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.


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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.**

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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).

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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:

  • Great data storytelling. Schleicher used data to tell the story of how countries compare on education metrics and what the trends look like over time. He shared findings on spending per student, how countries spend their money (e.g., hours of schooling and teacher compensation), and value for the money. He augmented the data charts with specific examples that brought the story to life. For example, 9 out of 10 students in Japan believe that excellence in math is a result of their own investment and effort. In contrast, students in North America believe that to be good at math you have to be born a genius.
  • The transformational power of data. To be clear, it’s not the data alone that’s valuable; it’s the sum of the collection, analysis, and communication of the data. Schleicher gave an example of this power in Germany. In 2000, Germany’s scores on the PISA were low compared to other countries. This was a shock to many. For months the public debate centered on education. Policy makers got involved, the federal government increased its investment in education, and the beliefs people held about education began to change. Nine years later, Germany’s scores improved significantly.
  • It’s about one of the most important issues facing humanity. In case you don’t get a chance to watch the video, I’ll share with you some of the characteristics that high-performing school systems share, according to PISA. They place a high value on education. They believe all children are capable of success. (As examples, today every young Korean finishes high school. And in Finland there is only a 5% performance variation across education systems in that country; there, success is systemic.) And they invest in educators. They are careful how they select, recruit, and train teachers, and how they structure teacher pay. They provide an environment for teachers to collaborate, focus on growth pathways for teachers, and provide room for teachers and principals to be inventive.

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.pizza.jpg

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:

  • Analyze 57 million transactions
  • Consolidate data from 35 separate sources
  • Cover 500 pizza sales outlets across multiple venue types
  • Allow franchisees to view relevant datasets in a central location over a secure browser interface

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.

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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.

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