Analytics professionals need to be communicators. Just being technically proficient is longer enough. It is not enough to slap a report or dashboard together on the go. Rather, we have the responsibility to help the business get information out of their data. This is especially true as data volumes continue to grow. I wrote about this in a recent blog post.
The question though is how to best do this. Earlier this week, I came across an excellent blog post by web analytics guru Avinash Kaushik. His November 5th post provides a detailed example of how to convert a complex data set into a compelling story. I highly encourage you to spend some time reading this inspiring blog post.
It’s that time of the year. Millions of kids are excited about hunting for Easter Eggs. Why not do the same here on the blog? Below are three charts. All of them are colored according to the season. But there are some problems with each one of the charts. Can spot them? Scroll down to see some comments….
Stacked line charts are a great and yet simple tool. Here is why. We often run into a situation where we need to analyze data with different units of measure. Think about a classic but yet simple situation: Vital company data such as revenue, margin % and expenses is used to obtain insights about the past and current performance . One could dismiss this as an easy task and simply review a standard table. But raw data is really tough to analyze. Detecting trends and patterns quickly is almost impossible. Especially with regular data sets that span multiple organizational units
Raw data is hard to analyze. Even simple data sets as this one here.
The other option would be to stick the data into a traditional line chart. But this won’t work in many cases for two obvious reasons:
The units of measure are different (Revenue ($), Margin (%), Headcount (#), Volume (#), etc..)
The units of measure have large differences (example: Revenue is measured in millions, travel cost in thousands)
Both cases result in a pretty much useless chart. You can see a fine example right below:
An almost useless chart – What are the margins again?
For data sets containing just two different units of measure, we could alternatively consider a dual axis graph. But I personally find them distracting and many casual users get confused. This is where stacked line charts come in handy.
The power of stacked line charts
Stacked line charts are basically a bunch of line charts that we stack. Why is that useful? Well, take a look:
A stacked line chart – A better option
The stacked line charts allows us to easily identify and compare the trends and patterns in our data. Using this stack is fairly easy. We just have to keep in mind that the units of measure or the scale is different in each one of the line charts. But that should be obvious.
Your analysis
Generating these stacked line charts is really easy with personal analytics tools like Cognos Insight. Spreadsheets typically required us to generate various different charts and to align them manually.
If you haven’t use them before, get started today! Stacked line charts are very powerful, yet easy to use.
The other day I reviewed a dashboard. It looked great. But there was a chart on the bottom that just did not make any sense. It was way too long and stretched out. As a result, it was very difficult to use it appropriately. And that reminded me: We have to watch out for the chart aspect ratio.
The basic idea
Wikipedia defines the aspect ratio as follows: “The aspect ratio of an image describes the proportional relationship between its width and its height.” It’s as simple as that. We get confronted with the aspect ration when we purchase a TV or computer monitor or when we work with photographs. Does the aspect ratio matter? Oh, yeah it does! Take a look at the two photographs below. The first one uses the common HD 16:9 ratio. I cropped the second one down to a square format (1:1). Do you see the difference in the overall impression of the photo?
16:9 (HD) Aspect Ratio: Can you feel the wide and open ocean?Square Aspect Ratio: Not that great. The boat has too much visual weight and the ocean does not seem vast and wide.
Your charts
The aspect ratio does matter for charts as well. We have to watch out for that when we create reports and dashboards or when we perform ad-hoc analysis. Not every chart aspect ratio works equally well. Take a look at the two examples below. Both of these charts have problems:
It is difficult to make sense of the data. It is too flat.The peaks are very pronounced.
The first chart is definitely too flat – it is very difficult to analyze it. The second one is probably a bit too dense. The peaks are extremely pronounced and it would be easy to come to wrong conclusions.
A better approach
What is the idea aspect ratio then? Hard to say. It is typically a good idea to use a ratio that is wider than it is tall (2:1 or something like that). But it depends on what you want to show. From my point of view, it makes sense to experiment a little bit. I have noticed that some visualization experts have issues advice but I have found it to be very academic and hard to implement. To stick with the example from above, I did re-size the graph a bit and finally settled on this chart aspect ratio:
This aspect ratio seems to work best for this data
Your dashboards & reports
Pay attention to the chart aspect ratio. Only because there is some space left in a dashboard does not mean we can or should stick a certain graph in there. The chart aspect ratio does matter quite a bit as we have just seen in these simple examples. Also, try experimenting with different chart aspect ratios when you perform analysis. Resizing charts with personal analytics tools such as Cognos Insight is really simple.
Cognos User Groups are quickly gaining a lot of interest from IBM customers around the globe. These groups provide users with the ability to learn, to connect and to share experiences. A few weeks ago, I had the honor to meet with one of North America’s largest Cognos User Groups – the ‘Groupe d’utilisateurs Cognos du Quebec‘. The president of this group, Steve Veilleux and I sat down for a quick interview.
Christoph: What is the purpose and mission of your Cognos user group?
Steve:The « Groupe d’utilisateurs Cognos du Quebec »has a clear mission. We primarily want to provide the Quebec BI community with networking opportunities around IBM Cognos technologies and BI concepts. We typically do that by organizing two full-day events per year (in Montreal and Quebec City). Our members help each other to gain new knowledge they can apply at work. We also share the latest news about IBM Cognos. Members frequently share case studies as well.
Christoph: Is this a new initiative or does this user group have a longer history?
Steve:I am proud to say that our Cognos user group has a long history in the IBM Cognos world. We were founded over 15 years ago! I personally joined the group in 2002 and have played the role of the president since 2007.
Christoph: How many members do you have and how do you communicate with each other?
Steve:We currently have around 450 people. Our meetings typically attract around 100 attendees. To communicate with each other, we established a group on LinkedIn. Members and non-members can also use our web site: www.gucquebec.org . We also publish a newsletter and share the results from our different meetings.
Christoph: Who participates in the user group?
Steve:We have a well-balanced mix of members. The majority are IBM Cognos customers or prospects from the business or the IT side. There are also consultants and some IBM employees.
Christoph: What are the benefits of being a member in a Cognos user group?
Steve:A user group is definitely very beneficial for its members. I personally see three main benefits:
The ability to stay informed about IBM Cognos products
The ability to networking with other business analytics professionals
Privileged contact with IBM employees
Christoph: What is your relationship with IBM through the group?
Steve:We have a very close relationship with IBM. They actually sponsor us to a certain degree and provide us with resources for our meetings. We typically invite speakers to help us understand the latest news about the technology and services.
Christoph: There are some regions that do not have a user group. What advice would you have for IBM Cognos sponsors and users who are thinking about forming or joining a similar user group?
Steve:My clear advice: Start or join a Cognos user group! First of all, you need to find a few like-minded people. Once you have made up your mind, make sure to share responsibilities. A successful user group requires some time and effort. People need to provide some help with organising meetings, managing contact lists, finding and selecting presentation topics and speakers, reserving the facilities, etc.. Our “Groupe d’utilisateurs Cognos du Quebec” is managed by an executive committee for that purpose. Once the user group is up and running I recommend to take care of a few things:
Listen to your user community. If possible, try to find conference topics they ask for (we frequently conduct a survey).
Avoid consultant-only presentations. We strongly prefer customer presentations and we think this is one a the reason why our Cognos user group is so successful.
Encourage your members to actively participate. It can be a challenge to find and convince customer “champions” to prepare materials and to present them. To encourage them we offer free registrations to our meetings and also offer them a gift for their effort.
Work with IBM. We have had great IBM people present at our meetings. Exactly like you, Christoph!
Charge a registration fee for your meetings. Not only does this help cover fixed expenses (room, audio/video, meals) but it also helps us get some prestigious speakers. We were able to attract influential experts like Wayne Eckerson, Shawn Rogers, Brett Knowles, Philippe Nieuwbourg, Naomi Robbins and some others. Interest in our events has significantly increased since we started bringing in these prestigious speakers (+40%).
Try to have fun and share the good news! This is really important! Once you start having fun and people get value out of the community, word of mouth will bring in new members.
Christoph: Tell me about your career in Performance Management and Cognos
Steve Veilleux
Steve:I started my career 17 years ago at Groupe Canam Inc.. Until 2000, I was involved in payroll, manufacturing and financials systems development. With all the knowledge I had gained on those systems at Canam Group Inc, I started a Data Warehouse project in 2000. And for the past 11 years I was thus responsible for the development of the BI environment. Can you believe it – I started with Cognos 6.6 back in 2000. I guess that makes me an “early adopter”. I have hands-on experience with almost all versions between Cognos 6.6 and IBM Cognos 10.1. During those years I also participated in Customer Reference and IBM Cognos Beta Programs. You can even find my profile on the IBM website. I recently decided to make a major change in my career by join Keyrus Canada as a Business Intelligence Consultant.
Each indicator must have a strong correlation to your ability to effect change
In my last post I laid out 3 practical and compelling questions in developing your dashboarding program:
How should my company be using a dashboard(s)?
What is the basic process for choosing my KPI’s?
What are some common mistakes I should avoid in my dashboarding?
Today I conclude with Questions 2 and 3.
Selection of KPI’s
KPI’s are dictated by the strategy of each business against the backdrop of standards or benchmarks for its industry, so every dashboard is different. Your KPI’s are singular to you and your business. While you can look to examples for general guidance, you need to work through the process of defining KPI’s for your own business.
These questions may help you start your KPI identification and selection process:
At what level of responsibility is the dashboard being used?
What are the strategies and objectives that are driving the data requirements?
What data provide the best indicators of performance for these requirements?
How can this data be portrayed to maximize readability and minimize response time?
What is the strength of the correlation between the data and your ability to influence change?
The first two questions presume that you have already completed other required steps, such as developing a strategic plan and defining the related goals and objectives. Data points floating against dark space are meaningless. They must be oriented against your goals and industry/competitor benchmarks. The last three questions address the qualitative aspects of KPI’s.
Perhaps the most basic consideration is reflected in the last question. Each indicator must have a strong correlation to your ability to effect change. Stated more simply, the whole purpose of dashboarding is built on the assumption that you have the ability to quickly influence outcomes as you respond to information from key indicators.
For example, daily magazine advertising dollars spent is probably meaningless because display advertising doesn’t move sales on a daily basis and the lead time to place such ad sales is at least 6 months. You lose on both counts – sales and costs.
Common Mistakes in Dashboarding
These are some of the most common and harmful mistakes in dashboarding:
Overloading the dashboard – This is the most common mistake. Getting the most from the least is your goal. Loading every metric about your company onto a dashboard will only confuse and delay your response; equals damage to the company.
Expecting too much – Dashboarding has a very specific purpose and value. It does not replace regular reporting. Don’t try to manage your business entirely from the dashboard. This will push you to put too much onto it and you will tend to lose sight of longer term trends.
Misreading the data – You can minimize the risk of misreading data in the KPI definition process. Choose data that is easy to interpret and consistently reliable.
Responding incorrectly – Lives have been lost more than once from a pilot pulling up the nose when the warning system is telling him to increase altitude. He should have first put the nose down for speed to create lift needed for altitude. He thought “up,” pulled the stick and stalled the plane. Know how you are going to respond to an indicator before going live.
Conclusion
There are books, classes, and careers dedicated to the practice of dashboarding. It is a very important business practice and can become an invaluable business tool to make your life easier and your business more successful. Spend the time needed to do it right.
About the author of this post:
Mike Duncan is Partner and co-founder of Bizzeness, LLC. Mike began his career with KPMG and Deloitte. He has been a business owner and advisor for over 30 years serving over 300 businesses in various capacities. Mike focuses on SMB’s with concept development, business modeling, start-up, market adaption, strategy and succession. Mike lives in the Kansas City area. You can contact Mike at mike@bizzeness.com.
Your dashboard should provide the least amount of the most critical data
In a previous post I discussed the art of dashboarding at a very fundamental level. That post sparked enough interest that I wanted to follow with more discussion about the practical aspects of dashboarding.
Here are three of the most compelling practical questions on the subject:
How should my company be using a dashboard(s)?
What is the basic process for choosing my KPI’s?
What are some common mistakes I should avoid in my dashboarding?
Dashboarding in Your Organization
You have probably seen a view of mission control during a space shuttle mission. There is a large screen on the wall tracking the most basic information about the shuttle – where it is, its projected path on the current trajectory, speed, and other basics. That is Houston’s dashboard.
Dozens of mission specialists are seated around the large screen viewing their own small screens – their own dashboards. Each specialist has an area of responsibility, so each has his/her own dashboard, providing real time data indicating the performance of the key systems for their area of responsibility. For example, the APU specialist probably has a screen showing the amount of power from and condition of each APU – auxiliary power unit.
Mission Control in Houston provides a comprehensive example for your own dashboarding program. The contents and use of each dashboard is determined by the goals and objectives of the user’s area of responsibility – from the big screen on the wall (responsible for mission success) to the screens on each person’s desk (e.g., responsible for APU’s).
Each business has a unique dashboard specific to its objectives and industry, and each critical function of the business has its own dashboard specific to its area of responsibility. The CEO watches the entire business entity, the CFO watches the financial systems, the COO watches operations, and so on. For small and medium size businesses (SMB), the business owner usually gets the privilege of watching all of these areas, making their dashboarding program even more important and more challenging.
Breaking down your organization by functions will help in the layout of your dashboarding program. Each dashboard should be designed to provide glance and go information – the least amount of the most critical data for the function. If there are multiple levels of managed responsibility, a cascading dashboard program should be used – multiple dashboards providing KPI’s for each area of responsibility.
Next Time . . .
Check in on my next post as I conclude with Questions 2 and 3, providing some insight into the process of selecting your KPI’s and address some of the most common and damaging mistakes people make in dashboarding.
About the author of this post:
Mike Duncan is Partner and co-founder of Bizzeness, LLC. Mike began his career with KPMG and Deloitte. He has been a business owner and advisor for over 30 years serving over 300 businesses in various capacities. Mike focuses on SMB’s with concept development, business modeling, start-up, market adaption, strategy and succession. Mike lives in the Kansas City area. You can contact Mike at mike@bizzeness.com.
Dashboarding remains one of the most important topics in the Business Analytics area. Most of my clients are actively working on deploying them. Back in January dashboarding was one of the key topics at the Gartner BI Summit. The broad interest in our dashboarding workshops further shows just how important this topic is for companies.
DASHBOARDING FOUNDATION
Business Analytics basically allows us to make better business decisions by providing answers to three key questions:
How am I doing?
Why is that so?
What should I be doing?
Dashboards do a fine job with answering the first question: You quickly assess the current situation, you identify potential opportunities and risks. But to do that effectively, dashboards need to be designed in the proper way:
They require the right mix of information
The information needs to be displayed in a manner that effectively delivers the story
The technology needs to support proper interaction so that the next two questions can be answered.
BIZZENESS
Last week, Google+ recommended an excellent blog post by Mike Duncan from the business advisory firm Bizzeness. Mike provides some simple but very effective thoughts about dashboards. I highly recommend reading his short post. There are some great ideas in there that can help you articulate the purpose and value of a dashboard to a broader audience.
Mike and I ended up discussing his post via Twitter and email. I am very happy that he has agreed write two guest posts on this blog (Performance Ideas) next week. The articles will focus on interacting with dashboards, selecting proper KPIs and avoiding some common problems. Make sure to check in on Tuesday of next week or simply subscribe to Performance Ideas via RSS feed or email.
The other day I took some time to review a few chapters of John Medina’s excellent book ‘Brain Rules: 12 Principles for Surviving and Thriving at Work, Home, and School‘. It is a great read. There are a lot of interesting stories and insights that apply to various different aspects of our lives. One chapter in particular is quite relevant for Business Analytics: Rule #10 – Vision trumps all other senses.
THE POWER OF VISION
According to Medina, our brains devote over half of their resources to vision. The nerves between our eyes and our brains are much more powerful than those of our other senses. As a result, pictures allow us to absorb information much quicker and the information also tends to be stickier in our brains. Medina says:”Put simply, the more visual the input becomes, the more likely it is to be recognized – and recalled”.
THE PROBLEM WITH TEXT
Text on the other hand is very inefficient. It takes us longer to recognize information and we are likely to retain less of it. Medina states that each letter is technically a separate picture. When we see words we see tons of little images and our brains have a harder time to process the information. George Bernhard Shaw once said “Words are only postage stamps delivering the object for you to unwrap.”
THE LESSON FOR BUSINESS ANALYTICS
A picture says more than a thousand words
Most of this is common sense, but many of us still choose to ignore these facts. We create long reports with hundreds of columns and numbers. We spend hours analyzing these numbers. And we have a hard time recognizing the important patterns. If we want to follow Medina’s advice, we should visualize our data, instead. This not only speeds up our ability to recognize patterns and dependencies, but it should also help us with retaining the information. The old saying goes “A picture says more than a thousand words”, right?
AN EXPERIMENT
Dashboarding guru Stephen Few created a nice little experiment that shows how true and important this insight is. Take a look at the simple report below. It shows revenue numbers for two regions. Spend about 30 seconds to study the table. Then look away ask yourself what you saw.
What do you see here?
Most people are only able to recall three to four different things from the table. The bigger picture usually remains hidden for a while. Now, take a look at the chart below. This is the same data. What do you see now?
Same information…
Notice the difference? The chart is a lot easier to read and chances are that you are able to retain a lot more information.
THE SIMPLE LESSON
John Medina’s advice can be extremely valuable for all of us. We should strive to move away from pure number and text based reports. Instead we should visualize as much data as possible. But that requires us to spend some time to learn more about charting techniques. There are a lot of different options and not all of them are appropriate for any given set of data. You can find a bunch of valuable tips on this blog to get started. Also, utilize the appropriate Business Analytics platform. Cognos 10 offers over 160 differrent chart types, for example.
So, toss those tables and go visual. Inspect your current repository of reports and think about how you can improve in this area.
Listen to John Medina:
“Professionals everywhere need to know about the incredible inefficiency of text-based information and the incredible effect of images.”
Do you like pies? I do! But not for analyzing data. Pie charts are just too busy and too hard to read in most situations. Yet they are the frequent tool of choice for visualizing the composition of a certain variable. Take a look at this example: I want to find out how total revenue is split between different product categories. The easy choice would be to create the following chart:
A product pie – created with IBM Many Eyes
Personally, I don’t like this! You constantly jump around the different pieces and it is really tough to obtain the overview that we are looking for. Pie charts work for few variables that account for larger pie slices. Another and better option is to use a bar chart. To make it easy for the viewer, I ranked the values in IBM Cognos 10:
Ranked bar chart – much better!
Isn’t this much better? You can quickly identify the best performing products. It is easy to read the individual contribution of each product. But I am not able to see my total revenue amount. Good news – there are different ways to perform this type of part-to-whole analysis
CHASING WATERFALLS
Waterfall charts (sometimes called Progressive Charts) allow us to visualize the composition of the a value along different segments. In plain English: Total revenue can be visualized as a build up of the different individual values of the products. Take a look at the example below. The values are once again ranked:
A classic waterfall chart: Total revenue across products
Notice how quickly you can see the segment revenue along with the total revenue of roughly 540 million. I personally like the clean and uncluttered look. Reading the individual values is a bit harder than in the traditional bar chart. But IBM Cognos 10 allows me to hover over each segment to obtain the actual value. It’s personal taste which chart is more effective. Here you can see both versions side-by-side.
Which chart is your favorite?
Waterfall charts are great for any kind of part-to-whole analysis: revenue/ margin across products, customers, channels. Composition of Profit across the P&L, etc.. There are a few interesting examples on Wikipedia.
THE PARETO CHART
There is yet another great option for displaying this type of data: Pareto Charts. They are are named after the Vilfredo Pareto who proposed the 80/20 principle. This chart simply enriches the bar chart we saw earlier with a cumulative percentage line. Take a look:
The Pareto chart: The cumulative percentage line adds further context
This graph allows us to quickly answer questions such as: Which products create 80% of my total revenue? (roughly everything up to Alpha Bronze). In other words: the pareto chart allows me to identify the most important items. IBM Cognos 10 allows different customization options which I would highly recommend looking at. Hiding one of the axis is not a bad idea, for example. The use of colors could be helpful here to identify the main product categories:
Colors allow the user to identify the main product categories
Waterfall Chart vs Pareto Graph?
Seems like a lot of options, right? Which one is the best? Can’t say. It really depends on the situation. I like all of them. There are slight differences and it depends on the user. Waterfall charts are probably better suited for executive dashboards. Pareto charts are more likely useful for analytical purposes. And the classic bar chart is always is a winner. Try to add these charts to your tool-box! And drop those pies.
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