![\"Elegant\"](https:\/\/www.kaushik.net\/avinash\/wp-content\/uploads\/2014\/02\/elegant.jpg\")
There are three elements to our “big data” efforts, or unhyped normal data efforts: Data Collection, Data Reporting, and Data Analysis.<\/p>\nThere are three elements to our “big data” efforts, or unhyped normal data efforts: Data Collection, Data Reporting, and Data Analysis.<\/p>\n
(More on that here: DC-DR-DA: A Simple Framework For Smarter Decisions<\/a> .)<\/p>\n We are all aware that the best companies in the world have an optimal DC-DR-DA allocation<\/a> when it comes to time\/money\/people: 15%-20%-65%.<\/p>\n All well and good.<\/p>\n But there is one crucial part we often don’t invest in sufficiently. The last mile. Data presentation! The actual output that is almost singularly responsible for driving the change we want in our organizations. The thing that is the difference between an organization that data pukes and the one that influences actions based on understandable insights.<\/p>\n I believe we should present our data as effectively as possible in order to first build our credibility, second to set ourselves apart from everyone else who can present complicated graphs\/charts\/tables, and third allow our leadership teams to understand the singular point we are trying to make so that the discussion moves off data very quickly and on to what to with the insights.<\/p>\n A vast majority of occasions where data is presented (reports, executive dashboards, conference presentations, or just plain here’s a automated emailed thingy from Google Analytics<\/em> ) end up being abject failures because most of the discussion is still about the data. And if you are sitting in a Nth level tactical meeting, that is ok. But if the occasion is a strategic discussion, any occasion about taking action on data, then you need to get off data as fast as you can.<\/p>\n It is hard to do. After all you spent so much time on collection, reporting and analysis. You want to show them all data stuff<\/em> and how much you worked and how cool your technique was. But trust me, it is better for your career (and, this is a lot less important, but much better for your company\/audience :)) to get really, really good at data presentation.<\/p>\n This post shares eight before and after examples that illustrate seven data presentation tips that I hope will inspire you to look at your report\/dashboard\/PowerPoint slide in a new light. We will look at some simple errors, and some much more subtle ones that end up limiting our ability to communicate effectively with data.<\/p>\n Here’s a quick summary:<\/p>\n #1. Don’t be sloppy. Your data presentation is your brand. <\/a> <\/p>\n #2. Bring insane focus, and simplify. <\/a> <\/p>\n #3. Calibrate data altitude optimally. <\/a> <\/p>\n #4. Eliminate distractions, make data the hero! <\/a> <\/p>\n #5. Lines, bars, pies… stress… choose the best-fit. <\/a> <\/p>\n #6. Consolidate data, be as honest as you can be. <\/a> <\/p>\n #7. Ditch the text, visualize the story. <\/a> <\/p>\n<\/div>\n We are going to have a lot of fun, and learn some not-so-obvious lessons.<\/p>\n It’s not the ink, it’s the think<\/em>.<\/font><\/strong><\/p>\n An important point first.<\/p>\n This post is not about tufte’ing your work. It is not a post about expressing your inner Excel geek with the most advanced remastered sparklines or conditional scatter plots. Advanced, sophisticated visualizations are important. But I find that so many times people focus on the ink<\/em> and not the think<\/em>. Hence all the insights-free data visualizations floating around the web that are totally value-deficient, even as they are pretty.<\/p>\n In this post I simply want you to focus on the think<\/em> and not the ink<\/em>. What was the error in thinking? How can you ensure you never make that error? Then, go express your inner visualization beast. :)<\/p>\n [My inspiration for a focus on the think: Bob Mankoff<\/a>]<\/p>\n <\/a>Lesson 1: Don’t be sloppy. Your data presentation is your brand.<\/font><\/strong><\/p>\n This graph is from a McKinsey article.<\/p>\n It actually shows very interesting data. The article is a bit dry, but valuable.<\/p>\n Yet, I could not get over how sloppy the graph was. For me, and perhaps for others, the sloppiness made the data appear to be an amateurish effort (surprising, given the source) and took away from the deservedly mighty McKinsey brand.<\/p>\n Can you see what the problems are?<\/p>\n The first problem is that the title is weirdly placed. Then the y-axis legend is even more weirdly placed. The most important part seems to be to get the names of the company, gigantic, over two lines and distracting.<\/p>\n Finally, this is picky, but why is most of the x-axis yearly and then suddenly just until Q2, 2013? And if it is only two quarters of data, why is it taking up the same distance as represented by one year?<\/p>\n Surprisingly sloppy from McKinsey, right?<\/p>\n Watch out for these errors. People in the room (in a small room or a board room or a conference auditorium) will know a lot less about the data than you will, their first impression, and often the lasting impression, might be how clean your data presentation is.<\/p>\n Even without access to the raw data (let’s say I’m a busy McKinsey blog post writer), you can make a couple of simple changes to the graph to make it cleaner and less sloppy…<\/p>\n Clean up the title, rephrase it.<\/p>\n Move the y-axis description to the right place.<\/p>\n Make the source attribution much smaller. If the data is good, people will seek it out. If the data is stinky, no one cares. Either way, why make it intrusive?<\/p>\n Scroll back up. Then down. Much cleaner, right? 30 seconds of work.<\/p>\n If I had the raw data, I would also fix the x-axis and representation of the partial 2013 data. That is still bothering me. But at least you can see what 30 seconds can do.<\/p>\n When it comes to your work, take the 30 seconds.<\/p>\n [PS: The data in the graph is cool, you can see my brief analysis on my LinkedIn Influencer Channel: Email Still Rocks! Social, Surprisingly, Stinks!<\/a>]<\/p>\n <\/a>Lesson 2: Bring insane focus, and simplify.<\/font><\/strong><\/p>\n I’m sure you’ve either seen someone present a slide that looks like, or you’ve created a slide\/executive dashboard like this one. Or, both.<\/p>\n : )<\/p>\n Before you scroll any further, what errors, subtle or obvious, do you see? Don’t rush. Give it some thought.<\/p>\n [Minor Rant: Never, ever, never obsess this much about CPCs. Yes, cost per click is metric. But if you had to obsess about something, obsess about the value delivered to the business. You will never obsess about the cost per trade of your E-Trade portfolio, right? It could go down from $10 per trade to $1, and you could have completely gone bankrupt as a result of your trades. So, don’t obsess about CPC. Focus on Economic Value<\/a> from your search advertising. Focus on Profit<\/a> from your search advertising. Focus on the outcome. As long as you make a profit, does it matter if your CPC is $1 or $200? And would it matter if your CPC went from $200 to $1 if you were making no profit?]<\/p>\n The metric CPC aside, we do present data like this all the time.<\/p>\n The first challenge is that there is too much of it. We have actuals and we have the YOY change. Then we have it for the company and its category. Finally, we have it segmented into desktop and mobile and as if that was not joyous enough, further segmented into Brand and Non-Brand.<\/p>\n As if that was not enough, the data presentation itself is a bit uninspired.<\/p>\n We can quickly fix it though.<\/p>\n First pick one primary thing to focus on. When you design dashboards this is absolutely critical.<\/p>\n In this case, I believe, the most interesting thing is the YOY change. I bring it center stage, and make the actual CPC as small as I possibly can (in case someone wants it that desperately).<\/p>\n Next I create a simpler data presentation, God bless Excel, by creating two big clusters next to each other. Now it’s just a matter of two similar columns that we can distinguish with the use of color.<\/p>\n Here’s the result…<\/p>\n Again, something very quick you can do. (I’m sure like me you have a favorite custom font you use to make your presentations really yours.)<\/p>\n The orange and purple are easy on the eyes, and distinguish the two clusters nicely. The size of the font used makes the things that should stand out, stand out easily.<\/p>\n Notice because the company performance is all in one row, it is much easier to see that their CPC year-over-year change is less than the category (something harder to see in the original version).<\/p>\n Bring insane focus to your data presentation. If you can, focus on a singular metric for each module\/slide\/element. Then present the data as simply as you possibly can. And often, you don’t need to go very far from the defaults in Excel – though you are welcome to use any software you want.<\/p>\n <\/a>Lesson 3: Calibrate data altitude optimally.<\/font><\/strong><\/p>\n Here’s a more subtle error.<\/p>\n Ignore the ugly graph and the terribly formatted axis, time periods used, etc. All simple fixes.<\/p>\n Look at the text under the graph. Do you see the problem? Don’t scroll any further. Look at it again, see the mistake made?<\/p>\n It is not completely obvious, but the Analyst is expecting that in the very short time the leadership team has to look at this data, that they’ll also be clever enough to do the math for each row, commit it to memory and then compare all four rows and figure out which video is performing better.<\/p>\n Terrible error in judgment. The altitude is all over the place!<\/p>\n You are the Analyst. You do the math. Then make the hard decisions and figure out how to present data as effectively as you possibly can.<\/p>\n In this case I had to decide what the key point was (this is the think<\/em> part). I believe it was that using advertising to drive views of a video fueled organic views as well.<\/p>\n That gave me the anchor, paid views. Then it was simply a matter of figuring out the best way to present the data. I decided to use an index of 100. All that’s left now is to do the math in Excel and paste it on to the dashboard…<\/p>\n The recipient can get to the insight really fast because there is less data (fewer words and clutter), it is well thought out, and we can move to asking hard questions about performance.<\/p>\n What the heck happened with Video B? And OMG what is up with Video D???<\/p>\n That is what you want, shift the discussion from the data to what happened and what to do now.<\/p>\n Bonus: As the smart Analyst that you are, at this point you’ll realized Earned and Paid Views don’t tell the full story. So you’ll change the table to Total Views and % Earned. You would not have known that’s what you needed if you’d stuck with your original textual version! The value of focus and think.<\/em><\/p>\n <\/a>Lesson 4: Eliminate distractions, make data the hero!<\/font><\/strong><\/p>\n Raise your hand if you’ve not created a slide like the one below for your presentation. Come on!<\/p>\n My hand is raised.<\/p>\n We have all done this.<\/p>\n And it is so silly.<\/p>\n We take the most interesting part, the data, and surround it with clutter that only makes it harder to understand what the point is. The data is the hero, what is the need to have the arrows and the box and the descriptions? Is there any need for the useless stock photos (and what is up with the magnifying glass to represent research, who does that?)? And why repeat “use online sources,” is that not obvious in the awfully crafted title?<\/p>\n Look at the image for a moment. Don’t scroll. Stop. Really. Don’t scroll. How would you decrapify this slide?<\/p>\n Got an answer? Ok, now scroll.<\/p>\n Share your decrapified version via comments below.<\/p>\n My process was to simplify the title to something more direct and easy to understand. Then use three different bars to represent each stage of the process, and to fill each up to represent the percentages. Finally, I’m slightly allergic to terms like awareness and consideration. They are too generic, they encompass too much. So I took the direct route, just wrote down what each bar actually represents.<\/p>\n You can use different colors, mix to suit your own taste. Red in my case is to make the online usage stand out on a very large screen.<\/p>\n I’d experimented with having a break in the gray x-axis (yes, I worry about those things!), it looked nicer. But visually it ended up representing a break, rather than the continuity that each stage represents. Hence the single line you see above.<\/p>\n If you spend sometime on the think<\/em> , it is so much easier to decrapify the data presentation to focus on the most essential element and make data the hero (again, so that you can get off the data very quickly and have a discussion about what the business should do).<\/p>\n <\/a>Lesson 5: Lines, bars, pies… stress… choose the best-fit.<\/font><\/strong><\/p>\n If you are a student of the Market Motive web analytics master certification course<\/a>, you’ll note my love for segmented trends rather than snapshots in time when it comes to data presentation.<\/p>\n Trends are often better at delivering deeper insights. And because all data in aggregate is crap<\/a>, segmented trends are even better!<\/p>\n But, as all smart analysts know, often is not always.<\/p>\n Here’s a great example… The dashboard module shows how American’s consume media, and how that behavior has changed over the last four years.<\/p>\n Please take a minute and reflect on the graph. Do you love it? Does it communicate the change optimally?<\/p>\n You’ll agree, the graph is nice and clean. It is easy to understand what is going on. Sure we can line up the numbers on the right correctly, but that is a minor point.<\/p>\n As a Digital Marketing Evangelist, you can imagine I love the data. : ) I was not sure that I love the line graph.<\/p>\n I felt it would take too long to understand just how much things had changed. People would spend too much time trying to understand the graph. And even then, at a deep gut level, not internalize it (even though to you perhaps it is utterly obvious).<\/p>\n My decision was to eliminate the trend. Except for TV, the trends adds almost no value (and even for TV just a little). This allowed me to switch the x-axis to each media channel, they were the heroes here. And finally, switch to a bar graph.<\/p>\n Here’s the result….<\/p>\n I believe this version shows the change much more starkly and since you can look at one channel at a time, you can absorb the change much, much faster than with the line graph.<\/p>\n While with the line graph you could see people spent more time with digital than with TV in 2013. The big rise in digital consumption vs. 2010 is much more obvious now. And while TV is physically from Digital in the above picture, you can easily see that one is much higher than the other.<\/p>\n Remember, often is not always. Question how you’ve always done things. Even question your teacher who might love segmented trended graphs! : )<\/p>\n Understand who your audience is, think<\/em> about the point you are trying to make with your analysis, and then use the best-fit data presentation method.<\/p>\n <\/a>Lesson 6: Consolidate data, be as honest as you can be.<\/font><\/strong><\/p>\n This example comes from a presentation. The data was spread over two slides. Notice how nicely it is presented.<\/p>\n The first slide showed the desktop and laptop performance for search traffic for puppies (real data below, just not that category!)…<\/p>\n It is easy to see how puppies are doing in context of the average number of searches for land animals and sea animals. Put another way, company performance compared to two benchmarks.<\/p>\n The second slide illustrated the mobile search performance for puppies, and compared it to the same categories…<\/p>\n Both sets of data presented simply. You cannot misunderstand it.<\/p>\n So, what is the problem. Look at the graph above carefully. Then scroll up a little more, look at the first one. Now scroll back down.<\/p>\n See the problem?<\/p>\n One obvious problem is, why spread the data on to two different slides? Most people are terrible at keeping track of things as they jump slides\/pages.<\/p>\n The second problem is more subtle.<\/p>\n The graphs make it seem like there are two similar sized problems to deal with for us as PuppiesRUs Inc. But that is not really true. Look at the y-axis.<\/p>\n Perhaps, for a good reason, we want the company to believe that they are similar sized problems because our company sucks at mobile and we want to light a sense of urgency under our collective butts.<\/p>\n I believe as an Analyst we should be as honest as possible in these cases. (I’m NOT implying that there was a deliberate attempt to not be honest above.) We should show the data in as honest a way as possible, we should be as objective as possible.<\/p>\n I simply took the data in the two graphs and put it on to one graph, same bar graph, and fixed the title to make the presentation simpler (I hate long complicated titles).<\/p>\n In an attempt to pay an homage to the importance of mobile, changed the color to red…<\/p>\n To our leadership team, the recipient of our presentation, it is really clear how we are performing overall and in mobile.<\/p>\n It is also clear that desktop plus tablet, blue, is the most important area of focus. We have to keep the pedal to the metal when it comes to that. But that mobile is also an important area deserving some dedicated focus.<\/p>\n There is no chance that they will inadvertently think the size of both the opportunities is the same.<\/p>\n An effective presentation of data by 1. consolidating it and 2. having it play off the same y-axis.<\/p>\n <\/a>Lesson 7: Ditch the text, visualize the story.<\/font><\/strong><\/p>\n Often we hear that data is overwhelming or that graphs are evil or that tables suck or… well, I’m sure you’ve heard it all.<\/p>\n Our response to that is to try and “simplify the story” by eliminating all that and just writing the insights in text with a big summary number.<\/p>\n That strategy does work some times. More often than not you end up with something super-ugly and value-deficient like this…<\/p>\n Imagine yourself to be sitting in the audience and trying to internalize everything that’s going on here! I’m sure someone is going to walk you through it. But still. Do you think there is any chance you can grasp the multiple agendas at play above?<\/p>\n I seriously doubt it. Scroll back up. Look at it!<\/p>\n Even if you only have two minutes, all I had in this case, it is pretty easy to fix the above textual representation and make it much easier to understand what is going on.<\/p>\n First, get your custom font. Ok, kidding.<\/p>\n First, think<\/em> of what the key point is and replace the long red-book ended title with it. In this case: Search Opportunity.<\/p>\n Then draw a bar in PowerPoint, eyeball the size (no, really, don’t even go in Excel to create the graph, no one is going to notice!), and fill in the sub-components.<\/p>\n For data you can’t find an obvious home for, use call-outs.<\/p>\n Two minutes later…<\/p>\n So much easier to see that story is about how many people search for our company topics and that weight management and monitors are the most interesting. In this case we have the data that can fill out rest of the bar, but we want the leadership team\/audience to focus on just two and those are the ones you see above.<\/p>\n It is less obvious how to illustrate the mobile growth. Two more bars? Perhaps a heat-map showing high and low? Nah! Just add two call-outs and you are done!<\/p>\n When the data’s end state is a PowerPoint\/Keynote presentation, use the fade transition (all other transitions are evil) and bring one piece of data at a time up on the screen. It will look beautiful and the audience with stay with you as you narrate other insights you know that are not represented on the slide. [A style of presentation you should use every time you present anything.]<\/p>\n Here’s another example of eliminating text, reducing complexity, focusing the the key point and visualizing data simply to get off the data quickly and discuss actions.<\/p>\n Pause. Look at the example below. What is done right or done erroneously? If you had to improve on the power of communication for this example, what would you do?<\/p>\n Pause. Really think about it. Got it? Now scroll.<\/p>\n The first simple mistake you likely won’t make as an analyst is to use two different things to represent the same number. For example, either stick to the dollars or use the percentage. This might not seem like a big deal in isolation, but every little bit like this takes a tiny bit of your credibility away and it causes the audience to have to shift their minds a little. Over a number of these types of mistakes in your dashboard or your presentation take away 0.25% here and 0.5% there and 1% somewhere else. Taken together, you lose 30%. Why dig that hole for yourself to have to climb out of?<\/p>\n The second simple mistake, obvious in hindsight I’m sure, is that there is simply too much text. Why not simplify the data presentation to make it boom (!) impactful right away?<\/p>\n I did like the map, but it was intrusive. So my first act was to take the map, fade it out (use a white transparency, 13%). It is there, but it is not in the way.<\/p>\n Then I did not like the numbers, they don’t add any value. Just throw in two simple bars (standard shape in PowerPoint, no Excel necessary), and add a touch of color to show targeting efficiency of TV and Radio. Finally add the bridging text and use the brace (use the little yellow handle to drag the brace so it is aligned) to show how well or badly each media channel is doing.<\/p>\n Red is bad, blue is good….<\/p>\n Scroll back up. Then back down. Then up. Then down. (Think of the Old Spice ad! :)<\/p>\n The presentation is simpler. Even without reading anything you can get a sense for what is good and bad. The questions will come fast and loose: Why do we do TV? And if there is 75% leakage, is it still worth it? What is the optimal media-mix for our efforts?<\/p>\n We believe that summarizing our findings in text is the solution. We believe tables and graphs add complexity. We could not be further from the truth.<\/p>\n Closing Thoughts.<\/font><\/strong><\/p>\n It’s not the ink, it’s the think.<\/p>\n It takes a tiny amount of time to really look at the data you are presenting, really think about what you are trying to say and identify the singular point. Once you know that, it is only a couple of minutes of work to decrapify the report\/dashboard\/slide\/spreadsheet and ensure we are presenting data as simply as possible using the most optimal visual.<\/p>\n You worked so hard to collect the data. Then invested all that time and energy in reporting it. Finally, really dug deep, did the analysis. Don’t stop there. Spend time optimizing the end product. Your goal: Get of the data as fast as you can, switch to the discussion of actions.<\/p>\n Victory, I promise, will be yours!<\/p>\n Bonus:<\/strong> Speaking of data visualization, more inspiration for you: <\/p>\n <\/p>\n As always, it is your turn now.<\/p>\n Which one of the eight examples above is your favorite? And the least? Would you have taken a radically different approach on any one of them? Care to share your version? What are your go to filters for taking something complicated and making it simple? What is your favorite annoying data presentation method? Is there a visualization strategy that consistently helps you switch the discussion from talking about the data to talking about what to do with the insights?<\/p>\n Please share your insights, recommendations, critique, alternatives and complaints via comments.<\/p>\n Thank you.<\/p>\n","protected":false},"excerpt":{"rendered":" DC-DR-DA: A Simple Framework For Smarter Decisions .) 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<\/p>\n\n 1. Data Visualization Inspiration: Analysis To Insights To Action, Faster!<\/a>
\n 2. Great Storytelling With Data: Visualize Simply And Focus Obsessively<\/a> \n<\/div>\n