Amazon.com recently recommended the book Naked Statistics: Stripping Dread from the Data. Since I already knew the author Charles Wheelan from his awesome book Naked Economics: Undressing the Dismal Science (Fully Revised and Updated) I went ahead and bought this one for my Kindle. Great decision – it is one of those books that is fun to read while also adding (hopefully) long-lasting value. To make it short: Business Analytics professionals should read Naked Statistics. We work with data on a daily basis and there is an increasing emphasis on Predictive Analytics. Professionals therefore have a growing need for a decent working knowledge of statistics.
Many people have a hard time with statistics. College and university courses usually throw around a wild mix of scary looking formulas containing lot’s of Greek symbols. It certainly took me a while to make sense of my professor’s scribble. As a result, lot’s of people develop a fear of of this subject. Naked Statistics, however, demonstrates that it is possible to teach a seemingly complex topic in a simple manner. Charles Wheelan provides a journey through some of the most important statistical concepts and he makes it fun and easy to understand.
Naked Statistics covers a broad range of the most fundamental statistical concepts such as median, standard deviation, probability, correlation, regression analysis, central limit theorem and hypothesis testing. Each concept is explained in simple terms. The author also uses a mix of fictitious stories (some of them are funny) and real-life examples to show how things work and why they are relevant. Math is kept to a bare minimum – you will only find a few formulas in the main text. Reading is easy and fun. I was surprised to find that I devoured many chapters late at night in bed (I don’t usually read business books that late).
Naked Statistics is a great read. It provides you with a sound working knowledge of statistics and it actually motivates you to dig deeper (I pulled out one of old text books). For those people who know statistics, this book can help you brush up on some concepts. Analytics professionals might also want to recommend this read to colleagues who start working with predictive analytics and other advanced tools. Students should buy a copy before they attend statistics classes – they will certainly be able to grasp the more advanced subjects more easily. I wish I had had this book back at university. It would have saved me some sleepless nights. Two thumbs up – Charles Wheelan does strip the dread from the data.
Wow. I cannot believe it. It’s been two months since the last post on this blog. Thanks to all of you who reached out to find out why it’s been so quiet here. There is a simple reason. Sometime around New Year, I realised that I was due for a creative break from writing. It’s a ton of fun to run a blog with so many awesome readers. Still, writing got a bit harder in the last quarter of 2012. I decided to take an inventory: 196 posts over 1.5 years. That’s a lot of ink on paper! Blogging should be fun and the decision to take a step back and focus on other things for a while was surprisingly easy. I have used the time to start a few different projects including a new photography blog along with a new posterbook publication.
Is the Performance Ideas blog done? Nope. I will be back in a while. The focus will probably shift a little bit. In my new role at OSIsoft, I focus on real-time data and the according analytics. There are a ton of interesting stories and best practices.
In the meantime, I’d like to invite you to submit guest posts, ideas, inspirations and stories. Stay tuned for updates!
2012 is almost over and I just realized that I have not yet posted a single entry about big data. Clearly a big mistake – right? Let’s see: Software vendors, media and industry analysts are all over the topic. If you listen to some of the messages, it seems that big data will create billions of jobs, solve all problems and will make us happier individuals. Really? Not really – at least in my humble opinion. It rather seems to me that big data fills a number of functions for a select group of people:
It provides analysts with a fresh and fancy-sounding topic
Media have something big to write about
BI companies obtain a ‘fresh’ marketing message
Professionals can have ‘smart’ discussions
Consultants can sell new assessment projects
Big data – really?
I do apologize for sounding so negative. But I have a hard time finding big value in this big data discussion. Please don’t get me wrong – I would be the last person to deny that there is a tremendous amount of value in big data. But it does not deserve the hype. On the contrary, I personally find that the current discussions ignore the fact that most of us do not have the skills to do big data. We need to get the foundation right and make sure that we can tame the ‘small data lion’ before we tackle the big data Gozzilla. Don’t believe me? Consider the following:
Spreadsheets are still the number one data analysis tool in most organizations.
Managers still argue about whose revenue and unit numbers are correct.
Knowledge workers have yet to learn how to make sense of even simple corporate data sets.
3D pie charts are floating around boardrooms.
Companies spend over 6 months collecting and aggregating budgets only to find that a stupid formula mistake messed up the final report
Hardly any professional has ever read a book or attended a course about proper data analysis
Here is the thing: Dealing with big data is a big challenge. It will require a lot more skills than most of us currently have (try finding meaning in gazillion TBs of data using a 3D pie chart!).
A big data problem
Earlier this year, I acquired a 36 megapixel camera. You can take some amazingly gorgeous photos with it. But it comes at a cost. Each photo consumes 65-75MB on my sad hard drive. Vacations now create a big data challenge for me. But guess what: this camera is anything but easy to handle. You have to really slow down and put 100% effort into each and every photo. 36MP have the ability to reveal every single flaw: The slightest camera shake is recorded & exposed. Minimal focus deviations that a small camera would not register, kill an otherwise solid photo. In other words: this big data camera requires big skills. And here is something else: The damn camera won’t help you create awesome photos. No, you still need to learn the basics such as composition, proper lighting etc.. That’s the hard stuff. But let me tell you this: If you know the basics, this big data camera certainly does some magic for you.
Big data – what’s next
Ok. That was my big data rant. I love data and analytics. No doubt – there is a tremendous amount of value we can gain from those new data sources. But let’s not forget that we need to learn the basics first. A Formula 1 driver learned his skills on the cart track. At the same time, there is a lot of information hidden in our ‘small data’ sources such as ERP, CRMs and historians. Let’s take a step back and put things into perspective. Big data is important but not THAT important.
With that: Thank your for following this blog. Happy holidays and see you next year!
December is always an interesting month. Analysts, software companies and journalists post a ton of predictions, reviews and opinions to celebrate the start of the new year. 2012 is not different. Here are a a few posts that I highly recommend reading.
Most influential visualizations
Tableau Software without a doubt knows a lot about data visualization techniques. That’s why I happily viewed one of their new presentations out on Slideshare. It’s called ‘The 5 most influential data visualizations of all time”. Some of the featured visualizations have been discussed by Stephen Few and Edward Tufte, but it’s well worth spending a few minutes reviewing and thinking about how they changed the course of time.
Are you ready for some hilarious reading? Well, here it is. The good folks over at the Simply Statistics blog compiled a number of data visualizations that appeared on Fox News (don’t worry – this is NOT about politics). Most of the featured charts are flawed from a technical point of view, but it turns out that they do an excellent job of communicating the intended message (which can be very different from what the actual data says….). Read with a smile but don’t loose focus on the idea that there is an important message! Most of us strive to produce visualizations, dashboards and reports to provide an accurate portrait of reality. But we can also twist this around and do the opposite: confuse and mislead. You might also want to take a quick look at the comment section of that blog entry. That’s where the post starts getting political.
Nucleus Top Ten Predictions for 2013
Nucleus is one of those research houses that produces very interesting reports. I don’t always agree with the stuff that they write, but it is certainly amongst the most tangible in the industry. Their 2013 predictions don’t disappoint. And guess what – BI is on top of the list. The remaining predictions represent a mixture of different trends – most of which affect analytics to a certain degree. In any case, the free report is well worth a five minute investment. One of my favorite statements is: “It’s time to make sure HP has signed its organ donor card.”You can download the free report from the Nucleus website.
Many of us get really frustrated when business people do not immediately embrace our analytics solutions. But let’s step in their shoes for a moment. Trusting analytics for decision making is leap of faith. Imagine you are a manager who is used to listening to his gut feeling and intuition. We can’t expect that person to immediately embrace the latest and greatest analytics solution. As a matter of fact, data can often be viewed as some scary. Starting to rely on analytics can therefore often feel like the proverbial leap of faith.
Why is that so? When we simplify the feelings that a new analytics user experiences we can identify three major stages.
Reject: Can I trust the data? What am I supposed to do with it?
Accept: I can see the value but I can’t identify the stories
Embrace: This is cool! What else can I do with this?
We as analytics professionals have the duty to help people make that leap of faith. We have to make it easy for them to get from stage 1 to stage 3.
A personal story
About ten years ago, I got really serious about my running and cycling. Instead of just following my gut feeling for developing a training plan, I purchased a heart rate monitor, a cycling power meter and some analytics software.
Stage 1 – Reject: The initial experience was intimidating. Getting everything to work was complicated and there were a ton of data drop-outs. What about the data itself? It did not tell me anything. All I saw was a bunch of colorful charts and nothing else. I was ready to throw the stuff out of the door. It felt like a waste of time.
Stage 2 – Accept: After a few weeks, however, things started to work smoothly and a coach finally helped me understand the charts and taught me how to identify a few weaknesses in my approach. Based on those insights, I tweaked my plan a little bit. It was a positive step forward but I was still waiting for the big impact.
Stage 3 – Embrace: Studyingbooks and consulting with other athletes allowed me to achieve a real break-through. That’s when I finally learned to really rely on the data. Here is an example: Analysis showed that I had trained too hard for over two years. I needed to change my approach and spend more time recovering. It sounded scary: Train slower to race faster? Guess what – it worked! Once I started to back off, I was able to dramatically improve my performance. And that is my personal story of moving from stage 1 (reject) to stage 3 (embrace).
Don’t expect your users to immediately embrace your cool analytics solution. It is a leap of faith. It is your job to help and coach them. Show them how they can apply their data and the associated insights. Also, make sure that you develop solutions that are easy to use and that communicate clearly. Don’t let them alone. Move them along these three stages. It’s your responsibility! You can also find some ideas how to do that on this blog.
Greetings from San Francisco. I am back here to attend Osisoft’s vCampus developer conference. The conference kicked off with a true highlight: Stephen Few delivered one of the keynote presentations. Hopefully, all of you know Stephen and the awesome work he has done over the past years. Today’s presentation was content-rich and also very entertaining. There were a lot of smiling faces in the audience. I will write up a short summary of his messages over the weekend and share it on this blog.
Is this the information age?
Stephen Few started his presentation with a strong statement: We do not live in the information age…..yet. Instead, many of us are drowning in data and we struggle with making sense of the data. Part of the issue is that we are lacking ‘data-sensemaking’ skills. To highlight this point, Stephen Few showed a video. I had never seen it before. It’s funny but there is a strong message behind it: we do not understand how to deliver information properly.
Those concentric circles
Does your organization have a ‘concentric circle’ problem? I certainly know a lot of them. It’s time to change that. Take some time to evaluate whether your reports and dashboards are able to deliver real information.
Check back here in the next few days for a summary of Stephen Few’s presentation.
Some of you might have noticed that the posting frequency on this blog has decreased a bit. I have been traveling more than ever before. This past Saturday, I returned from a 15 day business trip to San Francisco. As tough as traveling sometimes is, it does provide you with some quiet time for reading. And that’s exactly what I did on those 13 hour flights. Right before I left, Amazon.com had posted a number of fantastic new business books in their monthly 3.99 Kindle promotion section. There are a bunch of really good books this month. One stood out.
“How will you measure your life” is a relatively new book by famous innovation expert Clayton Christensen. It is based on a speech he gave to the 2010 graduating class of Harvard Business School. This is not another business book. Instead, Christensen provides powerful and provocative ideas for finding meaning and happiness in our life. Sounds like a self-help book? Not at all. Christensen blends personal stories with deep business research. The combination of business ideas and personal life is what makes this book such an enjoyable and valuable read. Christensen looks at some of the more well-known theories such as Herzberg or the discovery-driven planning approach. He then applies those theories to our own personal life and derives some very interesting ideas and thoughts. As a business professional, I really enjoyed this combination and it left me thinking about my own career and personal life. The book is structured in three sections:
Look out for some hopefully exciting posts in the next two weeks. I will be heading back to San Francisco next week to attend OSIsoft’s vCampus Live event. This technical conference focuses on developing powerful analytics applications with the OSIsoft PI server. I am especially excited about the opening day keynote: Stephen Few will be speaking. You will see some notes and photos on this blog soon.
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.
The other day I wrote about lessons for delivering a better software demo. This article ended up being one of the most popular ones in recent times. I have therefore decided to add a few more tips as a solid demo can really make a difference. Likewise a bad software demo can really hurt you and your project. Remember – the first impression is usually the most important one. You therefore have to make sure that you do a great job.
1. Keep it clean
A few weeks ago, I watched a demo. It wasn’t that bad. However, the guy ran it of his own desktop. And what a messy desktop it was. Icons cluttered a photo of him floating in a swimming pool. Oh well. Various apps were open and the person delivering the demo often had a hard time finding the right window. Also, his email program was open. The little Outlook bubbles kept popping up and we could read some of the email subjects (Viagra for sale!). Too bad! This could have been a good demo but the overall impression was anything but positive. You wouldn’t want to sell a dirty car, would you? Before you head out to deliver your next demo make sure to do the following:
Close all apps that you don’t need
Kill all incoming emails, instant messages or Skype calls
Clean up your desktop
Choose a professional desktop background (the group photo from your bachelor party is probably not the right choice…)
Even easier: run the demo from a clean virtual machine
2. Keep it relevant
Demos need to be short and sweet. Don’t waste time explaining useless stuff. Imagine the car sales person talking about the spare wheel. Not all that exciting, is it? Spending time on irrelevant features can seriously harm you and your message. People might leave thinking your solution is not capable. You won’t believe it – but it’s true. I recently witnessed a person spending 2 minutes showing the audience how to change a password. It was irrelevant and painful to watch (message received: we have basic security). You have to make sure that what you show resonates with your audience and that it has impact. When you prepare for your demo, ask yourself the following questions:
What is the business pain of my audience?
Which features solve that pain?
Does that feature look great on screen?
Is it easy to understand?
Is this something interesting?
3. Fast forward
Have I mentioned that demos ought to be short and sweet? There are times, though, when it’s hard to stick to that idea. There are processes that may have to run, we might have to complete various ‘boring steps’ etc.. Don’t torture your audience with running through the entire process. It is so easy to loose people’s attention today. A good demo is like a river: It keeps flowing. Consider one of the following alternatives:
Record the entire demo or parts of it. Recording the entire script allows you to edit out irrelevant steps. You can also enhance a live demo with some video to show those steps in a quick manner (kind of like a timelapse effect).
Prepare the irrelevant and lengthy steps before the actual demo. This is possible in many case.
Only show the relevant fragments. We don’t always have to show it all. A simple before and after often speaks louder than hundreds of demo minutes
Team up with a colleague. Show some slides during the ‘boring’ parts while your colleague advances the demo
Better software demos
Delivering better software demos does not have to be difficult. Follow some of these ideas to improve. It’s worth it. The greatest dashboard will have a hard time getting accepted if the demos really suck.
Analyics are an extremely hot topic. While there is a lot of talk about it, too many companies are still failing to reap the true benefits from “bread and butter” tools such as dashboards. It’s safe to say that there is a disconnect: lot’s of talk and excitement, yet little true engagement on the business side. What’s causing the problem? It’s tempting to blame the technology.
Having worked with many organizations over the past decade, I have come to the conclusion that a majority of the problems are caused by needless complexity and by a maddening drive towards technical excellence. Let’s face it – an analytics solution is only as good as the adoption by the user community. Brilliant technology fails when people don’t know what to do with it. How can we fix this? I think we – the analytics professionals – need to look at ourselves and make some changes to the way we work and engage with the business community. It’s easy and comfortable to stay in a comfortable cocoon of technical talk and optimization. Our objective needs to be to step out of that cocoon and start communicating with the business.
Last weekend, I started reading an excellent book by Tim Elmore. The book is about communication. Tim makes the case that our society requires a different communication approach. In the past, we adored the great orators that would read a carefully scripted speech. Today, we relate to people who deliver messages that connect with us. The author drafts up a comparison between the past and today: public speakers (aka technical experts) vs communicators. When I studied this, it struck me: The content applies to our business analytics profession as well. I have taken the liberty to modify it a bit. Take a few minutes to study the table and to reflect how this might apply to your and your team:
Need to change
Let me tell you, this comparison really spoke to me. As analytics professionals, we need to make a serious effort to connect with our audience – the business. That requires us to leave the comfortable cocoon of technical talk. Here is an example: the classic requirements gathering. We interview, we document, we ask for sign-offs. The whole process is technical and it usually doesn’t help the business. It’s a process that was designed to help and protect the IT professional. A communicator on the other hand goes further than just creating a thick document. The communicator goes out of his way to really understand the business. That might require a simple prototype. It might require us to take a personal risk and ask more questions.The end result is a better analytics solution.
Here is a suggestion: Print out this table and take a look at it before you head into that next meeting or before you hand over that new dashboard. Think about your team. Are you a an analytics professional or an analytics communicator?
P.S.: I highly recommend reading Tim Elmore’s book. It’s an excellent read. There are a ton of exercises and self-assessments that help you improve your personal presentation and communication style. I have read many books about presenting and this is belongs in the category of books that can really have an impact.