Roman Stanek

Archive for the ‘BI’ Category

The Masses Against The Classes

In BI, Work, cloud on July 20, 2010 at 11:44 am

“When you open BI to the masses, people get a taste of what they can do and start demanding more and more information and analytics” Dan Vesset, IDC analyst, Computerworld, June 21, 2004

“Let them eat cake”. Marie Antoinette, Versailles, 1789

I’ve always found the BI industry’s fascination with elitism a throwback to the old days of IT. It seems that most of the industry calls users with no access to their tools “the masses”. And it gets worse. Bloggers from Endeca call them half jokingly “the angry mobs” and SAP has BI for “the rest of us”. All these words describe a business user who doesn’t have the time or skills to operate a complex BI solution designed for electrical engineers (who go by the name of IT). BI has penetration rate of 10% and everybody else is “the rest of us”.

It’s not just BI. The telco industry thinks their customers reside in “the last mile” – as far away from what’s important (the core of the network) as you can get. Shouldn’t their customers be in “the first mile”? And now BI is adopting the same “last mile” language, and the intent is the same: “keep my business users as far away as possible so I can focus on the core of my BI system.”

Making BI accessible to the “angry mobs” is in contradiction with BI industry’s quest for ever more complexity and hype. Petabyte warehouses, data visualization, social media analytics, predictive clustering, corporate performance management are the current industry buzzwords. Press releases and PowerPoint charts are full of names like Pig, Hadoop and Hive. These trends and tools were designed for the selected few; not for the average business user.

My vision for GoodData was always very different. Our goal is to get rid of the convoluted BI value chain. We are using the economics of the cloud to offer a service that can be used by a business audience. I am on a personal mission to support “the masses against the classes” and to build BI that is not a dumbed down version of an expensive, complex and brittle enterprise solution. I’ve always believed that the enterprise data warehouse is the place where data goes to die, leaving the poor business users with Excel spreadmarts.

This is why we just announced a fully integrated and free service: GoodData for Zendesk. Every Zendesk Plus+ customer gets free analytics from us; and the setup time is less than 5 minutes. And why free? We actually believe in what Dan Vesset wrote back in 2004. That once our users get a taste of what they can do with it they will start demanding more and more information and analytics. GoodData is BI for the business user. Something the elitist industry will call BI for “the masses”, “angry mobs” or even “the rest of us”…

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With friends like Forrester and Gartner, IBM and SAP don’t need enemies…

In BI, Work, cloud on February 15, 2010 at 7:21 pm


The Innovator’s Dilemma by Clayton M. Christensen is my favorite business book – its main idea (disruptive technologies serve new customer groups and “low-end” markets first) was the guiding principle of all my startups. The best part is that even though everybody can read about the power of disruptive technologies, there is no defense against them. Vendors can’t help themselves. They study The Innovator’s Dilemma, pay Christensen to speak to their managers, but their existing customer base and “brand promise” prevent them from releasing products that are limited, incomplete or outright “crappy.” That’s what makes them disruptive. And industry analysts seem to be the only hi-tech constituency that has either never read Christensen, or is still in absolute denial about it. It makes sense: a book claiming that “technology supply may not equal market demand” is heresy for people who spend their lives focused primarily on the technology supply side.

Christensen argues that vendors no longer develop features to satisfy their users, but just to maintain the price points and maintenance charges (can you name a new Excel feature?). But in many cases the vendor decisions are driven more by industry analysts and their longer and longer feature-list questionnaires. The criteria for inclusion into the Gartner Magic Quadrants and Forrester Waves seem to be copied straight from Christensen’s chapter: “Performance oversupply and the evolution of product competition”. Analysts are the best supporters that startups can have: they are being paid by the incumbents to keep them on a path of “performance oversupply”, making them so vulnerable to young vendors “not approved” by the same analysts!

Forester BI analyst Boris Evelson gives us a great example of this point in his blog about “Bottom Up And Top Down Approaches To Estimating Costs For A Single BI Report”. While Boris is a super smart BI analyst, he somehow failed to observe that his price point of $2,000 to $20,000 per report opens a huge space for economic disruption of the BI market. Anybody interested in power of disruptive technology in BI should listen to a recent GoodData webinar with Tina Babbi (VP of Sales and Services Operations at TriNet). Tina described how the economics of Cloud BI enabled her to shift TriNet’s sales organization “from anecdotal to analytical”. This would not be possible in the luxury-good version of BI, where each report costs thousands. Fortunately, Tina is paying less for a year for a “sales pipeline analytics” service delivered by GoodData than the established vendors would charge for a single report.

I hope Boris’ blog post will appear in one of the future editions of The Innovators Dilemma as a textbook example of how leading analysts failed to recognize that established products are being pushed aside by newer and cheaper products that, over time, get better and become a serious threat. And with friends like Forrester and Gartner, the incumbents don’t really need young and nimble enemies…

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COSS BI: Open Source, Open Core or Openly Naked?

In BI, OSS, SaaS on November 17, 2009 at 9:27 am

Peter Yared wrote recently a BusinessWeek guest blog post called “Failure of Commercial Open Source Software.” Not surprisingly his post caused a lot of angry replies from people who work for COSS companies. “The emperor is not naked” they argued.

I believe that the COSS emperor is openly naked. And the discussion shouldn’t be whether COSS is a complete or a partial failure just because there are few successful exits that Peter neglected to mention. At the end of the day Peter’s comment that “selling software is miserable” is true. Every sales rep involved in selling COSS would agree (I’m interviewing many of them now). Selling COSS is no easier than selling any other form of software.

Any company using the word “open” should be able to explain the true cost of delivery (this is one of Peter’s points). And there is an obvious litmus test of openness of COSS companies: One that I would call “open pricing.” COSS companies should openly publish their price list and clearly mark what’s free and open and what’s paid and closed. Otherwise OSS is just a bait-and-switch to a familiar proprietary software tactic of customer lock-in. This is what OSS was supposed to get rid of in the first place.

Let’s take a look at some of COSS companies in the Business Intelligence space. The bait and switch is in a full swing here:

Jaspersoft: https://www.jaspersoft.com/jaspersoft-business-intelligence-suite-0 Let us prepare a custom quote for you.

Pentaho: http://www.pentaho.com/products/buy_bi_suite.php Request a Quote

Talend: http://www.talend.com/store/talend-store-inquiries.php A Talend account manager will be in touch shortly to provide information and/or a detailed quote.

We announced GoodData pricing earlier today and I would actually argue that we are a more open company than any of companies listed above. Our customers know exactly what service they get and how much it will cost.

We stick to our company motto: GoodData = BI – BS. And at there is a lot of BS going on in COSS space. It may actually be its biggest failure.

 

Full disclosure: I have been a big believer in open source since we opensourced NetBeans more than 10 years ago.

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Please Don’t Let the Cloud Ruin SaaS

In BI, SaaS, cloud on October 1, 2009 at 2:49 pm

Back in the old good days of enterprise software, we did not need to worry about our customers. We delivered bits on DVDs – it was up to the customers to struggle with installation, integration, management, customization and other aspects of software operations. We collected all the cash upfront, took another 25% in annual maintenance. Throwing software over the wall … that’s how we did it. Sometimes almost literally…

I now live in the SaaS world. My customers only pay us if we deliver a service level consistent with our SLAs. We are responsible for deployment, security, upgrades and so on. We operate software for our customers and we deliver it as service.

But there now seems to be a new way how to “throw software over the wall” again. Many software companies have repackaged their software as Amazon Machine Image (AMI) and relabeled them as SaaS or Cloud Computing. It’s so simple, it’s so clever: Dear customer, here is the image of our database, server, analytical engine, ETL tool, integration bus, dashboard etc. All you need it is go to AWS, get an account and start those AMIs. Scaling, integration, upgrades is your worry again. Welcome back to the world of enterprise software…

AMI is the new DVD and this approach to cloud computing is the worst thing that could happen to SaaS. And SaaS in my vocabulary is still Software as a Service…

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Bad economics are difficult to shake off

In BI, cloud on September 24, 2009 at 9:12 am

Terry Pratchett once wrote that “Gravity is a habit that is hard to shake off”. We could make a similar comment about the financials of SaaS BI companies. As much as startups in this field would like to shake off their bad economics, reality always catches up. We’re seeing one after another SaaS BI startup to go out of business. Back in June it was LucidEra and earlier this week Blink Logic ceased operations. But anybody who only briefly looked at Blink Logic’s finances (it was a public company) shouldn’t be surprised by this event.

Why do so many of the attempts to marry BI and SaaS fail? The problem is that Saas BI sounds simple … simple enough to take an existing BI asset (integration engine, open source analytical engine, columnar database, dashboarding, even domain expertise & consulting) and just host it! All it takes is VMware or an AWS account, web server and Flash or JavaScript. Some people call this a paradigm shift, I call it window dressing. LucidEra was essentially restarted Broadbase, BlinkLogic was once called DataJungle, PivotLink recently changed their name from SeaTab, Cloud9 Analytics has a secret history as Certive, Success Metrics morphed into Birst. I could go on…

Why do SaaS BI companies have bad economics? It’s an attractive market – one of the last few open spaces in software. BI requires dealing with lots of data, lots of compute power and many users. SaaS + BI seems obvious. But truthfully, it’s such a difficult opportunity that it requires a new approach, yet everybody is taking shortcuts. SaaS BI isn’t just hosted BI just as email is not just better faxing, wikis are not just simplified Microsoft Word. Some time ago I wrote a case study on how my former company, NetBeans, was able to successfully compete against giants like Symantec, Borland or IBM, this case study is very relevant to our SaaS BI discussion.

The SaaS BI paradigm shift needs to be truly transformational in order to be successful – something that will get BI above the 9% adoption flatline it’s been at for years. Not everybody gets this. One of the best analysts in this space Boris Evelson wrote a blog post earlier this week where he focuses on differentiation of SaaS BI startups. His first question is: VC backing. Is the firm backed by a VC with good track record in information management space? But LucidEra was very well funded by leading VCs. The correct question that Boris should have asked is: Are the backers of the company funding innovation? Do they understand that it takes three years to become an overnight success?

At the end of the day, it’s about economics. At Good Data, our economics are simple – cloud computing, multitenancy and adherence to customer development. We’ve spent two years investing in innovation. That is what I tell my investors every day. And that is how we are going to avoid the startup death spiral.

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Friends Don’t Let Friends Overpay for BI

In BI on April 24, 2009 at 1:19 am

Business Intelligence projects are famous for low success rates, high costs and time overruns. The economics of BI are visibly broken, and have been for years. Yet BI remains the #1 technology priority according to Gartner. We could paraphrase Lee Iacocca and say: People want economical Business Intelligence solutions and they will pay ANY price to get it.

Nobody argues with the need for more Business Intelligence; BI is one of the few remaining IT initiatives that can make companies more competitive. But only the largest companies can live with the costs or the high failure rates. BI is a luxury.

I believe that the bad economics of BI are rooted in the IT department/BI vendor duopoly on BI infrastructure. This post focuses on IT’s inability to deliver efficient BI projects; I will write about the BI industry in my next blog:

There are three fundamental reasons why IT departments in their current form fail to deliver economical BI solutions:

1) They don’t understand elastic scale

IT departments are good at scaling: adding more and more hardware and software but scaling makes sense for tasks that are highly predictable. Given the ad hoc nature of BI we not only need to increase the compute power when we need it for a complex queries but we also need to be able to decrease the compute power when it’s not needed to keep the costs down. Elastic is more important than scalable. And this precisely why internal BI solutions will always be either too expensive or too slow for complex queries…

2) They try to control BI with a single version of the truth

While the volatility of business environment is increasing the IT departments are trying to button up the business knowledge (data, metadata, processes) into a top-down, inflexible and lengthy process that should produce a single version of truth. The problem is that the underlying business is changing so rapidly that by the time this is done the resulting analysis and reports are not correct anymore and the BI project becomes shelfware.

3) They cannot measure success of BI

“If you can’t measure it, it’s not worth doing!” is one of the selling point of BI but it is difficult to measure the success of BI projects. IT delivers on initiatives that are quantifiable (throughput, response time, performance, data sizes) and since the data size is one of the few easily measured aspects of BI it is the only metric where IT can claim success. This is why we often read about terabyte and petabyte datawarehouses. But it is a small portion of the BI market (2%) and they happen to be places where data goes to die.