Management Reports & Dashboard Best Practice

1. Well-chosen KPIs = Better Business Decisions
How to choose the right KPIs to put into Management Reports and Dashboards.
2. Dashboard Design
What is the best way to present and layout a Dashboard for Management?
3. Dashboard Visual Indicators
Choosing the best Charts, Gauges, Tables, Scorecards to communicate the message.
4. Choosing the Right Chart
How to pick the correct chart to fit your KPI or performance figure.
5. Time and Category Charts
Time and Category Charts are fundamentally different and therefore should be used differently.
6. Measurement Charts
The best charts and approaches when you want to see exact values.
7. Trend Charts
The best charts and approaches when you want to communicate trends.
8. How to Reveal Trends
How to show a trend from fluctuating data.
9. Comparison Charts
Building charts that compare one year to another.
10. Distribution Category Charts
How to make a chart (such as a pie chart) communicate the distribution of categorised data.
11. Filtering and Pivoting Categorised Data
See time-based figures by category, and compare categories side-by-side over time.
12. Don't Forget The Data
Why it's important to display data with your visuals and how to do it.
13. Paper and Electronic Reports
Paper is just as important as electronic dashboards, but there are some key differences in how to present information.

1. Well Chosen KPIs= Better Business Decisions!

I regularly see hundreds of Key Performance Indicators, that aren't really KPIs; they are just 'measures for measure's sake' or low level management data. The purpose of your KPI is to communicate a situation to a particular person, but almost every manager forgets this and focuses on what they are measuring. In this chapter we are going to look at the principle of what you should measure, why and how.

Firstly, let's consider a typical company structure. Normally this is a pyramid.
 
Depending on the size of the business it may have more or less layers than outlined in this diagram.

The Ideal Information Flow

Now let's consider the information flow in an 'ideal' business. Typically this starts at the bottom with our lower tier managers reviewing detailed information on a day to day basis from their staff but with higher level managers seeing simply an overview.

Let's imagine one of our operational managers monitors our production. A delay in our production here (say down to staff sickness) is something she would want to know about. If she can see we are behind schedule then she can do something about it by moving other members of staff in to lend a hand and get the order out on time.

Whilst this is a KPI for the lower Tier manager, this is certainly not important for someone higher up the management pyramid. This manager's job is to manage this issue; it's not an upper management issue.

When producing your KPIs you need to 'tier' them. Knowing what kind of data people need is an important part of data management. One manager's critical Key performance Indicator is too much detail for another manager.

Ideally you will have a small number of KPIs for each manager to review. Companies often produce too many metrics, and often managers end up producing statistics without a clear idea of why they are doing this.

Know the "Message"

Consider that a KPI's job is to tell you one of these three things;

1. Things are OK
2. Things are looking bad
3. Things are looking good

For a key performance indicator to be useful, a manager must know what to do in each of these scenarios. Most likely "1" would mean do nothing, but "2" must have an action associated to it or it misses the point of the performance indicator. Equally "3" may well have an action such as "expand with more staff".

KPIs almost always have dates.

This may seem an obvious point, but almost every KPI should have a date associated with it and as a result operate on a fixed period, i.e. daily, weekly, monthly, quarterly or yearly. We often see people who forget this.

For example, I once saw "Average production time" for a particular job, but the figure took into account all the jobs the company had ever done, and was displayed as an "all-time" average in a single figure, e.g. "2.35days". On the report there was only this one figure and no previous values were shown. This was an actual key performance indicator for the company. Considering one of our earlier points, what actions would this trigger? As there was only one figure, there was nothing to compare it to, and no way of knowing whether this average is good or bad. If this metric was shown on a project management KPI dashboard, it would rely on the memory of the reader to give it context. If he/she remembers that the value last month as lower he/she might take action - Bad approach.

It is always better is to measure a KPI over regular intervals (e.g. every month) and monitor its progress. Therefore, for "Average Production Time", you should calculate the average for all jobs for each full month, starting with January, and save each of these figures. Before long, instead of one single figure we'll have a list of figures that we can see a trend from, making our data management a lot easier and more efficient.

Management Data vs. KPIs

It's easy to mix up management data with key performance indicators. So, what is a KPI? Simply put, they are measures that are reviewed and shared periodically, and show how your business is performing. On the other hand, management data is normally just for a specific manager to analyse and manipulate as it happens. For example a "support desk case" is profiled with information about what type of case it is, say a "printer problem". The database of every support desk case can be very useful to analyse and review from time to time. Excel is great for doing this, and you can often find out some interesting facts and review your processes accordingly. However this is not a key performance indicator, but an analysis of management data. A KPI is something we measure periodically and compare, so we might produce a monthly summary of the number of "Support desk case Types", for example:

This is a standard metric that we can plot monthly and watch for changes. For example, if "training issue" increases, we can review and improve our training programmes to hopefully  reduce the number of issues.
.
Another example is Accounts systems, which produce management data. Normally there will be people in your business who are expert at manipulating accounting reports with specialist accounting software. When you want to find detailed information about a certain invoice (e.g. the amount invoiced), this is best done here. But, we can actually summarise a lot of this detailed data into KPIs, and use this data  in management dashboards or reports to tell us something about overall performance. Therefore, you can take the '"Amount Invoiced" for every invoice in your system this month, and summarise it as"Total Amount invoiced this month".

The Four Types of KPIs

Each KPI you have will likely be one of the following types. Knowing the types of your KPIs is important,  as each of these types has good and bad ways to chart and display them. The best KPI dashboard is one where information is presented in a simple, easy-to-follow way. We will discuss this later on.

Quantitative KPIs

These are KPIs with a very specific number and where knowing this number is critical, for example, a chart in a marketing KPI dashboard showing "Number of leads" [per month].

Directional KPIs

With many KPIs the number is much less important than the direction that the data is trending. For example, "Number of days lost to staff sickness" [per month] in a HR KPi dashboard. Here, the exact number of days is not that useful as we can't control this, however if the trend is rising we can investigate and take action accordingly.

Actionable KPIs

Most often these have a target / budget associated with them, as well as actions that happen if we fall above or below this budget figure. For example, if we have "department costs" and we also have a budget figure every month, then we will likely take action if we go over our budget.

Distribution / Category KPIs

Often you want to see the split of various categories within  your KPI metrics, such as in our previous example "What type of support case types are you receiving?" Again, a shift towards "general help" could indicate a problem with your training.

2. KPI Dashboard Design

There are KPI dashboards where you just can't help but admire the total beauty of their graphics; surely your boss will love you if you show him a shimmering, shiny black dashboard with gorgeous animated charts. If that's what you are looking for, then hire a great graphic designer.

Our focus has always been on building dashboards that help manage businesses and organisations. The definition of a dashboard isn't pretty graphics: dashboards are an easy-to-digest view of an organisation's key performance indicators that lets viewers spot decisions and act on opportunities quickly. So, while we like to look good, a dashboard that fails to communicate key messages in your business data is a waste of time, money and effort.

With modern KPI dashboard software it's really easy to place hundreds of metrics on a single view, but this creates clutter and can cause you to take your eye off the ball. We want to track "Key" performance indicators, not "every" indicator we can think of. For example, if you have project management dashboards which you use to keep track of multiple projects, you'll only want to track what is absolutely neccessaryto keep things manageable. In this case, any unneeded data on your dashboards is just a distraction.

Try to build a selection of dashboards with overview and detail views, so that managers can quickly review high level information and then look deeper only if they wish. If you create an overview, make sure that everything a manager needs to know to make decisions in in this dashboard. If a crucial metric is only in a detailed view, it is likely to be overlooked.
 

This example of a management dashboard shows an overview of key information. Note the summaries of multiple departments, which can be crucial for decision-making.

 

Understanding the Purpose of Dashboards.

You'll be amazed how often managers start to build a business management dashboard, without considering what its purpose or objective is.
Dashboards are there simply for the following purposes:

• To make comparisons
  

• See trends over time
  

• See distribution

• See relationships between parts of our process / organisation
  

Dashboards by Management Layer

Remembering the pyramid structure of a typical Management team, you should normally model this structure in business dashboards. However, sharing your dashboards across the management team can be extremely beneficial for the management of a company.

Typically organisational data becomes trapped in its respective department. But consider this: if the operations department was aware of an increase in advertising spend by the marketing team then they could proactively have plans for the extra work load. This can only occur if business dashboards are shared across departments allowing managers to see the relationships between interdepartmental data.

One table of data - one chart - No!

To report on business data, Most people will prepare a table that collects multiple metrics running month-on-month, and use this data to create a single chart to display the results. Whilst sometimes this is OK, very often this doesn't communicate information as clearly as it could. It's tempting to show too many line charts on a single axis for perceived convenience, but the result can be confusing. Equally, too much detail over too long a time period can result in important current trends being missed.

 

This chart is too complex to make sense from - better to split it into several charts

Dashboard Design Tips

• Create 2 or 3 charts from the same data, or even an entire dashboard. Each chart has a different viewpoint or comparison to communicate.
  
• If you want a chart with "everything" showing on the same axis for exact comparison, consider duplicating this chart several more times, but with the duplicates showing just one metric at a time.
  
• To show metrics over a long time period, create two charts in your dashboard: Create your long range chart, but with the detail removed (as if you had zoomed out). Remove the detail by grouping by quarters instead of months or by adding a rolling average. Then immediately alongside it, show a highly detailed chart but for a much shorter time frame, say the last 2 months. This way we can see the bigger picture over the long term, but also get the immediate and recent data at the maximum resolution. This gives us context for decision making.
  
  
  Low detail, long time range chart, next to a high detail short range chart

 

Physical layout

There are no hard or fast rules about how to layout your dashboards. It's very easy to lay out charts and other visual indicators in a grid or in columns, but sometimes this does not allow enough room to view your performance values over a longer time period.

Depending on your data, you may want to choose a layout that allows some charts to be displayed with more width. As a general rule the more width a "time based chart" has the better, but a "category chart" such as a Pie Chart generally only needs a square and will be wasteful of our space if put into a larger width rectangle.

The left hand dashboard is based on a grid, the right hand had wider areas for viewing a longer time range.
As a general rule you are better to avoid too much scrolling. It's better to create new dashboards than have too much information on one dashboard resulting in clutter and potentially information overload.

 

 

 

3. Dashboard Visual Indicators

"What type of visual indicators should I put on my dashboards?" is a question that I am very often asked. Before answering this question, it is important to understand the following:

• What is the metric and how important is it?
  
• What is the message, good or bad, that you are trying to communicate visually?
  
• Does it have a target, budget or threshold value?
  
• Do we want to measure specific values from the Indicator, do we want to review trends or see distribution across some categories?
  
• Do we want to make any comparisons to other data?

Time Charts

Time-based charts are the foundation of most dashboards. They allow us to spot trends, measure values and make comparisons. The time chart is by far the most effective communication tool for the size that it takes up on your dashboard.

There are so many styles and layouts of time charts that you can normally represent any data in an easy to read way. To see which charts can best communicate your message, take a look at our list of KPI time charts.

 

Category Charts

Category charts take on many guises, but are more often represented as Pie Charts. They display the distribution of various categories across a specific time frame.
Category charts look great, but should not be overused as they do not show historical or trend information. A category chart is great to compliment an existing time chart using the same data but displaying a distribution breakdown.



Whether you display your key performance indicators in Pie Charts or in column charts depends on what you want to see from your data. Column charts are great if you want to compare the values for each category side-by-side, and pie charts are great if you want to see the relation of one category to the entire value, e.g. the amount that one salesperson contributed to the entire year's turnover.

There are many ways to present categorical data, and our list of category charts can show you how.

Gauges and Dials

Gauges are a long-time favourite of the marketing manager of Dashboard applications. They look glossy and great and present the current situation to a reader. They work best when combined with a target value, for example, showing a real-time display of a call centre's "number of calls waiting" but in my view they offer a poor method of communication to the reader.

The big problem with a gauge is that it takes up a lot of space and does not tell us anything about the past. So take the example on the right hand gauge above. Is "154 Emergency Repairs" [done on time] good or bad? It's above the target... but what if..

• 3 months ago performance had been awful, but since new changes came into place month on month performance has improved to the current level.
  Or,
• For the last 3 months performance has been getting worse and worse, viewing the trend would suggest that next month we would fall well below target.
  

Can you see how a gauge fails to communicate these two situations (one good one bad)? The point of a dashboard or management report is so that we can foresee problems and deal with them before they become a big issue. With a gauge the chances are that you will not see the trend and your customers will be telling you that your performance is poor well before your gauge turns red.
Gauges are not a favourite indicator or mine. I believe a time chart in the same square inches of space is a far superior management communication tool.

There are a few different types of gauges which can serve different purposes for your data. Our list of gauges will give you a breakdown of each.

 Key Point: To use gauges effectively, you should pair them with other time-based charts to get not only an immediate snapshot of your organisation's status, but also some trend data to give it context.

 

Spark Lines and Trend Indicators

A spark line or trend indicator is a clever way to put numerical information into some context. They are small and compact and can easily be included in tabular and numerical data. Their purpose is simply to "indicate" the trend and in my view they are a welcome addition to dashboards of any purpose.

 

Score Cards or Progress Tables

If you would like to get a lot of information into a small space then developing a scorecard is a good bet. Scorecards combine both numerical and graphical information in a very compact display. This is great for an overview or a dashboard where you want to display the "big picture".

What you put in a scorecard depends on how you would like to use your data, but typically you might have:

• Current values
• Previous values for comparison
• Percentage change up or down
• Target value of your metric
• Percentage on or off Target
• Addition of spark lines can also really help place the figures in context.
  

 

Comparison Charts

If your metric is best compared to the same period one or two years ago (e.g. Christmas sales) then a comparison chart is the best approach here. It provides good clear communication of the comparison as long as you don't add too many years, making it a great choice for performance management dashboards.



Again, use a column chart if you want to compare values, or line and area charts if you want to see the trend more easily. If you want to see which is best for you, take a look  at our comparison chart list.

Raw Data

Often forgotten in visual dashboards is the raw data. Sometimes it helps communicate the message if the numbers are combined with the visualisations, so you should consider short tabular summaries.



Take care not to put too much tabular data on a dashboard. Reading large tables of data may not be so easy on a screen,  so keep it summarised and short.

4. Choosing the Right Chart

Which Chart, Gauge or Indicator do you use on your dashboard or reports?

Dashboards must communicate a message, so before choosing charts and indicators for your Dashboard you should consider this:
"What is the message and action that this KPI should communicate?"

Also, remember you don't need just one ultimate, all-fulfilling chart. Try using several different charts on the same dashboard to present different messages from the same data.

Recall how we previously divided KPIs into 4 types, depending on what they communicate.

Quantitative

These are metrics with a very specific number and where knowing this number is critical. For example, "Number of sales" [per month].

Directional

These are metrics where the direction of travel is more important than comparing values. For example, with a KPI such as "Number of days lost to staff sickness" [per month], knowing if the number of days is going up or down is more important than the actual values themselves.

Actionable

These KPIs usually have a target/ budget associated with them, and an action that will happen if values fall above or below this budget figure. For example,  if we exceed our budget for "department costs", we'll likely take some form of action to address this.

Distribution/Category

Often you want to see the split of various categories within a performance indicator. For example, "Type of support case types received?" A shift towards "general help" could indicate a problem with your training.

Each of these data types requires different types of chart to communicate their message, and we will consider this in more depth later. But by way of example, here are 4 charts that are each ideal for the four types of metric.

Quantitative - a column chart showing 'Number of Sales' and the associated target.

Actionable - a gauge showing 'Number of Sales' and the associated target.

Directional - an area chart showing the "Number of Operations" [per month].

Distribution - a pie chart showing "What type of support case types are you receiving?"

 

Charts or Gauges

Pictures of glossy gauges sell KPI dashboard software, and provide the illusion that everything is going great. However whilst not discounting the use of gauges I am far from being a big fan of them.
Consider a speedo style gauge showing a current month's value and a target. If we reach the target then the gauge shows green, and red if we have failed to meet the target.

The problem is that this gauge only shows us a snapshot in time. It tells us nothing about historical performance - just the current situation.
If instead you use a chart with a target line, not only can this give us today's situation but we can also see it in the context of our historical data.




We might have missed the target this month by a tiny amount, so a gauge rings alarm bells, but what if over the last 3 months performance was steadily improving month on month making it look like it should smash the target next month - surely this is good news not bad news?

For the same space in a dashboard, and for the same time required by a manager to review a gauge a chart communicates the same and much, much more information. It does not look as shiny and cool as a gauge, but you have a choice of pretty or profitable.

Numbers and Comparisons

A picture tells a thousand words, so visual indicators are very powerful. But don't forget your audience will be a mix of people who like to see both the visual and the numbers.
Don't forget to make some of the numbers available in your dashboard alongside your other indicators.

One way of doing this is by adding value labels to your charts. Another is to add the latest few months' data as a table or to create a comparison chart in the style of a Scorecard.

A scorecard is a loose term for many different layouts of numerical data. However, no matter the layout, a scorecard's purpose is always the same: to provide useful status and trend information at a glance. For myself, I think that any scorecard ideally should show the following:

• The current month's value, as well as the Previous month's
• The Percentage change between current and previous months
• If appropriate, the relationship our current month has to its target.

Depending on your data, you may also want to make comparisons to the same period (month) the previous year so that you can make a performance comparison.

In the next few chapters we are going to look in depth at the pros and cons of the various chart types, and how they work with KPI examples.

5. Time and Category Charts

Charts have two axes, "X" & "Y" but these can be used in two different ways.

One simple but fundamental concept is that for displaying each of the four types of KPIs, there are normally two different chart types, "Time Charts" and "Category Charts".

Time Charts	Category / Distribution Charts
Time charts always have "Time" on the x axis. This type of chart shows values change over time.	Category charts are most often seen as Pie charts, but could also be a number of other chart types including a column chart. Unlike a time chart, time is not shown on the chart, instead it is broken down by categories within a specified time period.

The best way to see these two chart styles is like this:

• Time charts: Show Trends
• Category Charts: Show Distribution
  

 Most managers see lots of time charts on a week to week basis and they are easy to read. However category charts can often be a little misunderstood, so I'll just spend a minute considering a pie chart.


This category chart is a 3D Pie chart. However it could be any type of category chart, such as a radar chart or a column chart. Look carefully at this chart - what does it tell us?
The answer is actually very little, although it does look nice.
The pie chart is broken down by categories, but for what time period? Here, it's not clear, so as a communication of a performance indicator this is near useless.
If this chart had been titled "Product Sales from Q1" it now becomes more meaningful.

2D or 3D

I love 3D charts, they look great and never fail to impress the casual viewer. However if you really care about the numbers, 3D charts can be very difficult to read, so adding values or annotations is essential. Have a look some of these examples below.

In the example above, 3D can make it awkward to read values. On the pie chart below the values are much clearer.

I like the occasional use of 3D charts, if it helps the presentation. Sometimes round pie charts with annotations do not fit that well in dashboards and making them 3d will fit more neatly. However, making this type of chart into a 3D version can, when viewed on a dashboard, distort the perspective of the chart and cause the wrong value to stand out.

6. Measurement Charts

Depending on your metric, it might be very important to see the exact values plotted on a chart. Some charts are better at this than others.
The golden rule with most charts trying to communicate values is: don't try to put too much data on the same chart. This could mean too large a date range or too many metrics.

By far the best chart is the humble column chart.

The chart can be easily improved with a target or budget line and by changing the y axis minimum from in this case 0 to 30,000. You might see target lines in a quality management dashboard, where metrics are measured to industry benchmarks.



Side by side columns normally only work if you have 3 or 4 columns only, otherwise they become not so good: The chart becomes more cluttered and harder to read than using a target line.

This chart shows the same information as the previous chart but is harder to read

3D is generally a bad idea here and makes a chart even more unreadable.

There are many types of charts for measuring values, but the column chart is normally the most familiar and the best.
You may find that you can also combine this type of chart with other types, such as line charts. So for instance, adding a rolling average line as an indication of trend can give added insight to your chart.

Side by Side Charts

Sometimes we want to see both recent values and also view the data in the context of historical data. In this case you should consider charting the data twice. For example you could show a "rolling 6 month" chart with accurate, easy to read values, and alongside it show the same data over the last 2 years, so the trends and content are more obvious.

Measurement Chart Tips

• It's hard to beat the humble column chart
• Try to show value labels on your chart
• Do not try to plot too much data
• Avoid 3D as it makes values hard to read from the scale
• Consider two or more charts if you want to plot a longer time range, to give the data some context

7. Trend Charts

The most powerful use of time charts is to spot trends. If, as managers, we spot a trend, we can take action before the situation becomes critical and our business will run smoothly. Depending on your KPI type the most important thing might be to illustrate the trend, i.e. the direction of travel, rather than comparing exact values.

Before building any chart ask yourself,
"What is the message?" What is this chart going to communicate?
Trends take many forms, but let's start simply.



This line chart is plotted every month. If you have the space and the chart is not over cluttered, always try to include the values to help give the reader a sense of perspective.
Most of the space on this chart is unused, so we can make the trend more obvious by changing the minimum value of the Y axis from 0 to say, 30,000.



Now our trend is amplified but is still 100% accurate.

Whilst this line chart is 'OK' we can make it visually clearer by making this a filled area chart instead of just a line. Visually, a filled area chart is much easier to spot a trend on than on a line chart because the volume of block colour is easier to read at a glance.

The down side of filled area charts is that they can become difficult to read if you want to plot more than one KPI on the same chart. This is useful when the data has a relationship.

Combining Chart Styles

In this simple example "Costs" are plotted as a red line and the "Invoiced" as the green line.
As a rough guide this company's monthly profits are "Invoiced" - "Costs".
So this chart is very powerful, as the approximate profit is the space between the green and red line.
Again think about the message. Here we're trying to communicate a future problem of profitability and deal with it before it happens.

You can see that in April-13 the costs and invoice line begins to converge - this is bad news, and must be addressed. Let's say that once seeing this, the
 team address this issue. Though they may take some actions that initially cost more money, it will help productivity.

As a result the company briefly make a loss in Sept-13 but they return to profit after this. Not only this, but as the green and red line diverge the profit margin begins to increase, which is great news!

You might ask why didn't we just plot the "profit" on a simple line or area chart to see the trend? The answer is that this chart communicates more information to users. Note that the costs remain almost constant during the entire period and that it is the falling invoice value that is the main reason for our profit problems. This chart illustrates these two trends, whereas a simpler "Profit" line chart would not.

Trend Distribution

Often it's useful to know the trends of distribution. For example if we sell 3 products it's good to know how many of each is sold over time, which can help managers make marketing or product expansion decisions. There are many ways to visualise categorical marketing KPIs and other metrics.

More often than not, a manager will use the Stacked column chart. This is a very useful chart and shows us the total and distribution simultaneously.

 

Whilst this is a useful chart, there is a better and little used way to represent this this data in a much clearer way. Using the Stacked area chart we can more clearly see the distribution of trend over time.



Just like a stacked column chart the values are stacked on top of each other, but in this case it is much, much easier to observe how things change over time.

Trends Chart Tips

• Change the Y-Axis minimum from 0 for values that have a consistently high value. This helps make trends more apparent 
• 'Filled Area' charts are easier to read than line charts
• Multiple series of data plotted on bar charts often look cluttered
• Combine different chart styles, keeping emphasis on one key metric as a bar chart, but showing KPI targets or other information as less-emphasised lines
• Stacked Areas charts are often better for showing distribution over time than stacked column charts
  

8. How to Reveal Trends

For a company that sells 1000's of apps per month, they could track their sales easily on a chart, and the trend would be quite obvious. But consider a company that sells two or three big deals every month. Tracking their performance in a sales dashboard and seeing a visible trend is much more awkward. They might sell 5 projects in January and just 1 in February so any chart would look like a roller-coaster, without any discernable pattern over time.

Managers often find it hard to interpret the good or bad news in such figures. Whilst a best fit line could be added to a chart, I personally am not a big fan because you don't control the mathematical formula behind that line. As a result, you don't really know what's it's telling you.


The solution to this is easy...

Smoothing with a Rolling Average

Either simply chart your monthly data by quarter, so your data is effectively smoothed out. But the down side of this is that you have to wait a whole three months to see a change in your reports.
Or, much better, use a "rolling average", often called a "moving average". This is where we take the latest n (say 3) values and average them to produce a value. In Excel this can be a little complex, but tools like Target Dashboard make this possible with just a single click.

Above - a 6 month rolling average chart

Depending on your data you can increase the damping (smoothness) by increasing the number of months that you run your rolling average over. Using this technique your trend now becomes more obvious and it's easier to take action on what you see.

9. Comparison Charts

Comparison charts allow you to compare a value to its equivalent value at another period in time. For example if our business was seasonal then we might want to compare Dec-13 sales figures with the previous year Dec-12.
Depending on the message behind your KPI, a reader may want to measure values from your chart or simply make a visual comparison. Understanding which of these requirements is the most important will determine what style of chart you use.

Charting Measurable Values

If you need to see directly measurable values on your chart, then the best solution is to use a column chart with a column for every year. This can soon become cluttered, so you are normally best limiting this to a two year range.

Charting For Comparison Purposes

For the majority of uses comparison charts are used just to gauge performance against a previous year. In this instance being able to read the exact numbers is less important when compared to seeing the visual comparison.
3D charts don't just look good here but are actually better allowing us to see the more data than we would have otherwise.

Comparison Charts Styles

It's hard to specify a preference in comparison charts, and I find it very much depends on the type of data you have. If your data is increasing year on year then one style will be more readable than another. Here are some examples:

Comparison Chart Tips

• The more years you choose to show, the harder the chart is to read
• Pick a chart that most suits your data. Rising or falling data often is clearer on different chart styles
• 3D charts can help you to see the multiple years more clearly
  

10. Distribution / Category Charts

If you have a metric where values are broken down across different categories, then you are going to need a Category Chart to visually communicate the current situation.
Category charts are designed to communicate the split of various categories. The most popular of this type is the Pie chart.

Category charts are normally of limited use in a management dashboard because they only show the current situation and don't show any history. particularly with Pie Charts, Pie charts look great on a Dashboard and this often leads to them being over used at the expense of communication.

Unlike a time based chart which would likely show a "time", say months, on the x axis, a category chart has no moving time scale. Instead a category chart is a snapshot of time across a specific date range. So, for example, you might have a pie chart showing product sales by category for the date range "this year to date".

 

Overcoming the Limitations of Pie Charts

Consider a real world situation where we use a pie chart to display the quantity of sales in our key product categories. As the report designer our first job would be to say "what is the message here?". Well commercially I'd suggest that we would want to see if one product's sales were growing at the expense of another product. This might be because more marketing had been done or a product was reaching its end-of-line.

So, we could show a pie chart of last quarter's sales, but again this is limiting because it only shows the current situation and the reader must rely on their memory to decide if what they are seeing is good or bad.
One simple trick to overcome the inability to view historical data is to display not just one pie chart, but two side by side.
So in our example we can create our pie chart for "Last Quarters Sales" but alongside it show a duplicate of this chart, but across a different date range. For example "Rolling last 12 months". So now we have two pie charts from which we can directly compare, effectively showing the current split to a 1 year average.

Two pie charts, each with a different date range

 

Where do Categories come from in your data?

You can only produce a Category chart if your data allows this, i.e. you must have some categories stored in either rows or columns.
Generally there are two approaches to your data here.

1. Categories come from column names

In this data layout each category is a column of data. This data layout is good if you have a small number of categories. If you have 10's of categories then the data can become difficult to manage. Note: each month has one row.

2. Categories are stored in their own column.
If your data comes from a database, this is more typical of what you might have. Note that there are many rows for every month. Below we have a column that contains text of each category type. This format is more complex to handle but allows us to pivot data and track a category over time.

 

 

Chart Layout Tips

Below are some different examples of category charts, however here I am going to focus on a pie chart.

• Try to include labels and call outs to make the chart easier to read.
• Don't have too many segments in your chart. 10 segments below 3% in size will be unreadable. Set a threshold and add anything below say 5% to an "other" slice.
  
• Sometime percentage figures are useful, but at other times the raw values or interactive charts with hovers can be useful here.
  
• Put two charts with different data ranges side by side for comparison.
• 3D pie charts look great but really distort the numbers and can lead to incorrect reading of the chart.
  

Other Examples of Category Charts

While Pie Charts are perhaps the most well known category charts, you can display categories in many different ways, including funnel charts (as you would see in a sales kpi dashboard), donut charts, and bar charts (a basic yet incredibly useful variant).

Funnel Chart

Doughnut Chart

Horizontal Bar Chart

11. Filtering and Pivoting Categorised Data

If you've stored your categories in a single column, you can use Filtering and Pivoting to display your individual categorical KPIs in time-based charts. These are really useful tools for seeing how each category is performing, and also for comparing the performance of multiple categories.

Filtering Data

Filtering your data simply means that you only display a certain portion of your KPI, 'filtering' out the data you don't need. For example, take a look at this data table.



If you were to create a time-based column chart of this data, you would simply see the overall sales value for each month. By filtering it, we can see how each salesperson is performing.



However, I recommend that you include the option to quickly choose which category you want to display. This means that users can quickly flick through each category and get the information they need.



If you'll recall the previous section, we talked about store categories in your data in two ways:

• Including Each Category as an individual column in your data table (e.g. Jane's Sales, John's Sales)

• Placing all categories in one column (e.g. Salesperson), and all values in another (e.g. Sales)

Filtering only applies to the latter option, as if you've stored all categories in multiple columns, there is nothing to filter. Each column is not treated as a single metric but rather several smaller metrics. Therefore, I'd always recommend storing category data in one column if you can, as it gives your category data more context.

If you have more categories (e.g. "salespeople" and "region"), you can also filter a category chart by any category that isn't the one displayed in the chart. For example, you can create a pie chart showing the turnover of all of your salespeople, and then filter that by the region they work.

Pivoting Data

While filtering data lets you see how each individual category is performing over time, pivoting your categorical data lets you display time-based data for each category side by side. Using software, pivoting is usually very simple to do. You can do it in Excel, or in management dashboard software (such as Target Dashboard) in just a few clicks.

Essentially, what happens is that you select a category to pivot your data by, and the software you use displays each category as it's own individual column. This is identical to how your data would look if you chose to put each category in individual columns. Now, you can not only see individual category performance, but chart each category alongside each other.

12. Don't Forget The Data

It's easy to become focused on graphical visualisations for all of your numbers, but sometimes it's worth also showing the numerical values.

Consider you Audience

I personally love charts and anything visual, however I know lots of people who prefer to see numerical data. Every person finds certain kinds of information easier to digest and understand, so it's important that any management reporting information that we put in place bears the user in mind.

 

Throughout most of this article, we have looked specifically at visualisations of data; however in this chapter we care going to look at presentation of numbers when reporting via dashboards. It's important to note that this is often to complement our visualisation and not necessarily a replacement for them.

Displaying raw data

Within a dashboard or paper-based management report you may want to display the raw data as a table summary. It's very easy for this to become overwhelmingly large and therefore hard to interpret, so I would recommend that you limit it to perhaps the latest values or perhaps just the last few months. This is so that your table has only 6-7 rows, and acts as a numerical complement to an existing chart, rather than the focus of the dashboard.
 

Heat Maps

If you have a table summary which contains target and actual values, you can create a heat map that lets you instantly see how your actuals are performing against their targets. Do this by assigning colors to your actual values according to whether they've met, failed or exceeded their targets.

This makes your table easier to interpret quickly, while still keeping your data numerical.

"Score Cards"

There seem to be loads of definitions of what a scorecard actually is. Personally I believe the definition is totally irrelevant. In my view a Scorecard is a graphical and numerical presentation of data that you can use on a periodic basis to evaluate your KPIs. Exactly how that is presented depends on the metric you are measuring, the message you want to indicate and what works best for your organisation.

Above is a simple example used by a company and this works very well to convey a lot of information in a small space. We can see trends, KPI targets, traffic style colour indicators as well year to date (YTD) information. Percentage changed or percentage over or above target can be useful as well as very motivational.

 

Presenting Data Tips

• Consider showing more numerical information in paper based KPI reports.
• Don't show too much numerical information in electronic dashboards as it's more difficult to read.
• Develop your own scorecards as a consistent method of presentation.

13. Paper and Electronic Reports

In this electronic world, it's often tempting to push all our information online; after all this means we don't need to worry about distribution, geography or what type of computer, tablet or phone our reader has. However, no matter how good an online dashboard is, you can't write notes on it before your management meeting and you can't wave it around in your hand!

In my view, online dashboards are the future, but I don't feel they are ever going to replace the humble paper based report.

A paper based report is NOT a printout of your dashboard

Electronic dashboards offer a world of new possibilities for KPI reporting, with interactive drilldowns and automatic alerting but they are very different to a paper equivalent. Both fulfil different goals for data management.

• Electronic reports can be resized to suit a screen size, paper reports are fixed.
• Data is hard to follow and read on a screen, but easy on paper.
• You can't easily annotate or make notes on electronic charts.
• A screen resolution is 72dpi, but a printer is normally at least 300dpi. As a result, printing charts directly from a screen results is hard to read, poor quality chart text especially on axis labels and values.
• 
  

A Typical Example

To illustrate the approach of both paper based report and online dashboard reports complementing each other, here are some KPI dashboard reporting examples.



This particular example is an overview, containing data from support, finance and sales management dashboards. Each of the charts is interactive and designed to communicate our chosen message. You can drill into charts and also see values by hovering over points. This business kpi dashboard makes the most of its online platform.

However we also produce a paper based (PDF) version of this dashboard. Each dashboard item (chart, pie chart etc) has its own page in the report and not only includes the charts or visual indicator but also a scorecard for each dashboard item plus a data summary.

One page of eight from the paper based reports to complement our dashboard

Notes and Explanations

Sometimes our reports can easily unintentionally mislead, so it may be worth providing some form of reference notes. For example, say our departmental costs are extraordinary high this month because we sent everyone in the department on a training course. The hope is that this will boost productivity in future months. Adding notes or annotations to your reports will help outline planned or extraordinary events that otherwise would cause the reader to be misled by what they see.

About the Author

Johnathan Briggs started his first business when he was just 21 years old.  A decade later Johnathan had grown the business to a multi-million pound operation with blue chip clients across the world and a reputation for excellence.  Key to the growth of the company was Johnathan's focus on management reporting, measuring performance metrics and constant improvement.

Following the acquisition of his first business by a UK-based PLC, Johnathan became a sought-after and accomplished business mentor helping companies not only in Scotland but across the globe.  His business experience and passion for improvement, innovation and excellence have ensured that he is always in demand.

Johnathan is now a consultant at the leading online Management Dashboard company "Target Dashboard".  He states, "Managing business, people and processes has always been a big challenge, and is often the difference between success and failure. Target Dashboard is a concept I just love, an online KPI dashboard app that is so simple that managers can use it and be up and running in minutes".

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