As part of my work as User Experience Researcher, people tell me about their journeys of learning QlikView. This includes developers creating their first applications for other people, administrators setting up large scale environments and users of business discovery applications. These journeys describe both what people struggle with and what they find easy when using QlikView. Each journey is unique and extremely valuable for us in understanding how people use QlikView and how we can support their working process in the best way possible.
A particularly interesting trend I’ve seen is that people working within business, e.g., controllers, accountants and sales managers, can also have roles as QlikView developers at their organizations. Compared to the “conventional” developer who has specific IT or software developer skills, people with a background in business face quite different challenges when learning QlikView. For example, they are often not familiar with scripting or visualization techniques and worry a lot about best practices when designing apps. On the other hand, this specific kind of developers has an in-depth understanding of their business and the needs of their company and colleagues. They might struggle with implementing technical solutions but the applications they create are often immediately valuable to the business.
By understanding our different types of users we can create solutions that help people quickly learn and effectively use QlikView regardless of how they approach it. People’s journeys with QlikView are the basis for one of our most valuable design tools for QlikView.next: personas. A persona is a fictional character that represents core characteristics of real users based on research. Our personas at QlikTech describe behaviors and attitudes that we gather from engagements with large number of existing as well as potential users. When creating these personas, we do not only ask what people want but also observe and interview them to understand how we can support their needs efficiently and effectively.
Our personas give our different kinds of users names, faces and feelings rather than merely being a “type” or a categorization. They provide presence and influence from our users at all stages of the design and development process. The personas cover novice, intermediate and expert users and our aim is to provide solutions that can support them all when learning and working with QlikView.next.
Do you have your own journey to share or seen any similar trends when working with QlikView? Let us know in the comments below!
My youngest son recently turned 10 years old. And, the sad reality is that in many ways, he doesn’t need me that much anymore.
In fact, if I wasn’t so unwilling to give up in my role as his mother, I am quite sure that he could manage to get through an entire day without my help. Thankfully there is a lot more to life than just pouring yourself a bowl of Cheerios. Somebody actually has to make sure that there are Cheerios in the house… and for that matter, milk.
What does this have to do with the business of IT?
My role as mother is to empower my boys with the tools and resources that they need to be increasingly self-sufficient and to drive toward their own personal goals. As an IT leader, my role has always been to empower the business users and to give them the tools and resources that they need to propel the business forward.
I had to stand on the step in order to appear taller than my oldest!
Just as my relationship with my boys has evolved as they have grown, business users are much more tech savvy today than ever and it is important that we adapt our methods of delivering IT solutions accordingly. One example of this is happening is Bring Your Own Device or BYOD where business users take on at least some responsibility for self-support of their own technology devices. Another great example is the move toward self-service Business Intelligence where IT departments maintain discipline around their core mission (security, data integrity, scalability, etc.) while business users are provided with tools enabling them to answer their own BI questions allowing them to move at the speed of business.
Gartner’s research note: “How to Deliver Self-Service Business Intelligence” outlines a model for the critical issues that surround delivering a self-service BI capability and includes three key recommendations for IT leaders, all of which we see in organizations using QlikView:
A point highlighted in the paper which resonated especially well with me as a mother was the idea of giving the right amount of capability to each business user. My two boys are 5 years apart in age and sometimes it is easy to forget that they need different levels of support. The same is true for our business users. Although any business user can gain valuable insight from an interactive QlikView application with only minutes of training, not all users will be able or even want to be able to develop applications of their own. It is important to provide a platform which can deliver capability to both types of users as well as those in between and to help all users grow in how they use BI for themselves.
Learn more about the Gartner research and QlikView’s self-service BI platform here.
I am personally passionate about improving the partnership between business users and IT and would love to hear from you!
In one of Charles Dickens’ novels, a young English orphan boy named Pip received a large sum of money from an unknown benefactor and was told he would go to London and learn how to become a “gentleman.” Charles Dickens entitled his novel “Great Expectations”, describing how Pip felt on his way to the metropolis of London. In classic Dickens’ style, things are never what they seem and Pip’s fortune does not lead to a life of comfort and ease.
The theme of Great Expectations came up in a number of different ways on my recent trip to the metropolis of New York City to attend and present at the Big Data Summit organized by CDM Media. The presenters and delegates were a ‘who’s who’ assembly of people whose titles begin with the letter C: CIOs, CTOs, CDOs (Chief Data Officer), and even a CAO (Chief Analytics Officer), from some very well-known enterprises and brands, including American Express, Citi, AIG, Allstate, Suncor, and the National Basketball Association.
I certainly had great expectations going to the event: surely the industry luminaries would have Big Data all figured out and I would be able to come away with a better understanding of Big Data use cases. The first speaker heightened my expectations – he gave jaw-dropping statistics about how Big Data helps the healthcare industry fight the annual loss of two hundred billion dollars to fraud and how Big Data helps a wind energy company optimally place its wind turbines by crunching massive amounts of weather data.
Another speaker gave an impassioned call to train our schoolchildren in technology and mathematics so they could become data scientists, helping corporations and nations gain a competitive edge.
Three surprising commonalities came out of these presentations and nearly 20 private conversations with these executives:
What did exceed my expectations was the high level of engagement the executives had as they learned about QlikView in relation to Big Data. The top reasons were:
Like a great novel with unexpected plot twists, I entered the conference with great expectations, saw them brought low, but then ended with a fresh excitement over what QlikView can do for the largest of enterprises wrestling with the challenges of getting broad value from both small and big data.
For more information, check out QlikView’s page on what Big Data can do for you.
I sometimes get asked to explain what QlikTech means when it talks about association. Here’s how I explain it…
Too often we are compelled to adapt the way we think to the way software tools work.
This is the case with many business intelligence products, which optimise their performance by forcing us down linear drill down paths. But our brains don’t work in that way. Our brains work by association.
For example, if we lose our car keys we don’t work through a pre-set drill down path. We don’t think to ourselves, “Hmm. Let’s see, I was on planet Earth, in Europe, in the UK, in Hampshire, in Portsmouth, in Southsea, on Nelson road, at number 7 and in the kitchen. Are my keys in there? No, they’re not!” After failing we’d then have to start all over again down another pre-set path. If our brains were like most BI tools we’d probably have to wait for our consciousness to establish a new drill path!
In truth, what we do naturally, is think “What was I doing before I lost my keys? I remember; I was making a sandwich in the kitchen to eat while watching TV on the sofa. A-ha! There are my keys down the back of the cushion!” We find or make insights by associating non-linear data points. (At the same time you might find the remote control you lost or if you’re really lucky some loose change, which you didn’t expect). Providential discoveries rarely (if ever) occur through over structured thought processes.
We are used to being able to search freely for data quickly across billions of items on the web. Many users of traditional BI wonder why their BI isn’t as simple as this. Why do we have to change the way we discover things in everyday life just to suit a set of rules set down by a BI architecture detached from our working reality?
To give a real life example of this I was trying to book a flight for my family this year somewhere warm and dry (I live in the UK!) but on a budget. I went to the website of a well-known airline and selected my dates and destinations and then followed the path defined by the website. By the time I got to the 10th step and added all the taxes and baggage costs it worked out to be too expensive. Wouldn’t it be a much more pleasurable experience if I could enter my budget and dates and automatically get shown the destinations that were available for me? Or a country and budget and see what dates were associated and available with those selections?
Life shouldn’t be that difficult. We should all be able to just follow the associations.
A helpful team of operatives stood by to produce reports and make changes to the old BI platform’s semantic model…The Gartner report sets out two possible scenarios:
1) "Data Discovery Becomes a Feature." In this scenario, Business Discovery would become subsumed in broad BI platforms as traditional BI vendors copy or buy lookalike functionality.
2) "Data Discovery: The Leading New Analytic Architecture". According to the report, "In this scenario, data discovery muscles out and replaces the BI platform for a majority of analytical/diagnostic use cases."
In this second scenario Gartner highlights a key shift in priorities "Whereas previously, users were looking to have a portfolio of: (1) a BI platform (semantic layers providing the end-to-end spectrum of reporting, ad hoc query and OLAP functionality); (2) data discovery in a tactical fashion, adopted individually or in workgroups; and in some cases (3) statistical/predictive analysis tools; the selection criteria has shifted to look like this: (1) data discovery (now the central norm for analysis on all data sources, and where most BI budget goes); (2) production and external reporting tools for systems of record; and (3) additional statistical/predictive analysis capabilities."
Business Discovery is now being viewed by industry analysts as a viable mainstream alternative to traditional BI, which should prompt thinking about the investments organizations are making to meet their analytic needs. Do they want to continue to spend the majority of their BI budget on top-down reporting led approaches, or switch over to user driven discovery and diagnosis? For many QlikView customers, Business Discovery is already the "Leading New Analytic Architecture."
Gartner gives no indication as to which scenario it expects to prevail in the long term.
It’s obvious what QlikTech believes will happen.
What do you think?
Every year, QlikTech executes several strategic initiatives. These are cross-functional programs that are funded out of a special budget and are blessed with executive sponsorship from the highest levels of the organization. An example of a QlikTech strategic initiative is QlikMarket, which we launched last year. One of QlikTech’s strategic initiatives for 2013 is called Customer Success.
This initiative is very exciting for me on a couple of levels:
So the focus of my posts here on the Business Discovery Blog will change. Rather than writing about Business Discovery and trends in the BI market, I look forward to sharing updates with you about the Customer Success initiative. Stay tuned.
* See “Best Practices in B2B Customer Experience,” Temkin Group, April 2013 (by subscription or for purchase).
I’ve been an advocate of the consumerization of BI for a number of years. Business Discovery platforms like QlikView that embody consumer oriented characteristics are more acceptable to a broad range of people, and so see higher adoption. At core, the consumerization of technology is about empowering people to do what they need, themselves. To be able to do so any technology must possess the three key consumerization attributes of speed, usability and relevance. (For more on these see Jeff Boehm’s 2011 post on my definitional research note whilst at Gartner).
However, driving back from taking my children to school on Tuesday morning I heard a discussion, on BBC Radio 4’s Today programme about the 2013 UK Design Awards, that brought home to me that there’s a fourth attribute of consumerization, as important as the others: aesthetics. For some people how something looks or feels will overcome the three other consumerization attributes, no matter how strongly they’re made available. It’s worth noting that while usability and aestethics are closely related they’re not the same. Something can be very usable, but not look pleasing. I suppose that’s the difference between satisfaction and delight.
During an interview on the radio show Professor Josh Silver, of the Centre for Vision in the Developing World (CVDW), described the Child ViSion self-adjustable glasses his organization is distributing through schools. The glasses have fluid filled lenses that are adjusted using pre-attached syringes.
The glasses are a powerful example of the consumerization of an established technology:
• They’re fast; adjusting the lenses to correct someone’s vision takes a few minutes at most.
• They’re usable; each glasses wearer self serves by fitting their own specs – no optometrist needed.
• They’re relevant, directly to the individual life chances of the person that gets a pair, and broadly to the estimated 60 million young people that suffer from uncorrected myopia in the developing world.
Crucially though (and unlike earlier versions) the glasses are designed with aesthetics in mind. Their shape is pleasing. They come in a variety of colors. The syringes on the arms used to alter the focal length are easily removable. Why does this matter? Because the target group for these specs is 12 to 18 years old! Image conscious teenagers the world over won’t wear something that doesn’t look good, no matter how useful it is. I’ve personal experience of this – when I was at school the UK National Health Service (NHS) provided one style of glasses frame in black for children. Nowadays these NHS specs, my 16 year old son tells me, are the height of ‘geek chic’. Back then, kids would do anything not to wear them, even if they couldn’t see the teacher’s writing on the blackboard from their desk. That’s why my short sightedness went untreated until I learnt to drive…
We can learn lessons from the development of CVDW’s inspirational project.
It’s obvious that QlikView embodies the three attributes of speed, usability and relevance directly in how the technology works. The fourth one, the crucial aesthetic element, is largely up to the people who design the QlikView apps. It’s up to you to appeal to the consumers in your organization through the pleasing design of the apps you make available. Beautifully designed apps, styled to the users in question – a web site analytics apps for marketers should embody a different aesthetic to one for financial analysts – mean higher adoption, better perception of value delivered, greater return and more questions answered. The opposite means a less focused outcome.
A final thought on the Child ViSion glasses project: it’s a massively disruptive technology and extremely cost effective compared to the long established way of doing things. Sound familiar?
In the Harvard Business Review blog article by senior editor Scott Berinato, “Your Business Needs Insight, Not Just Pretty Pictures” (March 19, 2013), the author identifies an important trend in business communication. “Data comes first,” he wrote, “and it’s increasingly visual.”
Berinato describes the two drivers behind this trend as Big Data and the democratization of tools for creating good data visualizations. I agree about Big Data. But I would describe the democratization trend a little bit differently; it’s not just about broader availability of and access to tools for creating good data visualizations – because as the title of the HBR blog post says, your business needs insight, not just pretty pictures.
What’s even more important here is the democratization of easy-to-use, interactive apps that anyone people can use to quickly and easily ask and answer the next question that comes to mind, and the question after that, without having to create a new visualization or report . . . without having to create anything at all.
By its very nature, a data visualization can answer only a limited number of questions. In contrast, a Business Discovery app provides multiple ways for a user to interact with information. It provides many different data visualizations – charts, graphs, list boxes (the most basic object in a QlikView app), tables and much, more more.
With each click, tap, or lasso, users can always see what data is associated with their selections and – importantly – what data is not. They make a selection in one chart or graph and all the other charts and graphs in the app update instantaneously to reflect the new selection. It is this rich, straightforward interactivity, with a full data set behind it (often drawn from multiple back-end systems), that empowers users to discover insights in their data.
I recently read an interview on the Harvard Business Review blog with Amanda Cox, who is a trained statistician and the graphics editor at the New York Times. I appreciate the perspective she shared with author Scott Berinato.
A few key takeaways:
Data analysis is becoming a bigger part of more peoples’ lives. Amanda Cox mentioned in the interview that the people she works with are journalists, biologists, urban planners, and mapmakers. If I think about my own role in customer advocacy (and formerly product marketing), I am similar—I come from a background as an industry analyst, not a statistician. No matter what our profession or background, we can all benefit from data visualization – a key aspect of data discovery software – to help us tell compelling stories, ask and answer more questions, and take the right actions.
Sometimes you have to practice what you preach. Last month I wrote and delivered the keynote at Gartner’s European BI & Analytics Summit, during which I challenged the audience to make some important decisions, and to choose a new path for BI. Well, I’m doing exactly that, by joining QlikTech.
Some people have asked me, “Why go and work for a software vendor?” Well, I enjoyed my six years at Gartner. The analysts are great, and Gartner’s research remains fiercely independent and objective – you might even say that some of the analysts take pride in their robust dealings with vendors. (One analyst even said to me that if my first Magic Quadrant didn’t get escalated to Gartner’s ombudsman arbitration service by at least one vendor, then I wasn’t doing it right!)
But although I enjoyed being a critic, I recalled the excitement of being an actor. From my time in software development, and later at Hyperion, I remembered the excitement of helping to create and market technology, realized that I missed it, and so decided to go back to working for a software vendor. But there’s more to it than that – it’s also the realization, made endlessly clear to me when talking to organizations about their BI strategies for Gartner, that the balance of power in the world of BI and analytics is about to tip, and I want to be part of the force that makes it do so.
As a follow up question – and knowing that I’ve had frequent dealings with almost all the BI vendors in the last few years – people then ask, “Why QlikTech?” I answer them with a question: “Do you remember what the BI market was like before QlikTech began to disrupt it?” The market was growing in revenue terms, but moribund in many other ways. It was seriously lacking innovation and was more known for failed projects than successful implementations. QlikTech changed that: It’s a rare thing to find a company and product that completely shakes up a market to the point where the existing market share leaders have to begin emulating its approach, and a bunch of new vendors emerge to follow its lead.
That’s all good, but QlikTech must continue to change the market; it remains a fact that too many people are still working with BI that doesn’t deliver, and they need to revisit how they do it. But for QlikTech to get as many organizations as possible make such shift, it will need to change, too, growing its platform capabilities and extending its reach. The company’s vision for “QlikView.next” (the code name for the next generation of QlikView) sets out how it intends to do so. QlikTech’s plans are bold, and key in why I chose to join the company and to contribute my energies to transforming how people do analytics through discovery.
So, that’s why I’m here. I’m hoping, in the words of the Green Day song, that the move is “something unpredictable but in the end right.” I hope to have the time of my life.
Image attribution: http://www.flickr.com/photos/swimparallel/3455044234/sizes/l/ (Creative Commons ShareAlike license.)
Analysts at Forrester and Gartner are seeing a rise in adoption of enterprise app stores. As Forrester looks ahead a few years, they see corporate app stores moving beyond distribution of corporate-approved mobile apps to provide content sharing, granular discovery, provisioning, and reporting and monitoring services. Forrester goes so far as to predict that app stores will become the primary way for individuals to obtain applications.* Gartner predicts that by 2016, 60% of enterprise app stores will be primarily composed of third-party apps rather than enterprise-developed apps and that by 2017, 25% of enterprises will have an enterprise app store for managing corporate-sanctioned apps on PCs and mobile devices.**
I talked about this recently with Donald Farmer, our VP Product Management. A concept that’s on his mind when thinking about enterprise app stores is the information supply chain. How will all these apps be able to deliver the information users need so they can ask and answer streams of questions on their own?
In a traditional environment IT would build, own, and manage the entire experience of information, from sources to analysis and visualization. But in the supply chain model, an enterprise data warehouse is only one element of the information landscape, with many peripheral apps extending and augmenting it. IT seeks to publish as much data as possible through APIs, feeds, and other mechanisms – even reports. While some of this infrastructure requires IT support and maintenance, in a supply chain model, the goal is always to provide users with direct access and do-it-yourself tools wherever possible. (See the related blog post, “The IT Supply Chain: Making the IT Store Concept Work,” October 15, 2012 and the CITO Research white paper, “Putting the IT Store Ecosystem into Action.”)
Enterprise app stores and the information supply chain are first nature to QlikTech. Our customers have been calling their QlikView creations apps for a long time: lightweight, purpose-built, task specific applications. Our customers make these apps available to users via an internal web-based “store.” Today we call the place where users can search for and discover QlikView apps AccessPoint. In “QlikView.next,” the new AccessPoint will be QlikView itself. (See the blog post, “Compulsive Collaboration with ‘QlikView.next’ – Many Ways to Make Music Together.”) And as we set ourselves up to support customers deploying IT stores, we’re paying close attention to the information supply chain.
* See the Forrester Research report, “Build A Corporate App Store Into Your Corporate Mobility Strategy,” January 16, 2013 (available to Forrester subscribers or for purchase).
** See the Gartner reports, “Enterprise App Stores Can Increase the ROI of the App Portfolio,” February 4, 2013 and “There’s an App for That: The Growth of Enterprise Application Stores,” September 7, 2012 (available to Gartner subscribers).
“Learning is not a place, it’s an activity.” This is my favorite quote from a TEDTalk by Andreas Schleicher titled “Use data to build better schools.” Schleicher is the Deputy Director for Education and Skills and Special Advisor on Education Policy to the Secretary-General of the Organisation for Economic Co-operation and Development (OECD).
This talk was about PISA, the OECD’s program for international assessment of 15-year-old students around the world. PISA studies education investments and outcomes and conducts international comparisons. The latest PISA assessment (2009) measured 74 school systems that covered 87% of the economy. The study measures skills directly, not whether students can reproduce what they learned in school. It “measures whether students are prepared for change,” Schleicher said.
This is a video worth watching for several reasons:
Find this article and TEDTalk interesting? Check out the related blog post, “QlikView Is Playing a Part in Education Reform,” about how FirstLine Schools is using analytics to measure student and school performance and success and lighten the burden on administrators.
Who doesn’t like pizza? In every office where I’ve worked, free pizza is a great motivator. From a cost-benefit perspective, free pizza every day might be an effective employee incentive!
What does pizza have to do with Big Data? A recent white paper published by CITO Research and sponsored by QlikTech showcases many transformative uses of Big Data by businesses, including a large pizza chain.
The pizza chain, like most retailers, needed to understand what products customers were buying and optimize their product mix to maximize profitability. Menu items that were unprofitable needed to be eliminated to make room for profitable items (which hopefully included one of my favorite pizzas - the Hawaiian, which is topped with ham and pineapple).
They faced the same challenges many retailers face when it comes to analyzing data – a complex organization comprising the corporate entity and franchisees, and the need to present the data appropriately, whether to the company board or a franchise manager.
With QlikView, the pizza chain was able to accomplish some great feats:
What I found most impressive about the story is that this QlikView app took two developers only ten working days to complete.
With other BI platforms out there, after ten days, the developers would probably be still designing the requirements for a data warehouse just to consolidate all the data. The project would have taken months or years to complete and cost the company hundreds of free pizzas to motivate the developers.
I think fundamentally this is why BI developers are so passionate about QlikView. They can deliver incredibly useful apps within days to business users. Not only does that make them the hero, it frees them up to tackle other interesting business problems.
The moral of the story? With QlikView, companies could offer free pizzas to their employees and still be profitable!
I recently read a New York Times article called “What Data Can’t Do” by columnist David Brooks. The gist of the article is that while data can yield important insights to drive better decisions, it’s not the only input. He gave an example of the chief executive of a large bank that had to decide whether to pull out of Italy. While the data showed a series of downside scenarios, the executive decided not to pull out of Italy based on other, non-data-related criteria: the relationship, trust, and values.
This really resonated with me. Holistic decision making relies on multiple sources of input, some quantitative (hard numbers, GPS info from mobile devices) and some qualitative (e.g., others’ opinions, observations, questions, and ideas — sometimes gleaned while out “on location”). Conversation and collaboration, as well as indicators and information from the world around us, help create the context around data and drive better decision making.
With QlikView we embrace this reality that people make decisions based on multiple sources of input. Users collaborate on creation of analytic apps and can define and answer their own questions―in formal or informal groups. They communicate with each other to collaboratively explore data, forge paths to discovery and insight, and arrive at decisions.
How? For asynchronous collaborative analysis, when people can’t be in the same place or online at the same time they can initiate and participate in threaded discussions or send each other bookmarks that retain the selections they have made. When they are available at the same time but can’t be in the same place they can interact simultaneously with an app using shared sessions. People who are creating QlikView apps can send the entire app to others, who can pick up where they left off on development or analysis. This is just the beginning of collaborative Business Discovery. Click here to learn more.
This week, InformationWeek executive editor Doug Henschen published an article about the 2013 Gartner Magic Quadrant for Business Intelligence and Analytics Platforms, which came out in early February. (You can read the report in its entirety here.) We’re proud to be positioned in Gartner’s Leaders quadrant for the third consecutive year!
InformationWeek quoted Gartner analyst and report co-author Kurt Schlegel as saying, "Almost every user organization I talk to now is looking at making data discovery a more significant part of their BI and analytic platform architecture.” He commented that the benefit is improved agility because business users are freed to explore data and find new insights without having to put in requests to IT for new cubes or reports. QlikTech CEO Lars Björk was quoted in the article as saying, “Others are now confirming that [data discovery] is where the puck is moving, and it's a great testament that we're in the right place.”
The most exciting part of this year’s Magic Quadrant is that in our leadership of the data discovery category, QlikTech has helped transform the entire BI industry. But we’re not resting on our laurels. There’s more to come. Check out the series of blog posts about “QlikView.next,” the next generation of the QlikView Business Discovery platform.
We all like stories. Why? We can lose ourselves in them for a time. Stories can make us feel as if we are experiencing something new. This also explains why movies and, to an even greater degree immersive video games and virtual worlds, are so compelling – but that’s a topic for another day.
I appreciate the insight about the human brain and storytelling in the December 5, 2012 Lifehacker article, “The Science of Storytelling: Why Telling a Story Is the Most Powerful Way to Activate Our Brains,” by startup co-founder Leo Widrich. With data storytelling one of the product scenarios of “QlikView.next” (see the related post, “Data Storytelling with ‘QlikView.next’”), the article grabbed my attention.
Widrich pointed out that when we read words on a PowerPoint slide, for example, our brain goes into language processing mode; the brain is trying to decode words into meaning. In contrast, when we are engaged in storytelling (either on the telling or listening side), not only are the language processing parts of the brain activated—but also any other part of the brain that we would use if we were experiencing the events in the story.
Wait, it gets even cooler. Because this brain activity happens in both the storyteller and the person listening to the story, storytellers can synchronize their brains with the recipient of the story. Whatever the storyteller is experiencing, they can induce the listener to experience too.
What does this have to do with Business Discovery? A whole lot. The same principle applies to numbers on a page or screen as to words. If we just see the numbers in black and white our brain goes into processing mode. We try to figure out what the numbers mean.
With numbers, how do you get your (data) point across? How do you convey the emotion behind your discovery or proposed decision? How do you get others on board with you? If someone is telling or listening to a story about the numbers – how the numbers came to be, why they matter, what their implications are, and what should be done about it – more peoples’ brains (and more of their brains) are engaged. Telling stories with data requires a connection to the data being analyzed.
And, to take this idea all the way to its conclusion, isn’t brain synchronization the nirvana of business intelligence? The nirvana of BI is alignment – getting everyone on the same page so the organization can move as one in the right direction, based on facts.
See these related blog posts:
Thanks to Tom Mackay, principal solution architect at QlikTech, I recently came up on the article, “Seven Dirty Secrets of Data Visualisation” by programmer Nate Agrin and data visualization developer Nick Rabinowitz. In addition to shining light on some best practices in data visualization, this article helps illuminate the difference between standalone data visualization tools and a Business Discovery platform.
The article covered seven dirty secrets of web-based data visualizations; I have thoughts about a few of them:
Visualizations are just the tip of the iceberg – the iceberg being a person’s understanding of the data. To be able to derive meaning and insight from data, especially complex data sourced from multiple systems, the user requires not only well-designed, clear, concise data visualizations, but the ability to explore the full dataset on their own. They need to be able to ask and answer their own streams of questions without having to go back to an expert for a new visualization every time they have a follow-up question. This, in a nutshell, is the difference between a standalone data visualization tool and a Business Discovery platform.
During this time when student test scores convey doom and gloom and education budgets are pinched, I jump on positive news when I get it. I came upon some good news recently during a conversation with FirstLine Schools in New Orleans, Louisiana. I spoke with Sia Karamalegos, director of data management, and Rebekah Cain, director of development and communication. FirstLine Schools is a charter management organization managing five public schools. The organization has approximately 2,500 students and 300-400 employees and is a grant recipient in QlikTech’s Change Their World program.
In the words of Gillian Farquhar, QlikTech’s customer ambassador, “Like in most urban environments across the United States, lots of kids in New Orleans come from broken or economically challenged homes and the public education system has had a hard time producing the success it hopes for. Charter management organizations like FirstLine Schools intervened to make a difference early in children’s lives.”
Sia Karamalegos of FirstLine Schools said, “A lot of schools are trying to reform across the United States. A big aspect of reform in public education is using data to drive instruction. A challenge with this, though, is that school leaders, teachers, and special education and intervention staff are generally not data experts. They need to be able to easily access and make use of the data. But the diverse nature of the source data systems we use presented a challenge. Some systems permit users to export data while others don't. The data is in many different formats and the systems each have their own login. For teachers and administrators and even network administrators, this situation created a barrier to being able to make good use of data. People needed a better way to get a complete view of school and student performance.”
Rebekah Cain added, “School leaders have a big job. They are already working really hard. So any way we can make it easier for them to access the data they need to do their jobs, the better. Then they can spend their time on things that will improve instruction instead of looking for data.”
Using QlikView, FirstLine Schools is focusing on:
I asked Sia about FirstLine Schools’ “a-ha moments” with QlikView. In one example, they noticed that for different schools in the system, the rate of in-school suspensions vs. out-of-school suspensions had changed. This realization sparked further investigation. Moving forward, FirstLine Schools is planning to tie in additional data to identify which intervention programs are having the greatest success so they can spread best practices.
Are you inspired? I am.
When I’m asked what customers use QlikView for, I usually respond with the top of mind answers about dynamic reporting, actionable dashboards, and works-the-way-your-mind-works type of analytics. There’s nothing wrong with those answers – that’s why most customers buy business intelligence software, and QlikView in particular. Last week I attended the first-ever QlikView Technology Summit in the San Francisco bay area where I got to mingle with several hundred QlikView customers and prospects. One customer’s use for QlikView blew me away.
This customer works for a healthcare company. He told me their nurses use QlikView. Not too surprising, I thought to myself, as many hospitals use QlikView to analyze patient data. He then told me how QlikView helps nurses diagnose patients. As patients describe their symptoms, the nurses make selections in the QlikView app. QlikView displays a list of possible diagnoses, narrowing down the options as the nurses make more selections.
Wow! This is the power of QlikView’s associative experience at work. If you’ve ever been to a specialist at a hospital, you usually fill out a very long questionnaire about your symptoms. This annoys me because most of the questions have nothing to do with why I’m there. By using QlikView, the nurse is able to quickly zero in on the problem because all the unrelated options are greyed out as soon as the nurse makes a selection. You might notice that this creative use of QlikView, an ostensibly BI tool, has nothing to do with charts, visualizations, and dashboards. And unlike so-called “expert systems,” where nurses follow a predefined path of questions much like a traditional call center, QlikView allows nurses to follow the patient’s own train of thought and their own experience of their condition.
I can immediately imagine a list of tangible benefits:
At a time when the quality and cost of healthcare seems to be at odds with each other, QlikView shows how hospitals can deliver better care at a lower cost. Now that’s what I call a win-win situation!
A nighttime murder took place in 1991 in Linwood, California. Half a dozen teenaged eyewitnesses picked a man out of a lineup and he was eventually convicted. No gun was ever found, no vehicle was identified, and no person was ever charged with driving the vehicle.
For two decades, the convicted man – Francisco Carrillo – maintained his innocence. Eventually, forensic psychologist Scott Fraser got involved. He reconstructed the crime scene with a focus on the lighting. He convinced the judge that the eyewitnesses could not possibly have seen the shooter in the dark well enough to identify him; the witnesses’ color perception would have been limited and depth of field would have been no more than 18 inches.
As a result, Carrillo’s murder conviction was overturned and he was released from prison after nearly 20 years.
Scott Fraser told this story in a TEDx talk posted in September 2012, “Why Eyewitnesses Get It Wrong.” Fraser described how even close-up eyewitnesses can create “memories” they could not possibly have experienced. He explained an important characteristic of human memory: the brain only records bits and pieces of an event or experience.
The different bits are stored in different parts of the brain. When we recall those bits and pieces, we have partial recall at best. From inference and speculation and observations that took place after the event, the brain fills in information that was not originally stored there. Our memories – all our memories – are reconstructed.
Reconstructed memories are a combination of an event and everything that has occurred after the event. They are reconstructed every time we think of them. As a result they can change over time. Therefore, the accuracy of a memory can’t be measured by how vivid it is nor how certain we are that it is correct.
In this TEDx talk, Fraser made a couple of recommendations for the criminal justice system. As I was listening to him I thought that these apply to business decisions just as much as to the law. Fraser identified two things are really important for decision making:
Which initiatives should we invest in? Where should we open a new retail store? What is the best way to retain our most profitable customers? How can we reduce inventory costs? By using analytical skills and basing decisions upon a combination of hard data and experience we are best positioned to avoid big mistakes – some of which could be as significant as sending the wrong guy to jail.
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Do you know where the big data is in your own life? Or even the life of your ancestors? They are gone, but not forgotten, at Ancestry.com, which serves as an example of what big data really is, and how important concepts like accurate data enter the picture and our world.
