LucidEra: the People Express of On-Demand BI?

I am not happy to see LucidEra disappearing. It is not a good sign for the SaaS BI market in general and the startups in our space specifically. And I still believe Rob Ashe (IBM/Cognos) was wrong when he said that “BI doesn’t lend itself to SaaS”.

There are some fundamental differences between first generation SaaS BI providers and cloud-based platforms like Good Data. Some of them are technological while others are simply common sense:

  • Good Data is based on true cloud architecture
  • We use Amazon Web Services to host our multitenant platform and so we have minimal fixed and very low variable costs.
  • We are true believers in Steve Blank’s Four Steps to the Epiphany, and the idea of spending over $20M before validating our go-to-market strategy is foreign to us.
  • Cookie-cutter pre-built analytics apps are should be the STARTING POINT for customers to try – not the conclusion of an enterprise sales process.
  • LucidEra was probably too expensive for small companies and too limited for large ones. And this is why we offer plain-vanilla NetSuite analytics for free.

I am sure we will see the era of success of on-demand analytics. The most useful analogy here is the disruptive business model of low cost airlines – it did not disappear after the demise of People Express airlines either…

PS. Good Data Offers Safe Harbor to LucidEra Customers (link)

Cloud Expo Europe keynote: Building Great Companies on the Cloud

Yesterday I spoke at the first Cloud Computing Expo Europe and I enjoyed the conference very much. Here is my presentation:

PS. This presentation was featured today as one of the Top Presentations of the Day by Slideshare…

Friends Don’t Let Friends Overpay for BI

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.

You will not see us in your accounts

The analyst firm The 451 Group asks technology companies “Who else do you see in your accounts?” Being “seen in the account” is perceived as a sign of market presence and ability to execute. And the opposite is true as well. Not being seen in accounts is sign of weakness and lack of market penetration. It’s also a proxy for the longevity question: “Will they even survive if they are not on anybody’s radar screen.”

My perspective is completely different. I believe that being seen in the accounts of large competitors is a sign of confusion and a complete waste of time and money. Startups are best when they disrupt existing markets, not attack them head on. Any sufficiently disruptive technology should be first deployed in a market segment that is seen as secondary or completely irrelevant by the big guys.

Established companies often compete on feature/functionality depth — delivering more features at an ever diminishing rate of value to customers to extract more money from them. Clearly not an interesting place to be for a young company.

I would like to promise here to our large competitors: You will not see Good Data in your accounts if:

  • your customers believe in a single version of truth
  • you deal with BI and data warehousing “experts” who attend TDWI seminars
  • Inmon Vs. Kimball matters to you
  • your projects are measured in months or six figure dollar numbers
  • you engage in star-versus-snowflake schema debates
  • your product offers 30 ways to format a decimal number
  • producing 1,000 different reports a day is one of your product claims

I could go on and on. Simply put – every time we read that competitor XYZ doesn’t see us in their accounts, we consider it a small victory. We don’t want to be seen in your accounts. At least not until we are ready…

Looking for SOA in All the Wrong Places?

Systinet’s founding CTO and my friend Anne Thomas Manes pronounced the demise of SOA a few weeks ago. Honestly, SOA lost its meaning for me on the day when good, old Solaris became the “SOA operating system”. But is SOA dead or not? I don’t believe so but I think that Anne and others are looking for SOA in the wrong places. Here is why:

Part of our Systinet SOA pitch was this truism: “SOA is not something you can buy”. We believed that SOA didn’t come in a box and companies have to invest time and money to build it. And maybe this is the crux of the problem. What if the act of building internal service blueprint is beyond the capabilities and budgets of the individual customers? Go to the SOA mailing list and try to understand how to build your own SOA and you can spend the rest of your life reading the discussions and related blogs and comments.

Systinet SOA

My point is that IT departments will always spend most of their budgets keeping the lights on and there is not enough money left for a complete architectural redesign. And even if they decide to throw more money at it they will still not get it right because of lack of internal expertise, lack of vision and simply because it is too hard to rebuild systems that somehow “work”. Every company seems to have a set of requirements that none of the commercial products can ever satisfy and as a result the existing internal architectures are usually completely proprietary. And sediments of bad architectural decisions are nearly impossible to peel off…

Maybe it’s time to forget about this SOA delusion and look someplace else. For companies like Google, Amazon, Workday and others (including my company – Good Data) SOA is not only “yet another IT initiative” but the key differentiator that allows them to deliver a flexible and extensible set of services. And the only way IT departments will be able to “buy SOA” is to use services from the companies in the cloud. The role of proprietary internal architectures will diminish over time as companies move to an increasing number of on-demand services – and that is probably what Anne wanted to say when she declared SOA dead…

Entrepreneur Country – Land of Opportunity

I spoke at the Entrepreneur Country forum at Institute Of Directors in London earlier today. The event was organized by Ariadne Capital (Disclosure: I am one of Ariadne investors). Here is the feedback from the audience via Twitter and below is my keynote:

Only Google…

No other major SaaS company in the world could get away with this approach to paying customers. Not only Google offers no user-friendly tools to add shared contact to the paid version of Google Apps. They offer no tools. Period.

Here is the only information available to email administrators:

Administrative management of non-employee contacts now available

Premier Edition administrators can now add contacts that aren’t employees of their own company to the contact list that each user can access in the new standalone contact manager.

First, create an XML representation of the shared contact to publish. This XML needs to be in the form of an Atom element of the Contact kind, which might look like this:

<atom:entry xmlns:atom='http://www.w3.org/2005/Atom'
    xmlns:gd='http://schemas.google.com/g/2005'>

  <atom:category scheme='http://schemas.google.com/g/2005#kind'
    term='http://schemas.google.com/contact/2008#contact' />
  <atom:title type='text'>Elizabeth Bennet</atom:title>
  <atom:content type='text'>Notes</atom:content>
  <gd:email rel='http://schemas.google.com/g/2005#work'
    address='liz@gmail.com' />
  <gd:email rel='http://schemas.google.com/g/2005#home'
    address='liz@example.org' />

  <gd:phoneNumber rel='http://schemas.google.com/g/2005#work'
    primary='true'>
    (206)555-1212
  </gd:phoneNumber>
  <gd:phoneNumber rel='http://schemas.google.com/g/2005#home'>
    (206)555-1213
  </gd:phoneNumber>
  <gd:im address='liz@gmail.com'
    protocol='http://schemas.google.com/g/2005#GOOGLE_TALK'
    rel='http://schemas.google.com/g/2005#home' />

  <gd:postalAddress rel='http://schemas.google.com/g/2005#work'
    primary='true'>
    1600 Amphitheatre Pkwy Mountain View
  </gd:postalAddress>
</atom:entry>

To publish this entry, send it to the contact-list feed URL as follows. First, place your Atom element in the body of a new POST request, using the application/atom+xml content type. Then send it to the feed URL. For example, to add a domain shared contact to the list belonging to example.com, post the new entry to the following URL:

http://www.google.com/m8/feeds/contacts/example.com/full

The Google server creates a contact using the entry you sent, then returns an HTTP 201 CREATED status code, along with a copy of the new contact in the form of an element. The entry returned is the same one you sent, but it also contains various elements added by the server, such as an element.

If your request fails for some reason, Google may return a different status code. For information about the status codes, see the Google Data API protocol reference document.

End of the Retooling Decade?

Tim O’Reilly wrote a great post about the collapse of demand for consumer electronics and there he quotes the term “peak waste” – in an analogy to peak oil maybe we’ve reached the pinnacle of waste in our consumer culture. I absolutely agree that the “creative destruction”the process of transformation that accompanies radical innovation grew to unsustainable levels recently but here is my explanation of the radical innovation that our society went through over the last 10-15 years.

One of the biggest shifts of the last decade was the move from analog to digital media. The only digital media widely used only ten years ago was the CD. And the typical CD player fits more into the analog rather then digital era (most CDs still don’t support CD-Text). The rest of media was analog – TV, VHS, radio, phone, photographs…

Ever since the mid-nineties we saw the rapid development and adoption of new music formats (MP3, WMA, OGG, AAC, Apple Lossless), new video media and formats (DVD, BlueRay, HD-DVD, DivX, MP4), new interfaces (DVI, HDMI), move from analog to digital TV (HDTV, DVB-T, DVB-S) and digital radio (DAB, DVB-H). Along with these changes came the new business models of digital media distribution (iTunes Store, AmazonMP3, Netflix online), new music providers (Sirius, XM-Radio, Pandora, last.fm). We also saw the advance of digital communication (Bluetooth, GSM, UMTS, SMS, VoIP) and it led to the rise of new providers of communication services (Skype, Vonage). Photography underwent the same transition – from analog cameras to digital cameras and now to camera-phones and from photo albums to Flickr.

The move to digital era had a dramatic impact on the design of devices we use and so we saw some very rapid changes in the consumer electronic industry: move from VHS to Tivo, POTS to iPhone, analog TV to LCD screens and many, many others. The usecases for digital world were not clear when we started this retooling and it took ten years to discover how will users get access and consume digital media and the requirements for new set of standards and interoperability.

I expect that the once we finish this transition we will be able to design more interoperable and software upgradeable devices. These devices will hopefully last longer but I still can’t imagine handing down “my grandfather’s iPod”. The rate of innovation will not decrease, it will simply move to the social aspect enabled by this retooling. Once we assume that every person in the world has an access to a device that is always connected, has a microphone, camera and GPS chip we can change the ways our societies communicate. Fortunately it will require less physical waste…

“Business-IT Chasm”: The Business Perspective

My plan for today was to write more about the “Business-IT chasm” but I came across a great blog post written by Jorge Camoes that reveals the business perspective of this divide. There is nothing better than the first hand experience:

IT will try to change your project, naturally. Try to avoid the “security bomb” (their favorite). You know how poor their expensive BI toys are, and you should know what they can and can’t do with them. Minor concessions can earn you some points. When they tell you they can’t implement your core ideas be prepared to fake genuine surprise, compare costs (again) and emphatically say that their options clearly don’t meet the organization’s needs.

My suspicion that business has limited ability to influence the electrical engineers is demonstrated by this quote:

Pissing off the IT department is one of the most enjoyable games in corporate life, but be a gentleman and don’t make them look stupid. They don’t usually have a good sense of humour and take their quest to conquer the world very seriously. If you really want to implement the dashboard, don’t make it an island if you can avoid it (connect it to the tables in the IT infrastructure, instead of copy/pasting data).

Here is the link to the full post.

The New Chasm

I believe that readers of my blog are familiar with the chart below. It is the classical “Crossing the chasm” diagram from Geoffrey A. Moore’s book Crossing the Chasm: Marketing and Selling High-Tech Products to Mainstream Customers. This book was published back in 1991 and it is still number two on “Twelve Business Books in One Hour for the Busy CEO” list. The main argument that Geoffrey Moore makes here is that the “early adopters” have no ability to influence “early majority” and it leads to a chasm that is very difficult for startups (or any company with disruptive technology) to cross:

Adoption Cycle

This book was written in the days when startups typically sold to electrical engineers (a.k.a. IT) and Brad Burnham described it well in his recent post:

In the old days, electrical engineers focused on getting computers to work not on getting people to engage with the systems built on top of those computers. The folks that built enterprise software were vaguely aware that their systems had to be accessible to the humans that used them but they had a huge advantage. The people who used them did so as part of their job, they were trained to use them and fired if they could not figure them out.

This is why even Wikipedia uses the following example to describe the end-user:

The end-user or consumer may differ from the person who purchases the product. For instance, a zookeeper, the customer, might purchase elephant food for an end-user: the elephant.

But virtually no startup gets funded today if it sells directly to electrical engineers. Innovation happens in the consumer space anyway and so the assumption is that any disruptive technology (social networks, SaaS, web2.0…) gets adopted first by the end-users and then it is picked up by the IT. But here comes the new chasm: low ability of end-users to influence IT:

Reversed Adoption Cycle

This chasm is the new manifestation of the classical “Business-IT” gap but this time is the innovation flow reversed: business leads and IT follows. And this new flow doesn’t make it any easier to cross the new chasm