Category Archives: Analytics

Keep natural gas flowing with analytics

The Power of Data

Last week, I had the honor to moderate the OSIsoft 2014 user conference in San Francisco. Over 2000 professionals came together to discuss the value and use of real-time data across different industries. There were a ton of really interesting and inspiring customer presentations. It’s just amazing to see how much companies rely on analytics these days to keep their operations running and/ or to improve their situation.

Combating the Polar Vortex

One of the keynote presentations of the conference really stuck out and I want to share the content with you. Columbia Pipeline Group (CPG) operate close to 16000 miles of natural gas pipelines in the US. Keeping the gas flowing reliably and safely is not easy to begin with. But doing that during the polar vortex that struck the East Cost of the US earlier this year is even harder. CPG turned to real-time data and analytics to keep their assets safe. The benefits of using data are tremendous as outlined in Emily Rawlings’ presentation:

  • Estimated $ 2.8M in savings from event (outages etc.) prevention
  • Increased customer confidence
  • Improved asset reliability
  • Expanded operational visibility.

If you have a few minutes to spare, take a look at Emily’s cool presentation:

 

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Data is only useful if you use it!

The value factor

We have all become data collectors. This is true for corporations and individuals. Organizations store petabytes worth of customer transactions, social sentiment and machine data. SAP’s Timo Elliott recently wrote a nice blog post about the ‘datafication’ of our own private lives. Just to give you a personal example, I have over 2GB worth of exercise data (heart rate, running pace, cycling power, GPS info, etc.) ranging back to 2003. But there is a growing problem – too many people & organizations are just really good at collecting data. Not enough people are doing anything with it. Let’s face it – data is only valuable if we really use it!

The inertia problem

strava

There is a ton of data available

Leveraging data for your benefit can be a struggle: you have to process it, you have to look at it, you have to analyze it and you also have to think about it. Here is an example: let’s say I am a runner and I wear a heart rate monitor that is connected to my iPhone. I will only get value out of that data, if I am willing and qualified to analyze it after each run. Letting the data sit on my iPhone will not help me identify trends and patterns. And then there is also the step of developing and implementing specific actions: should I rest, do I need to run harder to improve my marathon time or do I actually need to slow down to accelerate recovery? The same thing is happening in organizations. Starting to trust your analytics is another whole big issue.

Take action

How can we prevent becoming masters in data collecting but rather champions in performing analytics? Based on my experience there are a number of actions we should all look at (personal & professional):

  • Examine your available data and make sure that you really understand what it all means. This includes knowledge of the data sources, meaning of KPIs, collection methods, etc..
Power data

Do you really understand your data?

  • Sit down and clearly identify why you are collecting that data. Identify goals such as increase sales, set a PR in the next marathon, increase machine performance.
  • Develop a habit of working with your data on a daily basis – practice makes perfect. Only cont
  • Acquire the right skills (attend training, read a book, meet a thought-leader etc.) – we all need to work on our skills
  • Invest in the right tools – not every piece of software makes it easy to perform analysis.
  • Collaborate with other people, i.e. share your data, discuss findings
  • Celebrate success when you are able to achieve your desired outcomes

What are your experiences? Are you really leveraging your data or are you just collecting it? What else can we do?

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The Power of Data – Collaboration

It’s my data!

No doubt – there is tremendous value in data. I use data collected from a small sensor in my bike to improve my cycling performance. Factories leverage data to keep their machines humming as long and as efficiently as possible. Unfortunately, most companies have historically tried to keep data for themselves. Sharing was a foreign concept. Security concerns and cultural barriers (“It’s my data!”) have fostered this environment.

“Share your knowledge. It is a way to achieve immortality.”― Dalai Lama XIV

Collaboration

What if we could share critical data with relevant stakeholders in a secure and effective way? Would we be able to improve our performance? Take a look at this short video to see what can happen if you start sharing subsets of your data. It is a fascinating scenario.


OSIsoft will release this new technology later this year. Stay tuned for more updates.

How could your business benefit from collaboration? What type of data are you ‘hiding’ from your stakeholders?

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Naked Statistics – A book review

Scary Statistics

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.

All Greek?

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.

The content

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).

NormalDistributionSD

The normal distribution – no need to be afraid

Naked Statistics

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.

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Big Data – Can’t ignore it?

Big data

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

Pie Chart

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.burj khalifa

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!

Christoph

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Recommended reading for December

Recommended reading

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.

The statisticians at Fox News

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.

Simply statistics

One of the charts that is being discussed.

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.

Nucleus predictions 2013

 

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Is your analytics solution a trusted advisor?

The trusted advisor?

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.

  1. Reject: Can I trust the data? What am I supposed to do with it?
  2. Accept: I can see the value but I can’t identify the stories
  3. 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.

Acceptance of Analytics

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.

Polar

Relying on analytics can be a leap of faith

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).

Your role

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.

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Inspiration from Stephen Few

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.

Concentric circles

“Concentric circles” in the corporate world

 

Check back here in the next few days for a summary of Stephen Few’s presentation.

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Recommended reading: How to convert complex data into a story

The Analytics Communicator

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.

 

Avinash Kaushik

 

 

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Three simple ideas for better software demos

Better software demos

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:

    • messy desktop

      Does this look good enough for a customer?

      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:

better software demo

  • 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.

Good luck!

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