g.
black or dark gray) fill for the areas of the respective
visualization elements.

If measured data of recent periods (“Actual”) are compared with
measured data from earlier periods (e.g. “Previous year”,
“Previous month’”, “Month YoY”) the areas representing the
earlier periods are identified by a lighter solid fill (e.g.
light gray).

The suggested two-letter codes for the most important measured
data scenarios are “AC” for “Actual” and “PY” for “Previous
Year”.

**Planned scenarios: fictitious data**

![Figure UN 3.2-2: Visualization of fictitious data](img/un-3.2-2.png)

Scenarios with fictitious data are identified by bordered
(outlined, framed) areas of the respective visualization
elements. The areas within these borders literally “fill up when
materializing”, e.g. when changing from fictitious data to
measured data.

The suggested two-letter codes for the two most important
fictitious data scenarios are “PL” for “Plan” and “BU” for
“Budget”.

**Forecasted scenarios: expected data**

![Figure UN 3.2-3: Visualization of expected data](img/un-3.2-3.png)

Expected data is strictly speaking fictitious, so they are also
identified by bordered (outlined, framed) areas. However, as it
is based on measured data, the area fill of the respective
visualization elements becomes hatched. The color of the dark
stripes correspond to the color of measured data (e.g. dark
gray).

The suggested two-letter code for the most important expected
data scenario is “FC” for “Forecast”.

## UN 3.3 Unify time periods and points of time

![Figure UN 3.3: Unify time periods and points of time](img/un-3.3.png)

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.

**Visual direction of time periods**

![Figure UN 3.3-1: Visual direction of time periods](img/un-3.3-1.png)

As opposed to structural comparisons, horizontal axes visualize data series over time. In tables, present data series over time in columns. In both cases time moves from left to right.

**Time period and points of time abbreviations**

![Figure UN 3.3-2: Time period and points of time abbreviations](img/un-3.3-2.png)

For a better understanding, use unified _abbreviations for
time periods and points in time_. ISO 8601 recommends
the following pattern for time periods: YYYY-MM-DD (e.g.
2017-05-13) for its unambiguousness and easy sorting. The
_abbreviations_ in the figure.

In some countries or organizations other abbreviations such as
Oct 2017, Q2 2017, W07 2017 are common. They can also be used as
long as they are used consistently.

A “.” (full-stop) before the period name indicates the _first
day_ of a time period, e.g. “.2017” for the first day of
2017 or “.Jun” for the first day of June.

Likewise, append “.” (full-stop) to the period name to visualize
the _last day_ of a time period, e.g. “2017.” for the
last day of 2017 or “Jun.” for the last day of June.

The sign “..” (two full-stops) indicates a _time span,_
e.g. “Jan..Mar” (without blanks) for “from January to March.”
N.B.: Use two dots instead of three dots (“ellipsis”).

**Category widths**

![Figure UN 3.3-3: Category widths](img/un-3.3-3.png)

When helpful, differentiate different types of time periods with
different _category widths_ according to this rule: the
longer the period the wider the category segments on the
category axis.

It might be necessary to use rather _wide_ category
segments to label stacked columns or rather _narrow_
category segments due to restricted dashboard space. In any
case, if certain period types have been allocated certain
category widths, this allocation should be the same for the
entire report or presentation.

## UN 3.4 Unify structure dimensions, use vertical direction

![Figure UN 3.4: Unify structure dimensions, use vertical direction](img/un-3.4.png)

_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.

## UN 4 Unify analyses

_Analyses_ are carried out in order to understand certain business
situations, e.g. finding the greatest variances from a plan or calculating the
monthly average.

This section comprises analyses regarding different dimensions such as scenario
analyses, time series analyses, and structure analyses. A section covering
different adjustment analyses is added.

## UN 4.1 Unify scenario analyses

![Figure UN 4.1: Unify scenario analyses](img/un-4.1.png)

_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.

**Scenario comparisons**

![Figure UN 4.1-1: Scenario comparisons](img/un-4.1-1.png)

_Scenario comparisons_ place the data of different
scenarios next to each other, for example actual data next to
previous year or budget data. This is relevant for both charts
and tables. In tables, scenarios usually are shown in columns.

Scenarios can be compared in an absolute or relative way:

Absolute variance = primary scenario – reference scenario

Relative variance = absolute variance / reference scenario

![Figure UN 4.1-2: Column charts with scenario comparisons](img/un-4.1-2.png)

Arrange scenarios of _different time periods_ (mainly
years) in temporal ascending order either from left to right
(horizontal axes) or from above to below (vertical axes), e.g.
PY (= AC 2014), FC 2015, PL 2016.

No rule governs the sequence of scenarios referring to the
_identical time period_ – e.g. PL 2015, FC 2015, AC 2015,
but the selected sequence should be kept the same in all charts
and tables.

_Scenario comparisons_ are visualized either by grouping columns or bars (e.g. overlapping columns of PY and AC or overlapping bars of PL and AC), or with *scenario triangles* using the respective area coding (e.g. solid light color for PY) to represent the reference scenario. _Scenario triangles_ can also be added to overlapped bars or columns in order to show a third scenario.

The scenarios AC and FC stand in the foreground of other
scenarios in grouped columns or bars.

**Absolute variances**

An _absolute variance_ is the difference between two
values of one measure from different scenarios.

The sign “Δ” represents the absolute variance as a prefix to the
subtrahend of the respective difference, i.e. “ΔPL” for the
absolute difference “AC minus PL” (AC-PL) or – if FC is compared
to PL – “FC minus PL” (FC-PL).

The most common _absolute variances_ are the following:

-   **Plan variance:** “ΔPL” for AC-PL or FC-PL
    (when comparing FC to PL)

-   **Previous year variance:** “ΔPY” for AC-PY or
    FC-PY (when comparing FC to PY)

If it is not clear whether AC or FC is compared to plan in ΔPL or
ΔPY, use the following notation:

-   **Plan variance:** “AC-PL” and “FC-PL”
-   **Previous year variance**: “AC-PY” and “FC-PY”

_Positive absolute variances_ (as well as positive percent
variances) have a “+” to emphasis this aspect: “+13” always
means a _variance_ of 13, “13” means any absolute value
of 13.

If absolute variances are displayed in columns or bars (“variance
columns” or “variance bars”), these variance columns or bars
have the same width and the same scale as the corresponding base
value columns or bars.

![Figure UN 4.1-3: Colors for displaying variances](img/un-4.1-3.png)

Variance bars and columns representing a _positive impact_
on business issues (mainly result) are colored green, those
representing a _negative impact_ red, see figure on the
left. Variance bars and columns representing a _neutral
impact_ are colored medium gray. If no color is
available, replace red with dark gray, green with light gray.
For readers with color deficiency, replace green with
blue-green.

If it is helpful, numbers in tables representing variances are
colored in the same way.

**Note**: These colors for positive, negative, or neutral variances must not be confused with red and green “traffic lights” (see also EX 2.5 “[Replace traffic lights](04-express.md#ex-25-replace-traffic-lights)”).

![Figure UN 4.1-4: Bar charts with absolute variances](img/un-4.1-4.png)

In order to visualize the _scenario to be analyzed_ (minuend), apply scenario notation to the fill of the variance columns or bars, e.g. _solid_ green or red fill for AC and _hatched_ green or red fill for FC. If in special cases the minuend is PL (e.g. variance of plan versus average) the variance columns and bars are _outlined_ green or red.

Position data labels for variance columns and bars always
_outside_ of these visualization elements. These labels’
position aligns with the direction of positive or negative
increase, i.e. the label of a positive variance (green) in a
variance column is positioned above the column; the label of a
negative variance (red) on the left hand side outside of the
bar.

In order to visualize the _reference scenario_ (subtrahend) of an absolute variance (in general PY, PL, or BU), apply scenario notation to the axis: For absolute variances to PY the axis is colored solid light, for absolute variances to PL or BU the axis takes an outline shape (two parallel lines).

Treat variances of ratios, e.g. percent values (profit on sales)
in a special way: Absolute variances of percent values are
called _percent points_, e.g. AC 50% – PL 40% = +10pp.

**Relative variances**

A _relative variance_ is an absolute variance as a
percentage of the subtrahend of the absolute variance.

For the textual notation of relative variances, use the sign “Δ”
as a prefix to the subtrahend and the sign “%” as appendix, e.g.
ΔPL% for the relative variance (AC-PL)/PL\*100.

The most common _relative variances_ are the following:

-   **Plan variance**: “ΔPL%” for (AC-PL)/PL*100 or
    (FC-PL)/PL*100 (when comparing FC to PL)

-   **Previous year variance**: “ΔPY%” for
    (AC-PY)/PY*100 or (FC-PY)/PY*100 (when comparing FC to PY)

Display “n.a.” (not available) if the calculated relative
variance cannot be interpreted, as is often the case when a
positive value is compared to a negative reference value
(denominator):

```
Profit AC = 30
Profit PL = -30
ΔPL = +60
ΔPL% = 60 /
-30 = -200% => n.a.
```

Use the following notation, if it is not clear whether AC or FC
is compared to Plan:

-   **Plan variance**: “(AC-PL)%” and “(FC-PL)%”
-   **Previous year variance**: “(AC-PY)%” and “(FC-PY)%”

_Positive relative variances_ (as well as positive
absolute variances) have a “+”-to emphasize this aspect: “+13%”
always means a _variance_ of 13%, “13%” means any kind of
percentage such as ratio or a share.

![Figure UN 4.1-5: Columns charts with relative variances](img/un-4.1-5.png)

Relative variances are displayed in thin columns (vertical pins)
or thin bars (horizontal pins), see the two figures on the
left.

Pins representing a _positive impact_ on business issues
(mainly result) are colored green, those representing a
_negative impact_ red. Pins representing a _neutral
impact_ on business issues are colored medium gray. If
no color is available, replace red with dark gray, green with
light gray. For readers with color deficiency, replace green
with blue-green.

![Figure UN 4.1-6: Bar charts with relative variances](img/un-4.1-6.png)

The labels of pins and the numbers representing variances in
tables can be colored in the same way.

**Note**: These colors for positive, negative, or neutral variances must not be confused with red and green “traffic lights” (see also EX 2.5 “[Replace traffic lights](04-express.md#ex-25-replace-traffic-lights)”).

Position data labels of pins outside the pin in the direction of
the positive or negative increase, e.g. position the label of a
horizontal pin depicting “sales growth in %” (green) on the
right hand side of the pin, position the label of a vertical pin
depicting “cost decrease in %” (green) below the pin.

Add head markers to the pins to visualize the _scenario to be analyzed_ (minuend). Apply the scenario notation to the fill of the heads, e.g. solid dark fill for AC and hatched fill for FC.

Apply the scenario notation to the axis in order to visualize the _reference scenario_ for a relative variance (in general PY, PL, or BU): For relative variances to PY fill the axis solid light, for relative variances to PL or BU the axis takes an outline shape (two parallel lines).

Treat relative variances of percent values the same way as
relative variances of absolute values, e.g. (AC 50% – PL 40%) /
PL 40% \* 100 = +25%.

## UN 4.2 Unify time series analyses

![Figure UN 4.2: Unify time series analyses](img/un-4.2.png)

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

**Year-to-date analyses**

![Figure UN 4.2-1: Year-to-date analyses](img/un-4.2-1.png)

_Year-to-date analyses_ (YTD) refer to the period from the
beginning of the year to the present (_YTD time span_).
The beginning of the year is not necessarily January 1. Some
companies have fiscal years beginning at other dates.

Where helpful, visualize analyses showing YTD values by prefixing
an underscore to the _time period name_, e.g. “\_Jun 2015”
or “\_Jun∅” respectively. Optionally, add
the first period of the YTD time span, e.g. “January_June 2015”.
In charts, add the underscores as a prefix at the left hand side
of the end of the columns or at the upper side of the end of
bars.

Year-to-date operations cover accumulation of values, calculation
of averages, and picking of last date values.

**YTD accumulation**

In this context, _accumulation_ means totaling successive
time period values from the beginning of a calendar year or
fiscal year to the present. In this stricter sense, accumulation
applies only to flow measures, such as sales or costs.

If it is helpful, visualize analyses showing _YTD
accumulation_ with the underscore prefix (without
additional notation) e.g. “\_Jun 2015”.

**YTD average**

In this context, the _average_ is calculated by dividing
the _YTD accumulation_ by the number of periods in the
_YTD time span_. YTD average applies to both
_flow_ and _stock measures_.

If it is helpful, visualize analyses showing _YTD
averages_ with the underscore prefix and an appended “∅”
sign, e.g. “\_Jun 2015∅”.

**Last date value**

A special YTD analyses for stock measures is picking the _value of the last date_ in the _YTD time span_.

If it is helpful, visualize analyses showing _last date values_ with the underscore prefix and an appended full-stop, e.g. “\_Jun 2015.”.

**Year-to-go analyses**

By analogy to year-to-date analyses, _year-to-go analyses_
(YTG) refer to the period from the presence (now) to the end of
the (fiscal) year.

Where helpful, visualize analyses showing YTG values by appending
an underscore to the _time period name_, e.g.
“Jun-2015\_”.

**Moving analyses**

![Figure UN 4.2-2: Moving analysis labeling in a column chart](img/un-4.2-2.png)

In general, _moving analyses_ refer to the period of the
previous twelve months.

If it is helpful, visualize moving analyses by prefixing the _time period name_ with a tilde, e.g. “~Jun 2015” or “~Jun∅” respectively. In charts, add the tilde as a prefix at the left hand side of the end of columns or the upper side of the end of bars.

Similar to year-to-date operations, moving analyses cover
accumulation of values (_moving annual total_ MAT),
calculation of averages (_moving annual average_ MAA),
and picking of last date values.

The visualization concept for _accumulation of values_, _calculation of averages_, and _picking of last date values_ is identical to the visualization concept of year-to-date analyses – the tilde simply replaces the underscore.

**Temporal indexing**

![Figure UN 4.2-3: Visualizing temporal indexing](img/un-4.2-3.png)

Using _temporal indexing_ (indexing a time series), all period values are depicted in relation to the value of a chosen reference period (1 or 100%).

To visualize temporal indexing, position a black arrowhead
pointing right at the left of the index point. “100%” or “100”
is written left of the arrowhead. If
helpful, add an assisting horizontal line.

## UN 4.3 Unify structure analyses

Notation for _structure analyses_ covers averaging, ranking,
selecting, indexing, and normalizing.

**Structural average**

![Figure UN 4.3-1: Visualizing structural averaging](img/un-4.3-1.png)

The term “_average_” usually refers to the mean of different values. The section time series analyses described _temporal averages_ (e.g. monthly average of a year). _Structural averages_ (e.g. average sales of several subsidiaries) are covered here. Typical structural averages are average by product, average by country, and average by customer.

Visualize analyses showing structural averages with a “Ø” sign
either appended or as a prefix, e.g. “EuropeØ” or “Ø464”. If needed, add an assisting line.

**Ranking**

_Ranking_ analyses refer to descending or ascending
rankings of structure elements. Words can be ranked in
alphabetical order, numbers in numerical order.

If helpful, append an arrow sign to rankings, e.g. “country
names↓” or “product sales↑”.

**Selecting**

The structure analysis _selecting_ is related to the
structure analysis _ranking_, used, in general, to
determine either maximal (fastest, most expensive) elements or
the minimal (slowest, cheapest) elements. Top ten, last ten,
first quartile, last percentile, etc., are common forms of
selecting.

**Structural indexing**

![Figure UN 4.3-2: Visualizing structural indexing](img/un-4.3-2.png)

_Structural indexing_ depicts all element values in
relation to the value of a chosen reference element (=1 or
100%). Typical reference elements are the mean, the maximum, or
a specific element in a given structure, e.g. “Germany = 100%”.

To visualize _structural indexing_, position a black
arrowhead close to the index point. “100%” or “100”, is written
next to the arrowhead. If helpful, add
an assisting line.

**Structural normalizing**

![Figure UN 4.3-3: Visualizing structural normalizing](img/un-4.3-3.png)

_Structural normalizing_ refers to the comparison of
several shares of some whole, e.g. shares of export to different
countries. Indexing and normalizing are similar analyses,
indexing refers to one element (e.g. a selected country),
normalizing to the whole of several parts (e.g. country sales in
% of Europe sales).

To visualize _structural normalizing_, add an assisting
line representing 100%. Position a black
arrowhead at one end of the assisting line. “100%” or “100”, is
written next to the arrowhead.

## UN 4.4 Unify adjustment analyses

_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.

## UN 5 Unify indicators

_Indicators_ in reports and presentations serve different purposes, e.g.
highlighting and scaling. Using the indicator with the same design for the same
purpose will help to identify the situation much faster.

## UN 5.1 Unify highlighting indicators

![Figure UN 5.1: Unify highlighting indicators](img/un-5.1.png)

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.

**Assisting lines and areas**

![Figure UN 5.1-1: Assisting lines](img/un-5.1-1.png)

Use _assisting lines_ for different highlighting purposes,
e.g. for showing differences, for separating, arranging, or
grouping data in charts or tables, or for coordinating
visualization elements of different charts, see figure on
the left.

Use _assisting areas_ for different highlighting purposes,
e.g. for highlighting words in a longer text, or for
highlighting certain parts of charts or tables.

**Difference markers**

![Figure UN 5.1-2: Difference markers](img/un-5.1-2.png)

Highlight differences in charts by using two parallel assisting
lines to project the respective lengths of two columns or bars
to a _difference marker_ highlighting the distance
between the two assisting lines.

Position difference markers in a way that they can clearly
highlight the respective difference.

Difference markers representing a positive impact on business
issues (e.g. profit) are colored green; difference markers
representing a negative impact on business issues (e.g. loss)
are colored red. Difference markers representing neutral impacts
on business issues are colored gray.

**Trend arrows**

![Figure UN 5.1-3: Trend arrow](img/un-5.1-3.png)

Arrows can highlight trends in charts and (seldom) tables, too.

_Position trend arrows_ in a way that they can clearly
highlight the direction of the trend with the respective slope.
The arrow starts at the first period and
ends at the last period included in the calculation of the
respective trend. The arrowhead is pointing in time direction.
Adding a number and a designation for the calculation method
(e.g. CAGR: 10.8%) will give additional insight.

Trend arrows representing a positive trend are colored green;
trend arrows representing a negative impact on business issues
(e.g. loss) are colored red. Trend arrows representing neutral
impacts on business issues are colored gray.

**Highlighting ellipses**

![Figure UN 5.1-4: Highlighting ellipse](img/un-5.1-4.png)

_Use highlighting ellipses_ to highlight single values.
Good reasons for highlighting single values are e.g.

-   **Highlighting messages**: If the message
    refers to a specific value in a chart, table or graph,
    highlight this value with a blue ellipse.

-   **Highlighting additional values**: Sometimes
    it is helpful to add additional values (e.g. percent value)
    in charts or tables. In this case, use a black ellipse.

**Reference arrowheads**

![Figure UN 5.1-5: Reference arrowhead](img/un-5.1-5.png)

_Use reference arrowheads_ for highlighting a reference
standard. Examples of reference standards are:

-   **Indices**: Either one value (e.g. the value of the year 2010) is set to 100%, or the total is set to 100% (see sections about time series analyses and Structure analyses).

-   **Benchmarks**: Popular benchmarks are market averages, competitors, or best practices.

Position the arrowhead close to the point representing the index
or the benchmark. Write the label for
the index (e.g. “100%” or “100”) or for the benchmark (e.g.
“Market avg.”) next to the arrowhead. The arrowhead points in
the direction of an imaginary index or benchmark line. If
helpful, add an assisting line.

**Comment references**

![Figure UN 5.1-6: Comment reference](img/un-5.1-6.png)

Use _comment references_ in pairs to link comments to the corresponding values or positions in a chart or a table.

**Variance highlighting indicators**

Highlight variances in tables by using visualization elements representing the magnitude of the variance, such as bars and pins (see also EX 2.5 “[Replace traffic lights](04-express.md#ex-2—5-replace—traffic-lights)”). “Traffic lights” might be useful for highlighting _single variances_ related to the message or to comments in tables without chart elements, though. Another means for highlighting _single variances_ are “warning dots” positioned next to the value or text element needing attention.

Indicators highlighting variances representing a _positive
impact_ on business issues are colored light green,
those representing a _negative impact_ light red. If no
color is available, replace red with dark gray, green with light
gray. For readers with color deficiency, replace green with
blue-green.

Use only few variance highlighting indicators per page.

**Other highlighting**

Add visualization elements for not-valid values, limits, or other
relevant phenomena. Standardize and document these “signals” so
that they become an effective means of communication.

## UN 5.2 Unify scaling indicators

![Figure UN 5.2: Unify scaling indicators](img/un-5.2.png)

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.

**Scaling lines**

![Figure UN 5.2-1: Scaling line](img/un-5.2-1.png)

Use scaling lines when comparing multiple charts (with the same
unit) having different scales. Position a scaling line parallel
to the category axis at the same numerical height in all charts.
If one chart among several other charts
uses a different scale, this fact can easily be identified (in
general, the differing scale uses a multiplier of ten).

**Scaling areas**

![Figure UN 5.2-2: Scaling area](img/un-5.2-2.png)

If helpful, fill the areas between the scaling lines and the
category axes with light color. Use
different colors for scaling lines and scaling areas used in
order to represent different scales.

## UN 5.3 Unify outlier indicators

![Figure UN 5.3: Unify outlier indicators](img/un-5.3.png)

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.

[← Ensure visual integrity](07-check.md)