Avoiding Vendor Lock-Ins

Apple had one of the most successful TV commercials of 1984, reminiscent of Orwell’s novel, “1984”. In it, Apple reacted to IBM’s explosive PC success by depicting IBM as “Big Brother” and Apple as the champion of freedom-seeking consumers.

In many ways this commercial was extremely ironic, for it was IBM who (naively as it turns out) introduced its PC architecture with off-the-shelf components, making it one of the first open platforms on the market; whereas Apple was, and continues to be, a fanatical proponent of their own proprietary, closed architectures.

Now, we mustn’t fault Apple for this. After all, its strategy to control its architecture and application interfaces as well as with its application marketplace has benefitted it handsomely (Apple was recently credited for being the second most valuable company in the world!).

The truth is that, from its inception, the information systems industry has undergone cycles of alternating dominance between proprietary and standardized technologies. It’s practically a law of nature that, as soon as a new technology emerges, you find vendors rushing to compete by providing unique, value-add approaches that usually fail to inter-operate with other vendor platforms; thus seeking to lock you in to their particular product offerings.

This tug of war between closed and open systems has occurred at nearly every level of the computer stack, beginning with hardware designs, operating systems (MVS vs UNIX/Linux), languages (PL/1 vs C), and networking technologies (IBM’s SNA or the now-defunct DEC pushing Decnet, as examples), up to the more recent middleware, content and presentation standards .

The inclination of vendors to capture markets via their own technologies is understandable, but standardization has actually benefitted vendors by ultimately expanding the reach and penetration of potential markets. Standardization usually won out in the past but, on occasion, it failed to materialize, resulting in the loss of market opportunities. For example, a few years ago Instant messenger was poised to take over as a communications channel. However, AOL’s refusal to open its chat protocol to standards made IM interoperability both complex and impractical. While Email’s MIME standards allowed us to exchange emails regardless of the email software or ISP we happened to be using, chatting with someone with a Microsoft account from AOL was extremely difficult and usually required additional software. Instant Messaging failed to become as pervasive as email, proving that the refusal to adhere to standards can also kill a leading vendor’s hopes to profit from a given market.

Interestingly we are now entering a phase in which proprietary systems are beginning to gain an upper hand. Facebook has become a worldwide community but, in a way, it is also a gigantic walled-garden intranet—the type of environment that AOL once aspired to become. Indeed, it is disturbing to see companies now advertising their Facebook addresses rather than their Web site addresses. The kind of lock Facebook is acquiring may well be impossible to break other than through future legislation. At the very least one could expect regulations intended to protect the access and privacy of the users as well as clarification regarding ownership of intellectual property posted on these types of social sites (as of now, almost everything you post in Facebook, including your pictures, your art and your writings could be owned by them).

Apple, on the other hand, is successfully extending the concept of AppStore for all Mac applications; not only for its iPhones. If you have ever tried to place an iPhone application in its AppStore you know that the process is akin to trying to go through airport security dressed up as a mujahedin (pat downs, included!).

Microsoft is now realizing the huge opportunity it missed out on by failing to create an “MS AppStore” of its own, offering “certified” Microsoft based applications for a fee (it is now attempting to do so). In retrospect, Microsoft’s failure to monetize its brand and create a common marketplace for all Microsoft certified applications seems like a multi-billion dollar lost revenue opportunity--not that Mr. Gates is hurting, mind you. Thankfully, consumers benefitted from the breadth of MS-based product available in the open marketplace (alas, they also suffered some negative consequences in the form of viruses and sub-par products!).

From a technology perspective, IT has gradually moved up the stack in the cycle of technology commoditization. The new standardization frontier (battleground, some would call it) is at the layer dealing with presentation, application flows, and content. I have no doubt that technology will soon make those layers also amenable to standards, but the kind of lock-ins that we will face in the future will be mostly commercial. In other words, “Lock-In 2.0”. The AppStore concept is an example of the commercially based lock-in that’s sure to receive further traction in the near future. This type of lock-in has the potential to be even more fastidious if the Telecomm-sponsored proposals against Net neutrality succeed.

Other than through the unlikely case of government regulation, the only real possible escape from heightened dependence to the likes of Facebook or Twitter is the eventual emergence of open source alternatives—something akin to Wikipedia. But the most likely outcome is that the next standardization push will take place within the confines of such environments. Let’s face it; right now it’s hard to envision an “open source” alternative to Facebook that will have the reach of users and content that that space currently enjoys.

Still, there are things you can do to preserve some modicum of leverage on behalf of your company. When it comes to technology lock-in, you can be certain that using SOA is the best antidote against dependence upon a proprietary vendor platform. However, large vendors are quickly coming to realize the best chance they have of locking in a particular customer segment (i.e. You) is via the use of marketing restrictions (i.e. Commercial Lock-In). You’ll need to place the focus on how best to protect your company against this. It’s not enough to make sure your team configures the system with the right interfaces; you should also take a deep look at your vendor contracts and the state of the industry in order to ensure that the small print in your purchase agreement does not prevent you from integrating alternative vendors or forces you to surrender your intellectual property rights.

When it comes to integration with sites such as Facebook or Twitter, do so in a loosely coupled manner (don’t forget to use services!) To the extent you can, don’t get too immersed in their technology choices. Build your business logic, content and data sets outside their specific development frameworks and hook to them via simple APIs (application programming interfaces) only . Finally, advise your marketing team to please advertise the company’s Web address and not its Facebook address! You can always place the Facebook, Yahoo or Twitter addresses as links within your web site.

Considerations on Experience and Expertise

If you are going to build a star team capable of delivering SOA systems, you will need to ensure the right mix of skills and experience. Just as in a good gourmet recipe, you will need to gather the proper ingredients and bake them together just right to achieve the desired outcome.

In addition to the more karmic aspects of this team formation: style, culture, motivation and focus, the element I believe to most define the likelihood of success is experience. The question that then arises is this: What, after all, is experience?

My older brother told a joke about a man showing up for a job posting. “How long have you been working in this role?” the interviewer asks. “I have never worked in this role,” the applicant answers. “Then why are you applying for the job?” The applicant pulls out the want ad he had seen in the newspaper and points to it. “Well, at the bottom of the Help Wanted Ad you wrote, ‘Useless to show up without experience.’ It just so happens that I have no experience and, according to my wife, I am quite useless.”

This story aside, experience is not something easy to define. Just as the US Supreme Court refused to define pornography, experience is something usually identified with the, “I’ll know it when I see it” mantra. For starters, let’s be candid and agree that experience is not necessarily what resumes claim it to be. The quality of the experience matters. How many times have you met someone who claims “thirty-year” experience when, in fact, what they have is the experience of one year, repeated thirty times? Also watch out for resumes claiming experience-by-proxy. You know, the “I am not a doctor, but I play one on TV” kind. You can identify these pseudo-experiential claims under resume sentences that read like this: “Worked with the team that developed XYZ” or “I was there when NASA placed a man on the moon.”

Furthermore, given that our objective is to build a team that can build and operate a world-class SOA system, experience is actually pointless if it does not lead to expertise. Herbert Simon, Nobel Laureate in Economics, and one of the pioneers in the field of Artificial Intelligence, stated that expertise was the ability to do a task at least three different ways. When I lived in New York, I knew of only one route to get to La Guardia from my home. However, a good cab driver knows the detours to take when traffic is jammed. (I know, today’s Navigation systems can help me match the capabilities of this cab driver—technology can be a substitute for experience).

Assuming good-quality experience, then it can be measured in terms of years of practice. According to some popular books on the subject (“Blink” by M. Gladwell, for instance), anyone can become an expert at anything by simply practicing and practicing and practicing. Interestingly, the point is made that the magic number of practice hours needed is about 10,000. I may agree with that estimate, but those quoting the study also refute the existence of natural talent under the “anyone can be a Mozart” argument, “if only they practice as much as Mozart did”. As someone who has practiced guitar for eons and who listens with envy to the virtuoso guitar playing of an eight year child prodigy (http://www.youtube.com/watch?v=NMnw7CcWO7E), I couldn’t disagree more. Still, if we ignore those savants as outliers for the sake of discussion, a 10,000 hour period represents a minimum of five years, assuming forty hours a week. This means that, unless you are a natural prodigy, you should expect it to take five years of practice (and in my book practice equals experience) to become an expert at something.

Experience can be quantified, but expertise is somewhat more ethereal. Back in the eighties, a class of software known as ‘Expert Systems’ made its appearance. This software was intended to replicate the knowledge of experts. The idea was to “reverse engineer” this knowledge via a series of heuristic rules that could then be made accessible to the rest of us mortals. As one of the most committed practitioners of this idea, I was actually able to experience the difficulty of this endeavor. First, to have experts explain how they arrived at their conclusions was more than difficult, if not downright impossible. Oftentimes, experts couldn’t even explain how or why they reached the conclusions they did!

Fact is, deep expertise is all about moving knowledge from the realm of the conscious to the realm of the intuitive; not unlike when learning how to drive makes us no longer think about the mechanics of driving. True knowledge is embedded knowledge; knowledge that has become part of our core mental fabric. Yes, Expert Systems can encode and replicate some basic If-Then-Else rules, but true expertise is often expressed by flashes of insight that are not so easy to explain, let alone dissect.

If you are familiar with the TV show House M.D., you know about the show’s leading character uncanny ability to diagnose a variety of obscure diseases thanks to his insights. President Lula of Brazil , who just recently stepped down after eight years as president with an 87% acceptance rating in the polls (imagine that!) was asked about his secret to governing. His reply: “Good government is simply the art of doing the obvious.” Of course, that’s easy for him to say. What is obvious to him may not be obvious to the rest of us. This is what made him by all accounts a great president. Stating the obvious is something we all try to do. And therein lies one of the main issues in accessing the services of true experts: It is practically impossible, at first, to differentiate the insightful advice of a true expert from the opinionated shallowness of a fool. A know-it-all fool can at times sound like an expert. Witness those cult leaders who frequently lead their followers astray with the decisive and resolute way in which they express their convictions.

But I digress. . .

You can weed out the shaft from the gold by becoming an expert at recognizing expertise. If someone claims experience in something ask them about it. What logic, constrains, rationale did they use in solving problems in the past. Get specific examples of their past performance. Evaluate their decision-making logic. Assess these and other thought-process aspects; and do not just focus on the number of years of claimed experience.

You should be just as careful when selecting the type of experience you wish to acquire in your team. Forming a great SOA team is not unlike forming a championship-level football team. You’ll need it all: the agile quarter back able to scramble and throw the ball far, the quick receivers, the strong offensive line and even the flimsy-looking field-goal kicker. Like a good football team you will need a variety of talents. The one resource with the Doctor House-like knack to quickly resolve system outages is not likely to be the one person who introduces innovation. The project manager with the ability to sense drifting timelines is much needed, but do not expect her to figure out the types of SOA services to write. The programmer able to draw up complex algorithmic code is a key resource, but he won’t be your go-to person to define the best quality assurance processes. Think of the natural leader who can motivate the team into action as someone priceless, but don’t expect her to excel at keeping track of the written status reports.

Mix the team with a variety of experiences. Remember, there are people who have a great deal of knowledge in very narrow areas (do make sure that the degree of specialization is not so narrow that you end up with someone who knows everything about nothing!) and those who have knowledge covering a wide range of areas, although their knowledge in each might be shallower. Try to have a reasonable mix of these two types of knowledge holders, and dismiss the ones who claim deep knowledge about everything. Those are the fools I referred to earlier.

For some key areas of expertise, it is and recommended to have some redundancy (the best football teams have a great second-string quarterback). In these instances, you will benefit from getting differing viewpoints from more than one expert and will be in a better position to reach you own conclusions to help decide courses of action. Having this kind of depth of expertise is not really feasible in all areas, but you should try at least to having it in the group responsible for overall architecture decisions. Lastly, make sure you integrate some bright, inexperienced talent in your group. In addition to helping you build your team for the future, having this type of resource will give much needed fresh perspectives. Potential experience can be as valuable as actual one!

In the complex world of SOA, uniformity is not bliss and experience morphed into expertise does matter.

The Web 3.0 Myth and the Emergence of New Channels

In a scene from one of my favorite movies, the cult mockumentary, “Spinal Tap”, the lead guitarist proudly brags about his amplifier. “This one is the best gear, there is,” he says. “Why?” the off-camera voice asks. “Cause this one’s volume knob goes all the way to 11, see?”

The guitarist goes on to explain that on most amplifiers the volume control has only ten notches, while this one has 11.

When I hear the term Web 3.0 being used, this Spinal Tap scene always comes to mind. “Web 3.0 is better ‘cause 3 is higher than 2, see?”

When the WWW was invented, the first web pages were basic experimental pages of the “Hello World” variety. Soon pages began to sprout up with an informational focus—simple descriptions about the owner of the page with some images—to the point that by 1995, the vast majority of Web pages were the equivalent of the About Us section on most web sites.

Search engines and web indexers began to appear too. Soon, Web sites began to exhibit a measure of interactivity. Users were able to enter their information on forms and submit them to the web owner. The next logical step was transaction oriented services. This saw the emergence of travel reservation sites and the beginning of serious online commerce. The rest is more contemporary history. Someone came up with the brilliant marketing term “Web 2.0” to highlight the emergence of social networking sites. Not that Web 2.0 represented a true technological breakthrough. When you think about it, sites like Facebook and Linkedit are essentially template-driven, personal web pages that can get created and maintained without the user having to learn stuff like HTML or XML. So, in summary the progression of the Web has been as follows:

· First Wave: “Look at me.” In this wave the early adopters created quick pages by directly editing HTML files and entering fairly innocuous entries intended to establish a presence.

· Second Wave: “Let me Inform You.” Some advanced companies and most of academia published their web pages with descriptions and bibliographies intended to inform their readers. Around this time, the rush to grab domain names began.

· Third Wave: “Please tell me.” Forms began to be used for the purpose of asking the reader to enter his name and contact information or to provide comments for follow up.

· Fourth Wave: “Transact with me.” Some audacious companies began to expose their product inventory. The gradual adoption of the SSL (Secure Socket Layer) protocols combined with web encryption enabled people to trust the Internet as a carrier of credit card information.

· Fifth Wave (Web 2.0): Get Involved. Initially, sites facilitating the creation of Blogs made it easier for the more extroverted among us to begin publishing our tales without having to actually understand the technical elements of Web page construction. Sites like MySpace, Friendster, Linkedin, and Facebook took this paradigm further by creating communities that enabled people to expose their likes and dislikes, profiles, and comments in a structured fashion.

What will the next Web wave be then? The putative Web 3.0? I don’t believe so. There will not be a Web 3.0 anymore that there truly was a Web 2.0. However you care to define this eleventh notch for the Web, the fact is that the Web is in the process of becoming a hidden commodity, a utility like TCP/IP, the networking protocol used to power the Internet.

Just as the Cambrian era saw the rapid proliferation of diverse sea creatures undergoing an evolutionary frenzy, we are now witnessing the emergence of the “End Point as a Channel” phenomena. For example, until recently, making web content available to cellular phones used to be an after-thought. Nowadays, the popularity of smart-phones, whether iPhone, Android, Blackberry or Windows based, is making it obvious that these devices represent a brand new distribution channel. Where we once had Web pages we now have “Apps”. The burgeoning success of emerging Tablet devices will only shift this paradigm even more.

In a recent article, Tim Bernes-Lee, the inventor of the Web, expressed concerns that Facebook, iTunes and other social networking sites were counter-currents to the WWW, acting as walled-garden sites and ultimately running against the philosophy of openness and sharing that underpins the Web. True, the earlier AOL was a walled-gardened community that became obliterated by the emergence of the open worldwide web, but it now seems that we have come full circle. Closed communities are the “in” thing, and the Web is seen only as the common ground. You may even have noticed that some companies no longer put their web site URL in their advertisements, preferring to list their Facebook page instead. Still, this does not mean that the Web will go away; nor that email is likely to disappear, despite the recent claims that it is being used less and less due to the heightened use of internal messaging systems available on social sites. Instead, we should view the recent emergence of “Social Networking” sites and other content delivery mechanisms as the new apex in the IT services pyramid.

What has actually been happening is that, as the Web has become a commoditized infrastructure component, it is no longer the one information channel. The Web is now simply the distribution channel of reference amongst the many channels in the exploding variety of information and distribution channels. The diagram below depicts this paradigm shift.

What does all this mean to you as a system architect? Well, basically it reinforces the importance of creating a layered services oriented architecture that allows you to support, with a minimum of effort, any channel the world throws at you. Aside from the presentation layer, you should avoid developing channel-specific components. Content Management, Merchandiser Engines, Security Servers, and all other backend infrastructure should be capable of operating on a channel-agnostic manner regardless. In addition, this new world reinforces the value of exposing the backend services via SOA and the importance of establishing the right infrastructure, capable of supporting a variety of SLAs and security modes at the boundary between the internal systems and the exploding channel zoo. Aren’t you glad to moved to transform your IT systems after all?

Information Distillers, Aggregators & Your Electronic “Mini-mes”

As the years ahead move us toward the enabling of understanding and wisdom, we should expect an increase in the commercially available services leveraging these new automation models. For example, consulting is already an embedded part of services provided by professionals, but in the future, consulting will evolve into a set of online services provided via moderated access to human experts or via the access to software-based expert systems. Whether they are made of flesh or metal, these will be bona-fide Information Distillers will always be ready to augment your thirst for information at the push of the button and the opening of your Pay-Pal wallet.

Emerging Information Distillers will successfully locate and turn the required information into “understandable bits” which can be digested by customers under several revenue models. While in principle these services are not fundamentally different from those provided by traditional consulting entities such as the Gartner Group or your corner H&R Block, the difference is that they will be democratized and available to all—individuals and companies alike. For example, in travel, distillers will not only publish travel magazines (electronically or via hard-copy), but will also package tours and offer special negotiated travel deals. (Tripadvisor.com can be seen as a first generation distiller leveraging the power of social networking.) However, information distillers in the future will be able to provide personalized advice either from paid human experts or from next generation expert mining tools.

As electronic commerce becomes more pervasive, and the speed and specialization of business increases, proxies or electronic avatars will become more prevalent. Functionally, such an avatar will not be much different from today’s travel agency role when booking travel for a client. However, whereas today’s agencies do not truly represent the interest of the traveler (agencies, in principle, represent the interest of the supplier), future avatars will act as your proxies—your electronic “mini-mes”—working automatically under business and engagement rules that you’ll define in order to be presented with the best deal.

As artificial intelligence becomes mainstream, and as technical standards facilitating electronic brokering are implemented, these avatars will become virtual software entities capable of representing you, the consumer. Eventually, avatars will completely broker and execute the best possible arrangements for you.

This type of avatar is already a reality in the hectic world of electronic trading, where complex software algorithms make nanosecond level decisions on whether to buy or sell stock assets. From this world, we should be forewarned that, as proxies become more commonplace, we must be prepared to face the consequences of relying too heavily on software avatars endowed with automated decision making permits. On September 7, 2008, in an already volatile and jittery financial setting, a Florida newspaper accidentally entered an old web article detailing United Airline’s 2002 bankruptcy. Google, all-obligingly, indexed the article and distributed it to e-mail subscribers who had requested alerts on any news regarding this airline. This is where automated software proxies took over. The stock trading software scanned the article and found the keywords “bankruptcy” and “United Airlines” and automatically ordered sales of UAL’s stock portfolio. Other software robots, responsible for monitoring unusually large trade volumes in the stock market, quickly took notice of the sudden sale of UAL stock and proceeded to sell their stock. The outcome was a selling frenzy that resulted in more than one billion dollar loss to UAL stockholders. The Securities and Exchange Commission began an investigation to determine responsibility. After all, who is at fault? The Florida newspaper? Google? The developers of the software? The companies that transact stock in such a perilous manner?

Clearly, we are entering a brave new world that requires added protocols to safeguard software agents going rogue and to answer the myriad concerns related to protection of privacy; not to mention the expected security issues related to fraud and software impersonators, with the logical progression to identity theft. In the meantime, if you are in the supplier’s side, you can start designing your systems to enable this future “Electronic Mini-Me” concept. Define and be prepared to have the appropriate services and architecture layers that can leverage the deployment automated selling brokers.

As you define this architecture, you will have to rely heavily on the implementation of publish/subscribe systems and asynchronous response patterns. You will also need to focus on implementing a sophisticated combination of Business Rules and Business Process Management based systems that can allow your business team to easily configure and define the automated way broker services will be made available to your customers. For example, these brokers could be configurable to making distressed inventories available electronically and able to dynamically price on-line offers with available inventory via dynamic revenue management rules as applicable. Think of how an electronic auction process in eBay.com works but on steroids.

Just as the electronic avatars discussed here are a practical instantiation of the move towards cyber-understanding, future systems applying basic rules-of-wisdom will emerge. True, Wisdom will always be a purview of humans and not computers. However, following the precepts of “Wisdom of the Masses”, we are now experiencing the benefits of the wisdom provided by virtual communities; areas where we find reviews in a broad range of areas, “How-To” tips, and better deals. A case can be made that this wisdom is an emergent property, resulting from the aggregation of large catalogues and information, and the associated tie-in of user areas and access to content. These areas are best represented by “Virtual Malls” such as Yahoo.com, Overstock.com and Amazon.com, but are also expected to rapidly merge with social networking sites in the so-called Web 2.0 world.

There is already a linkage between merchandiser sites and places such as Linkedin.com, MySpace.com, and facebook.com. This integration will ultimately occur via business partnerships or mergers, but it will be initially accelerated by automation known as Collective Intelligence, the process that combines the behavior, preferences or ideas of a group of people or sites to gain new insights[1].

Analogously, it is to be expected that, as this vertical industry matures, we will continue to see the emergence of portals specialized according to industry. That is, we will see “electronic virtual malls” integrating offerings on the one hand, and acting as “aggregators” dealing with the specific industry groupings. The aggregators will be able to convert the volumes of data found on the Internet into useful information. This information will be presented in a form which will be customized for information seekers as a consolidated package of knowledge. The automated assembly of related knowledge designed to fulfill the "seeker's" goals can be related to the area of specialization of the site. This trend will be evident first in consumer-facing verticals such as travel sites Expedia.com, TripAdvisor.com, Travelocity.com and various other special-domain sites such as MusiciansFriend.com and WebMD.com. The question you’ll need to answer is how to make your company part of this new world?

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[1] Programming Collective Intelligence—Toby Segaran

Data, Taxonomies, and the Road to Wisdom

In earlier days, computing was all about “Data Processing”. However, with the progressive sophistication of hardware and software, the term “Information Systems” started to become more prevalent. Initially the platonic ideal was to eventually have computers process the world’s information the same as humans do, except much faster. This goal was known as AI (Artificial Intelligence) and during the eighties there was a string attempt to apply this objective to narrow domains of expertise under the guise of “Expert Systems”. Expert Systems went through a hype phase only to fade away as we came to learn that the heuristics needed to replicate the way humans process and organize knowledge is dependent on contextual and even subjective, uncodifiable information rules. In other words, we humans process knowledge in a way that is often inaccurate, biased and intuitive, but that it is acceptable to our normal existential needs. Automating our style of “fuzzy” logic will give us computers with the capability to err just as humans do. Computer results that are mostly accurate, but not always correct, would not be a desirable outcome for someone spending millions of dollars on systems. No. Information interpretation and expert understanding will remain a human chore for decades even as computers continue to better facilitate the rapid analysis of data.

By now, you have probably noticed that I have been using the term “Information” in its most generic sense. Information can often be “misinformation”. Yet, misinformation and even lack of information are, ironically, forms of information (a dog that didn’t bark gave Sherlock Holmes a clue with which to solve the crime). When implementing information systems it does help to classify the type of information we are dealing with. We should be able to define the most appropriate ways to acquire it, handle it and interpret it. In order to do so, we can make a distinction between the concepts of Data, Content, Knowledge, Understanding and Wisdom. Each of these concepts represents a progressive evolution in the quality of the information and, on the road to Wisdom:

1. Data is primarily raw figures and “facts”; by nature it is voluminous and difficult to cope with, and so it is best stored and communicated in a mechanical way. There is nothing implicit in the concept of data that makes it right. Data can be completely wrong. The old GIGO adage (Garbage In/Garbage Out) captures what ought to be the highest priority in the automation of data: ensuring that the data inputted into the system is correct.

2. Content is data that has been collated, ordered and classified. That is, Content is Data plus its Taxonomy. As such, content possesses a higher level of value than raw data, particularly as the relationship between different sets of information is leveraged for increased quality and ease of maintenance.

A note of clarification, Ontology is a specification of the characteristics of a domain:

o Things that begin with the letter D

o Animals that have four legs

o Things that are used to write with

o Children toys

Ontology is what you apply when defining your data sets or when identifying the database schemas you plan to create. Taxonomy, on the other hand, is the categorization or classification of entities within a domain. Consider the following taxonomies used to describe the animal kingdom.

Linnaeus Taxonomy:

· Kingdom: Animals, Plants, Single Cells, etc.

· Phylum: For Animals: Chordatas, Nematoda (worms), etc.

· Class; mammals, amphibians, aves. . .

· Order: Carnivorus, cetaceous. . .

· Family: Ursidae (Bears), Felidae (cats), Canidae (Cats). . .

· Genus. . .

· Species. . .

In "The Analytical Language of John Wilkins,“ Jorge Luis Borges, the famed Argentinean writer who belongs to the ontological set of writers who deserved to win the Nobel Prize but didn’t, describes 'a certain Chinese Encyclopedia,' the Celestial Emporium of Benevolent Knowledge, in which is written a taxonomy in which animals are divided into:

· those that belong to the Emperor

· embalmed ones

· those that are trained

· suckling pigs

· mermaids

· fabulous ones

· stray dogs

· those included in the present classification

· those that tremble as if they were mad

· innumerable ones

· those drawn with a very fine camelhair brush

· those that have just broken a flower vase

· those that from a long way off look like flies

· others

As you can see, there are many ways to define taxonomies. It is the responsibility of your Information Architect (you have someone in this role, don’t you?) to ensure the agreed taxonomy relates to your line of business. Once you define and apply the taxonomy to your data, you have Content. With the advent of the Web, we have moved from the Age of Data to the Age of Content. “Content is King” is more than a cliché. Content was the engine that generated the fortunes of companies such as Yahoo and Google.

Until recently, the key differentiator between a popular and less popular web site has been its availability of content. But Content requires skilled use or the expenditure of considerable time to extract this value. It is an area that most companies would do well to handle in a structured manner. Dedicated content management groups should be part of the modern governance supporting your company’s information systems today.

3. Knowledge is what is produced when the information is placed in context and the resulting significance of relationships within the data is realized. The addition of contextual information requires some element of human input; so the progression to this stage will probably never be possible with the use of computers alone. If you want to see the difference between Content and Knowledge, I suggest you try this exercise: Go to google.com and enter “IBM Apple”. You will get content listing all sites where IBM and Apple are discussed. Now, go to wolframalpha.com and enter, “IBM Apple”. You will get a digested and structured response as to how these two companies compare to each other. The former is content, the later, distilled knowledge.

Production and discovery of knowledge are a large part of many industries today. Organizations such as Gallup exist to mine data and content and produce knowledge on a variety of topics. Voting trends, consumer preferences, etc. are examples of mined knowledge. Business Intelligence, associated Data Mining technologies, and the more recent Internet-driven “Collective Intelligence” applications are examples of the more recent trends in the automation of knowledge acquisition. We are on the verge of moving from the Age of Content to the Age of Knowledge.

4. Understanding is realizing the significance of relationships between two or more sets of knowledge and deriving prime causes and effects from this knowledge. While Gallup may unearth the knowledge that 33% of voters are likely to vote for a particular candidate, the understanding of why they lean that way is something that information systems today can only hint at. Understanding remains an endeavor only humans are adept at. Understanding cannot yet be performed by computers. Understanding is how pundits and large consulting/advisory outfits make their money. Companies like Gartner or your typical TV pundit, or writers of popular science or “How To” books are giving you distilled understanding.

5. Wisdom is the ability to choose from good understanding and faulty understanding. The fact is that understanding can be the result of wrongly extracted knowledge, which may come from bad Content or Data. In his mind, Hitler “understood” that he had a “Jewish problem”. Needless to say, his understanding was the result of bias, prejudice and cooked up analyses. For all his earthly power he was the most unwise of men.

Wisdom represents the highest level of value in the information progression. Wisdom is not always objective or static. It can be subjective or dependant on the cultural environment or transitory circumstances. That’s why it is unlikely that we will ever be able to codify wisdom within computers and why the idea that these future computers may act as judges is not feasible.

Wisdom can be applied for material or spiritual benefits. Yes, Wisdom can be applied for profit and business advantage. However, just because something is understood correctly, this does not dictate whether it is right or wrong. Beyond wisdom we enter into the realm of morality and philosophy and what might be wise choices to some, can be immoral to others.

But I digress. . .

Whether computers in the future will be capable of Understanding (much less Wisdom), is open to debate. There is much we do not know about how we humans think nor about the nature of our cognitive processes. What’s certain on a more pedestrian level, is that you can use the taxonomy of information to help you distinguish between what’s data and what’s content, in order to better map the specific goals and governance of your information systems. That’s a start.

On Software as a Service

True, the traditional view of software commercialization may go the way of the slide rule and the typewriter, but there will always be a need for the services that software provides. However, the ability to access software services depends heavily upon the enabling of shared infrastructure from companies providing hosting, data storage and networking and telecommunication services. This infrastructure should continue to move towards standardization to facilitate the kind of “plug-and-play” flexibility the market demands. The ongoing standardization of emerging “middleware” technologies supporting distribution and access of services via service interfaces will have an impact comparable to that of the world-wide-web.

Software as a Service (SaaS) is exploding nowadays. Google’s application suite is an instance of SaaS providing generic horizontal services. Function specific products such as GoTo Meeting and WebEx for meetings along with Sales Force Automation, a more focused horizontal SaaS tool have been gaining significant market share over traditional competitors. This explosion also includes vertical industry applications. Thousands of hotels use TravelClick for reservations; the health care industry has hundreds of SaaS applications for patient management, ambulance services, etc. Plus remember, ultimately, Facebook and Twitter are nothing more than social media SaaS environments.

Despite all of this, SaaS is not a panacea—at least not yet. The model has to mature and as a result, the range of options, costs and enrollment mechanisms is still too varied and complex. Most significantly, SaaS systems need to find the right balance between functionality and flexibility; plus the model presents a list of new security considerations. Are you comfortable having your company’s most sensitive data out there, somewhere in a cloud?

Take heart though, standardization breeds commoditization, and a result of standardization is that in the future there will be a consolidation of service models and expected features. This consolidation is also being facilitated by the emergence of the “Cloud Computing” model that essentially makes the infrastructure services supporting SaaS invisible to the user. Large vendors are already introducing sophisticated virtualization, security, and management tools that will enable SaaS providers to offer an expanded range of configuration and portioning models to their clients.

But SaaS does not necessarily need to be wholly based on a centralized service delivery. The paradigm also applies to distributed services such as those provided to smart-phones. Already the paradigm for the booming smart-phone market is that of downloadable “Apps” with modules providing functions. Some Apps run entirely standalone, but others provide a front-end that can access powerful backend systems. Google is making available a suite of shopping Apps that instantaneously leverage the powerful Google server environment displaying reviews, alternative prices and so on. The popular Shazam is a complex application that tracks and recognizes tunes being played, and there are a myriad of widgets for all kinds of things. The user, particularly the younger user, no longer views these Apps as software. The kid downloading a ring tone is not buying software or data but a experience. The fact is that many of the Apps providers are now moving away from straight purchase models and toward service subscription or ad revenue models.

Now, so far I have discussed that the SaaS paradigm appears to be a consumer of services. The question is how will your company fit the upcoming Infosphere economy and how will this impact your very own IT strategy. What kind of SaaS is your company planning to offer, if any? When you envision the IT system of the future, you need to ascertain how you are going to play in this brave new world, as a provider of software services, a user or both. This includes defining the manner in which you will make your IT services accessible to users. When doing this, you will be glad you followed a comprehensive SOA strategy as the baseline for the IT transformation.

In a way, SOA is a necessary (tough not sufficient) element for the habilitation of SaaS. SOA systems intrinsically create services that can be selectively commercialized under SaaS. The SOA services become SaaS services. In other words, the concept of Software as a Service will evolve into the more prosaic “Service as a Service.” This statement seems obvious, but it has deeper implications . . . a complex SOA system may well consist of an interplay of components. For example, Provider #1 of service S1 may access a second service, S2, from provider #2r #2, who may depend on service, S3, from Provider #3, and so on. The user needs only sees the integrated service provided by provider #1 and can be oblivious of the value chain behind the original service request. In essence, SOA enables the replication of the way traditional value chains operate, except now we are using digital means. Just like real markets, SOA systems can become incredibly complex. Their support has to be structured in such a way to allow quick resolution of issues presented by complex, intertwined value chains. There has to be clear accountability lines.

Having said this, I am doubtful that mission-critical IT systems should ever rely entirely on external SaaS services. I firmly believe that technology; some technology anyway, will always be a weapon to attain commercial advantage and to enhance one’s competitiveness. Don’t buy into the idea that all software will become so commoditized that it will be something you can always provision externally—a simple utility provided by SaaS. General purpose business software such as ERP systems? Use them as a commodity. These systems do what they do. Being able to process payroll or accounts receivable internally is not going to give your company a competitive advantage (I am sure though there are exceptions to this!) But there will always be that little extra function, that cost cutting algorithm or automated innovative process, that will not be available externally, either because it represents a core intellectual property asset of the company or because the cost or risk of placing it in a external environment is not acceptable.

The question then is “What services should you endeavor to create rather than purchase?” The answer to this question depends on an analysis of what are you trying to get out the service: Data? Content? Wisdom? More on this next…

The Emerging Business Models in Information Technology

Until recently, the traditional IT revenue model landscape was a rather trivial one. You had your vendors—the companies that developed software or hardware products for use by other companies— and then you had your clients who consumed those products through straightforward purchasing or licensing along with yearly recurrent maintenance payments. On the side you had consulting companies that served as honest brokers that helped to define high level strategies. Add to this the providers of ancillary services, and you end up with most of the IT world of yesteryear.

This simple scenario is no more.

Emerging IT technologies and solutions are now being offered under a cornucopia of models; many of which are only now beginning to be understood. Beyond the “pay-if-you-can” models spawned by the availability of Freeware, Shareware and Open Systems, the future will see the delivery of software under a variety of revenue models, including Software as a Service, Software as a Function, and ultimately the probable disappearance of software as a standalone product. Software-under-the-Hood represents a mindset shift wherein consumers are no longer buying software but rather the things that software can do. Companies providing these services will use a variety of revenue models: free plus maintenance, one-off purchasing, subscription, advertisement, charge per utilization, on demand among others.

Google, for instance, makes the bulk of its revenue from advertisement; not from selling search software. Likewise, eBay’s revenue model is based on its auction facilitation and commissions. Facebook’s revenue model has flipped the world from what was originally the customer (i.e. Facebook friends) into the actual product sold to advertisers (i.e. you, my friend, are the product!). The generalization of SOA and the emergence of more sophisticated technologies will facilitate the drive to offer services rather than software. After all, subscribing to WebEx may give you the chance to download a client-side software module, but what you are ultimately paying for is the ability to schedule meetings on demand.

Mix this recipe: pour a liter of globalized Internet seasoned with Cloud Computing; add a cup of SOA facilitated Software as a Service and a couple of spoonfuls of Business Process Outsourcing, heat with the mobility technologies and spice with the growing success of social networking as the new killer-app. What you’ll gave is a dish representing the transformative emergence of new players providing yet unheard of business services. Already, it is difficult to categorize Facebook or Google under traditional definitions. In the future, the roles played by Microsoft or IBM will still exist, but even traditional software companies realize the need to reinvent their product and business model if they are to better compete under a continually changing landscape. The future will also see the disappearance of some of the typical roles in the value-chain (witness the demise of brick-and-mortar electronic companies such as Circuit City or CompuUSA), and more importantly, the emergence of newer models, redefined to be better fit the changes in information economy. This type of change can only be ignored at the risk of the company’s survival. If you doubt this, recall Wang Laboratories and its Word Processing flagship product as it faced the PC revolution, Polaroid as it confronted the digital photography revolution or Blockbuster in the process of being busted by Netflix (pun intended!).

Just as earlier software models were based on the “a computer on every desk” idea, or the importance of search, or some other insightful tenet, the next Bill Gates, Larry Page or Mark Zuckerberg will most likely be a child of what has been referred to as “The Infosphere[1]”. The Infosphere is the paradigm that all informational elements will be accessible from the electromagnetic digital media around us. You can think of the Infosphere as 3G or WiFi coverage on steroids: ubiquitous, always available, and transparent. It will be the natural result of the pervasive advent of cloud computing and the continued decoupling from specific access devices[2].

Recall some of my earlier observations about how technology usually “evolves” from hype to invisibility as it becomes pervasive. Unlike Wired Magazine’s recent claim that the Web is dead (at least from the perspective of the Web Browser as a universal client) I believe that the Web is very much alive. It’s just that it is evolving into invisibility.

While the Web Browser is now embedded in the hidden fabric of technology, the delivery of new applications and content for new mobile devices on a demand basis, anytime, anywhere, is also becoming an assumed capability. There is an umbilical cord being formed between most of the world and the emerging Infosphere.

Already the rapid adoption of technologies such as Apple’s iPhone and other Smartphones can be seen as earlier examples of this Infosphere. Mobile devices are today’s equivalents to the PC’s of yore, computers that you can carry with you at all times—prosthesis for the brain. Using these devices to interact with the Infosphere from anywhere, at any time, is not a longer a technology question but a commercial one. If only phone carriers did the smart thing and lowered those outrageous data roaming charges!

Here we return from the digression of the topic. The key now is for someone to figure out the right revenue models to apply in the future Infosphere. Data roaming has got to go, ads on Smartphones might be fine but I doubt the revenues they generate will help pay for the totality of the mobile services. Subscription or membership fees to social communities may emerge, who knows… In the end, much will depend on what will become the killer apps and services in the next few years. Figuring that out is the key.

How to do this? Remember the suggestion I made about how best to predict the future of technology? The secret is to find the synergy. That is, to visualize the usually unforeseen ways parallel advances will combine to form a new game changing event.

Find the synergy, especially as it relates to the impact the future may have either on your business or your IT strategy, and you will be on the road to defining your follow-up transformation strategy. If you agree that we are in the midst of an accelerated transition to an Infosphere paradigm, then it makes sense to try to imagine what the likely future business opportunities of such transition will be.

More on this next time . .

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[1] Even though the term “Infosphere” has been around for a while (according to Wikipedia, since the sixties), it should be noted that IBM has recently created an Infosphere brand for one of their Information Management software products.

[2] A more esoteric term “Noosphere” has been used to describe a future global sphere of shared human thought—a sort of collective consciousness of human beings. I suppose some nice essays could be written on how the evolution and use of the Infosphere could be the technological enabler for a future Noosphere!