Richard Veryard on Computing

A Long Shot?

2009-11-03T10:27:00.002Z

William Hill, the UK bookmaker, is offering odds of 1000/1 on the possibility that the latest footballer baby will become prime minister. (News Release 3 November 2009)

Anything's possible, I guess. But from an IT perspective, my first thought was for the extraordinary cost to William Hill of this publicity stunt. Given that people can become prime minister at any age, William Hill is going to have to maintain records of these bets for at least seventy years. What are the lifetime IT costs of this commitment? Not cheap.

I suppose the upside for William Hill is that the punters will have to stay in touch with William Hill for the duration.

I have no idea whether the planners at William Hill thought through the implications of this, but there are too many organizations where the IT implications of an apparently minor business decision would not have been considered until it was too late.

Further clarification having discussed this with @EnterprisingA on Twitter.

1. I never said William Hill itself was wrong or foolhardy. I merely raised the question whether this had been thought through, and said I knew lots of organizations that would probably fail to do so. Jon suggests that good EA should help to resolve this kind of thing, but of course that would only be true if EA could anticipate all possible future business ideas, or were consulted whenever such business decisions are made.

2. Maybe assuming an IT solution was jumping to conclusions, but I couldn't see how any other acceptable alternative would be any cheaper. Jon thought that a bookmaker wouldn't need to store the details of every outstanding bet, and has confirmed this with the Gambling Commission, but even if this is true for this particular example, I think my general point is still valid.

Blame Powerpoint

2009-10-30T13:04:00.001Z

@cybersal asks @RSessions a different sort of s/ware complexity question from his usual stuff: "How would you compare complexity of Powerpoint 2007 v 2003?"

The first point I want to make in discussing this question is that there are two different things, both called "Powerpoint". One is a lump of shrink-wrapped software, which I call technology-as-built. The other is the Powerpoint that people actually use, which I call technology-in-use. (Fans of Chris Argyris will recognize the parallels with espoused theory versus theory-in-use). If different groups or communities use Powerpoint differently, there may be many different Powerpoints-in-use corresponding to a single Powerpoint-as-built.

The distinction between technology-as-built and technology-in-use is extremely important for technology adoption and management. (My favourite example of this remains Lotus Notes, which for some time after its initial release was mostly used in pretty boring and unimaginative ways, merely as a jumped-up file management system. I guess it took at least two years before the technology-in-use started to catch up with and then exceed the intentions of the Lotus design team.) My notion of technology maturity is based on a stable relationship between technology-as-built and technology-in-use.

However, this distinction is largely ignored by IT analysts, who try to rank the "vision" of the software producers but entirely overlook the "vision" of software consumers. This is related to my point about Venturesome Consumption.

By the way, the distinction is implicit in my post yesterday, Blame Excel, where I distinguished between blaming things on Excel itself (technology-as-built) and blaming things on people using Excel stupidly (technology-in-use). Is Microsoft responsible for how Excel or Powerpoint are used? Clearly software providers cannot be blamed for the stupidity of their customers, but Microsoft clearly has a strong interest in promoting good use of its products, and providing some protection against bad use.

Now here's how this distinction applies to the question of software complication and complexity. Let's acknowledge that each successive version of Powerpoint-as-built has loads more features, new menu options, design styles and so on. But let's also acknowledge that many Powerpoint users are still using

the same limited subset of features
the same font (Ariel)
the same style (bullet points, like this)
the same clip art (those horrible cartoon men).

When people talk about Death-By-Powerpoint, they are generally talking about Powerpoint-in-Use. It is clearly possible to produce lively and informative Powerpoint presentations, but many people (including Bill Gates) don't seem to find this very easy.

So there is a growing gulf between the technology-as-built and the technology-in-use. This is where the unnecessary complexity gets in: I call it The Baroque Style. The more complicated the technology-as-built, the greater the risk of poor results from the technology-in-use.

Blame Excel

2009-10-29T16:58:00.003Z

@thinkovation (Gary Barnet) argues that the current financial crisis was caused by Excel (via @neilwd).

@monkchips thinks this is silly. I think he means it is silly to blame things on Excel. Of course Gary make it clear that he is actually blaming things on people using Excel stupidly.

If it is silly to blame a lump of software when things go wrong, it is equally silly to credit a lump of software when things go right. But this is exactly what the software vendors do all the time - claiming all sorts of benefits from the use of their products.

@jevdemon adds: "bad carpenters blame their tools". And good carpenters never praise their tools.

There are some fundamental logical flaws in the way people commonly reason about lumps of software as instruments - means to producing some end. See my paper Reasoning about Systems and their Properties.

See also my post A Better Instrument?

And for a related point, see Mike Kavis, When in doubt, blame the cloud

Lotus Knows

2009-10-27T00:19:00.001Z

There are several interesting aspects of the IBM "Lotus Knows" campaign.

The campaign started as a debate with the extended Lotus community (people inside and outside IBM) about the best ways to promulgate the benefits of Lotus. The debate itself used some of the latest crowd-sourcing and idea-sharing features of the Lotus platform (including a third party app called IdeaJam), and therefore served as a practical demonstration of some of the topics under discussion. The campaign is therefore an exercise in metacommunication - an act of communication between two or more agents that also communicates something about the communication itself and/or about the relationship between the agents.

Much of the resulting material consists of a long enumeration of all the complicated details of our daily lives that Lotus "knows". For example, whether to take an umbrella to a meeting.

Okay, here's my algorithm for taking an umbrella. If I am wearing my best suit, and I expect to walk in a dignified manner across an unsheltered carpark, then I will take an umbrella if the probability of rain is greater than 25%. If I am wearing smart casual, then I can always sprint if there is a shower, so I will only bother with an umbrella if the probability of rain is greater than 50%. And if I'm slumming it in jeans, the threshold goes up to 75%. If the meetings in my diary are classified by dress code, then Lotus should be able to combine my schedule with the local weather forecast, in order to give me an up-to-date umbrella advisory.

But the important point is that my umbrella preferences may not be the same as yours. So how does Lotus know what my umbrella preferences are? Presumably I have to teach it my preferences. And how exactly do I do that?

Alan Lepofsky adds

'"Lotus Knows where that file is" would mean more to me if it said "Lotus Knows how you can share files with your team, or with your customers". Or, "Lotus Knows which calls you want to answer, and which ones you want to avoid". Make it personal.' [Cute Lotus Knows ad, but]

For my part, when I see the slogan "Lotus Knows", my first question is not "How many different things does this clever Lotus actually know?" but "How exactly does Lotus know the things it knows?".

In other words, I want to know the process. I want to think of Lotus not as a bit of magic that produces knowledge from nowhere, but as a platform supporting an intelligent and collaborative way of working.

And what about the collective brainstorming that kicked off the Lotus Knows campaign? How much reliance can be placed on ideas that emerge from a free discussion? David Tebbut points out a small flaw.

"A terrific idea, except it's a bit like asking a church choir what songs they should be singing. They're going to choose the easy ones, the catchy ones, the ones that appeal to the choir itself." [Lotus knows, but do you?]

In many situations, the intelligent approach is neither entirely traditional nor entirely crowd-sourced, but a balanced combination of both. So how does a platform like Lotus help us achieve this, and how do we know if we've got the balance right? How does Lotus know whether what it knows is Good Enough?

(I expect there are good answers to these questions, and I intend to discover them, but they are not the questions that are given most emphasis on the Lotus Knows website.)

#LotusKnows

Holistic Industry Analysis

2009-10-07T14:25:00.000+01:00

James McGovern ( @mcgoverntheory ) claims that Burton Group is one step ahead of Gartner by focusing on interoperability between products over just vendor characteristics.

I don't wish to comment on his assessment of these two firms. (Although it might be amusing to place these firms into a magic quadrant, it wouldn't mean much.)

However, what I strongly endorse is his statement that focusing on the interoperability between products is at least one step beyond focusing on vendor characteristics, and much more relevant to the concerns of those purchasing, deploying and using the products.

Industry analysts need to provide a joined-up (dare I say "holistic") account of emerging software technology and its relationship to the customer experience. In order to do this, we need to recognize three critical points of asymmetry.

1. The product is not the technology.
2. The solution is not the business.
3. The customer experience is not the customer demand.

IT Complexity

2009-09-21T10:57:00.000+01:00

According to @RSessions, "IT Complexity is a tax paid by everybody that benefits nobody."

Well not quite. @neilwd lists a few exceptions: vendors, integrators, analysts.

Roger's mission to eliminate complexity is fraught with two major difficulties. First, the number of powerful stakeholders who appear to benefit from complexity. Neil mentions a few obvious ones.

And second, the wide range of factors that cause complexity. Some forms of complexity may be justified in terms of requisite variety. Some forms of complexity emerge from a history of decisions that made sense at the time. And some forms of complexity may actually be caused by clumsy or one-sided attempts to eliminate complexity - for example, arrangements to protect one party in a procurement contract (especially in the absence of trust).

@patrickdlogan offers an analogy for IT complexity - the levees in New Orleans: no budget to fix them, but just enough budget to work most days, make more complex. Roger replies: Good analogy. But unlike most IT projects, the New Orleans' Levees worked at least for a while.

Actually, most IT projects work after a fashion. Where IT projects are regarded as failures, this is usually because something has gone wrong with such factors as cost and quality (value-for-money). One of the lessons for IT from Hurricane Katrina is about the ability of a large integrated system to withstand unexpected events. See my posts on Efficiency & Robustness 1, 2. See also my post on Processing New Orleans mail after Katrina.

A Jig for Gartner

2009-09-10T14:23:00.000+01:00

Technology spoke and we raised no objection at
Vendors, their briefings so light and affectionate.

Sun sent us crazy for core business services, not
Four BPEL engines could tear us apart.
Oracle then coloured the map of our land.
IBM muscled, and applications came ripe to the hand.
In the foothills of SAP we played happily, happily
Even SalesForce couldn't tell us apart.

The recession drew near and said 'This will not do at all -
If you continue, I fear you will rue it all'.
So after TechEd we vowed to eschew it all
Though we all knew it would break our heart.

But Spring made hay of our good resolutions.
Gartner, you may be as wise as Confucians,
Yet once tech betrays you he plays you and plays you,
Like fishes for ever, so take it to heart.

[with apologies to C Day Lewis]

BBC technology coverage

2009-09-05T10:58:00.000+01:00

@ruskin147 Rory Cellan-Jones, the BBC Technology correspondent, asks What makes a tech story? (With some good answers by DisgustedofMitcham2 and others.)

For my part, I think the BBC should offer a strong thread of the political aspects of technology. Politicians often seem to make naive and simplistic decisions about technology (e.g. databases for everything). Are they being conned by the big software vendors and system integrators? Or are they merely falling into the common trap of expecting technology to magically solve all sorts of social problems? (See POSIWID: technology.)

For that matter, when a large vendor generously provides loads of kit to schools (for example), is anyone looking the gift horse in the mouth? What is the political agenda of technology firms?

A lot of this sort of thing is excellently covered by Computing and The Register (as well as my blogs of course), but I think the BBC could perform a useful service bringing some of these stories to a more general audience, explaining both sides of the argument in a fair and balanced manner, as well as helping to educate the political class about how (and how much) technology really works.

A Silver Lining for Industry Analysis?

2009-09-02T21:02:00.003+01:00

You're everywhere and nowhere, baby,
that's where you're at
Going down the bumpy hype-curve in your sorting hat
Flying across the country and getting fat
Saying everything is groovy
when your tires are flat

And it's hi-ho silver lining
anywhere you go now, baby
I see your sun is shining but I will make a fuss
Though it's obvious

Flies are in your pea soup, baby
they're waving at me
Anything you want is yours now,
only nothing's for free
Life's a-gonna get you someday,
just wait and see
So put up your beach umbrella
while you're watching TV

And it's hi-ho silver lining
anywhere you go, well, baby
I see your sun is shining but I will make a fuss
Though it's obvious

[with apologies to Scott English and Larry Weiss]

A Value Proposition for Industry Analysis 2

2009-08-28T15:15:00.001+01:00

@mcgoverntheory (James McGovern) asks "Why do you allow us to remain blissfully ignorant not knowing what quality analyst research is?" But as James Governor replies, "find a way to pay the independents without us merging, and who knows what we could do for you".

I've been rather critical of the large analyst firms recently, but at least they've found a way to generate revenue from what they do. They have also evolved a reasonably efficient process for producing and distributing large quantities of knowledge, in a form that people are apparently still willing to pay for.

The challenge for "quality analyst research" is to find a way of funding empirically grounded and practically relevant work to a satisfactory level of rigour.

Empirically grounded means gathering concrete evidence from the technology-in-use. Not sitting around pontificating on what a given bit of jargon ought to mean, or inventing new frameworks, but measuring actual outcomes.

Practically relevant means producing something reasonably quickly that is of practical value to producers and/or consumers. I'm not interested in measurements of opinion or awareness, I'm interested in practical results. While long-term studies are important as well, this is a job for university researchers. (Unfortunately, a lot of academic research is disappointingly superficial as well, if not methodologically flawed, but that's a different problem.)

Satisfactory level of rigour means doing genuine analysis rather than casual sorting or mechanical feature comparison, taking nothing at face value, and examining the evidence through the appropriate lenses.

It is important to remember that the producers of software products and platforms may not themselves understand what they have produced. Over the years I have talked to any number of bright inventors and innovators, and I cannot fault their ingenuity and enthusiasm, but they are not always aware of things going on elsewhere in the IT world that might interact (positively or negatively) with their work. (I think that's an excellent reason for them to talk to me, but then I would say that wouldn't I?)

And the users don't understand everything either. They may stand up at conferences and talk about "success stories" with a given technology, but it is very common for people to identify a single cause of success or failure, without acknowledging that success and failure usually result from many interacting factors.

In any case, technology strategy isn't about selecting specific products, or even specific classes of product. That's pretty tactical, because product features change from one version to the next. Even vendor comparison and selection look pretty short-term once acquisition rumours start to circulate. (Perhaps last month IBM had a better story on technology xyz than SAP. But this month SAP has acquired a niche xyz specialist, and last month's opinion is now out-of-date. Until IBM retaliates by acquiring another xyz specialist. And so on.)

Technology strategy should be about deciding what factors to pay attention to. So if industry analysts are going to support technology strategy, we need to be able to show which factors have the greatest impact on outcomes. And this knowledge cannot possibly be derived solely from vendor briefings or anecdotes from selected users.

ICT for schoolchildren

2009-08-28T00:46:00.001+01:00

@bryanglick (editor of Computing) worries as the number of GCSE ICT students falls again, reckons it's not good for UK IT.

I asked Bryan if he thought our kids need a GCSE to become computer-literate? Bryan agreed that GCSE is not a measure of computer literacy, but interprets the fall in numbers as an indicator of how few kids are interested in a career in IT (link). I disagree with Bryan's interpretation, and I also disagree that this is a cause for concern.

The Computing story itself provides two main explanations for the falling numbers.

ICT as a subject is now considered irrelevant by many children because ICT is used as a tool in so many other subjects.
ICT is seen as a soft touch at GCSE and A-level by many employers (and universities).

At GCSE level, the focus of the ICT course appears to be life skills rather than vocational skills - the computer as a means to an end. My son uses the computer and the internet to do his GCSE coursework in science and history, and for this he has needed to learn techniques for effective search and evaluation of information sources, as well as effective graphical and verbal presentation. Besides his schoolwork, he also uses a range of social tools, from Facebook to Spotify.

As a parent, I am much more concerned about his grades in mathematics, science and history, because these are the subjects that are taken seriously by universities and employers. If he did want to study computer science at Cambridge, for example, the best choice of A-levels would appear to be mathematics, further maths and physics [source: Cambridge University]. ICT is on Cambridge University's list of "soft" subjects, along with home economics and sports science [BBC News, 7 January 2008].

As it happens, my son's school no longer offers a GCSE in ICT anyway. The school has adopted a new diploma called DiDA; we are promised (although with little evidence as yet) that this will be regarded as equivalent to GCSEs. So the total number of kids doing GCSE in ICT is influenced by decisions made by parents and teachers and exam boards, and is not an indicator of how many 14-year-old kids (which is when they choose their GCSE options) want a career in IT.

The fact that schools are downgrading their ICT education needn't be a bad sign for the UK IT industry. As computer and internet literacy among teenagers continues to increase, schools can hopefully go back to teaching more intellectually demanding subjects, at least to those capable of tacking them.

Meanwhile, what does a career in ICT look like - either now or in the future? If I wanted to be provocative, I could identify several tiers. The top jobs in ICT would go (as always) to extremely bright, extremely creative people, from a broad range of intellectually demanding academic disciplines. (Many of the computer pioneers studied mathematics or physics. People who had studied Latin and Greek sometimes became outstanding software engineers.) There would be a middling tier of competent systems developers, who have had a more vocational education including ICT and business studies. And a bottom tier of data entry clerks and operators.

If my son did want a career in ICT, I hope he would aspire for the top jobs. The route to the top jobs in ICT doesn't go via a GCSE in ICT. The health of the UK IT industry depends more on the number of top maths grades than on the number of ICT passes. If the GCSE in ICT vanished altogether, I can't see it would be the end of the world.

The GCSE is a qualification taken by UK schoolchildren, usually across Years 10 and 11 (ages 14-16). Children may take GCSE in a number of subjects; schools generally offer some compulsory subjects (including Mathematics and English) and some optional subjects; pupils need to choose their GCSE options when they are 13 or 14.

Magic Quadrant or Sorting Hat?

2009-08-21T13:31:00.001+01:00

What is it about analysts and 4 quadrant models (asks @aleksb6 )? Were x and y coordinates so firmly etched in our brains that we can't get away from it?

I presume Aleks is talking about 4-quadrant models produced by software industry analysis firms, such as Gartner's Famous Magic Quadrant, which is a bit like the Hogwarts Sorting Hat.

Leaders: Gryffindor
Challengers: Slytherin
Visionaries: Ravenclaw
Niche Players: Hufflepuff

Nate Orenstam (Gartner Magick Quadrante) offers a similar mapping - Finders, Keepers, Losers, Weepers - together with a cynical explanation of the x and y axes.

A quick internet search for Gartner's Magic Quadrant yields many hits from software vendors boasting that their product has been sorted into Griffindor, presumably because these vendors believe that this quadrant implies some kind of endorsement by Gartner. And Oracle's Billy Cripe tweeted triumphantly "Oracle WIN!" when his own product was sorted into Griffindor.

As Mark Whitehorn explains (Is Gartner's Magic Quadrant really magic?), Gartner actually collects a considerable amount of data before summarizing everything down to a simple static picture. The quadrant is not the analysis, it is merely a simple visual summary of the analysis. And as Alan Pelz-Sharpe of CMS Watch asserts,

It is both the beauty and the curse of the MQ that it dramatically simplifies a marketplace. (De-mystifying the Gartner ECM Magic Quadrant, September 2007)

But what is the methodology behind the analysis? According to Tony Byrne, another CMS Watch analyst,

Many of Gartner's "strengths" and "cautions" have to do with a vendor's "marketing effectiveness," "messaging," and "awareness." Things that matter to investors and other vendors, but not so much to buyers. (Looking beyond the magic quadrant to find the nitty-gritty, August 2009)

Thus like the equally famous hype curve, it tells you more about marketing and image than about the intrinsic qualities of the technology. This may be one of the reasons why Open Source sometimes gets a poor deal.

Of course, Gartner's fine print strikes a note of caution.

Gartner does not endorse any vendor, product or service depicted in the Magic Quadrant, and does not advise technology users to select only those vendors placed in the "Leaders" quadrant. The Magic Quadrant is intended solely as a research tool, and is not meant to be a specific guide to action.

But obviously the vendors placed in the "Leaders" quadrant don't want you to read this.

See also

Gartner's conservative mid-tier ERP Magic Quadrant, Dennis Howlett, ZDnet June 2009
... should have stayed in retirement, Frank Scavo, June 2009
The One and Only Choice, Thomas Wailgum, CIO June 2009

Responding to a range of criticism, Gartner analyst Jim Holincheck (Misunderstanding Magic Quadrants, June 2009) makes the following points.

1. "Sometimes you will also hear criticism that Ability to Execute and Completeness of Vision do not matter as decision criteria for customers. I think the evaluation criteria within Ability to Execute and Completeness of Vision give a well-rounded view of a vendor and its place in a particular market and that is really the point of a Magic Quadrant."

Jim thinks the Magic Quadrant gives a "well-rounded view", but other people don't see it like that. In any case, this is not an answer to the criticism that the dimensions of the quadrant are not relevant to customer decisions.

2. "A 2×2 matrix is a really convenient way of showing the relative comparison of vendors."

Convenient to Gartner and the winning vendors obviously.

3. "There is a perception out there that clients basically will look at a MQ and put the vendors in the Leaders quadrant on their short list. There is no doubt that some clients do that. They shouldn’t, but they do."

So Gartner accepts no responsibility for clients misusing the quadrant.

4. "More importantly though, most clients will set up an inquiry (or a series of inquiries throughout the selection process) with an analyst to discuss their specific requirements. ... The interactions we have customers and Gartner clients gives us perspective to tailor our advice for customer-specific needs."

Thus what Gartner really wants is to sell more detailed advice.

5. Is the Magic Quadrant a good tool to use to make a vendor selection? It can be."

I thought he said that people shouldn't do that. Now he's saying it might be okay after all. What's the recipe today, Jim?

Technology Hype Curve 3

2009-08-11T19:11:00.003+01:00

"Gartner predicts Twitter fall from grace, advises CIOs to wait before deploying" (V3.co.uk 11th August 2009)

The Hype Curve measures public perception of a given technology. The points on the curve are labelled in terms of perception and opinion ("buzz of expectation", "slough of despond", "renaissance of hope" and "liberal enlightment" - or something like that anyway).

Surely the sensible advice to CIOs is to discount public perception, and base technology judgements as far as possible on technological reality rather than hype.

Don't adopt something simply because it's popular.
Don't NOT adopt something simply because it's NOT popular.

It's certainly possible to find cautionary Gartner statements to this effect. But the emphasis of Gartner advice (at least as glossed by V3) seems to contract the second point. Don't adopt Twitter, says Gartner, because the hype curve will turn against you. In other words, base your technology judgement on the hype curve after all!

Apart from CIOs who are so stressed-out or weak-minded that they like safety in numbers, the people who really value this kind of prediction are the software vendors. For them, the hype curve (as well as the Magic Sorting Hat) may help predict their likely product sales as well as the effectiveness of a given marketing campaign, and help plan their investment in certain products.

And of course Gartner wants the hype curve to be perceived as accurate and relevant. Gartner benefits commercially if the majority of CIOs gregariously (herd-like) follow the Gartner advice. "Thinking with the majority". Even if it is confusing hype with reality.

Update: See also Geek and Poke's Gartner Hype Cycle Version 2.0 (via Cloud Ave)

Industry Analyst as Prophet 2

2009-07-06T07:44:00.004+01:00

Many religious prophets are characterized by their vision of a world to come; but also by their bitter criticism of contemporary society and its leaders, and by righteous anger. Beware the angry prophet writes Jim West about the prophet Elisha, who cursed those who mocked his baldness.

In my previous post Industry Analyst as Prophet, I described prophecy as a combination of forecasting and evangelism. But some forms of prophecy also contain a strong element of righteous anger. Alongside the well-coiffured industry analyst firms that take money from vendors, there are also bald sites that constantly attack the large vendors and document the smallest perceived deviation from the path of righteousness.

Seaching the Internet for "who pays for prophecy", I found a bitter denunciation of both Gartner and Microsoft (Another Hopeful ‘Prophecy’ From the Gartner Group’s Paying Clients) on a website whose agenda is evident in its name: Boycott Novell. Microsoft seems to attract more than its fair share of this kind of attention - see for example Slated Antitrust.

Anyone who bases their understanding of the software industry on angry websites like these is clearly an idiot. When my son had a school project on Genetic Modification recently, we found websites that praised Monsanto and websites that denounced Monsanto as evil; I explained to my son that he could (probably should) reference anything he found, as long as he didn't take any of it at face value. There are certain companies that everyone likes to hate: when I was a student it was Barclays Bank; when I started in the software industry it was IBM; nowadays it is Walmart and Monsanto and of course Microsoft.

Obviously the same should apply to software industry analysis. The analyst should take nothing at face value: whether vendor marketing materials, or snide off-the-record remarks from other vendors, or wholesale denunciation from the vendor's enemies. The CIO who wants to exercise due diligence on a software vendor may ask an analyst if there are any competitors who should also be considered, but may also ask (expecting the answer no, but better to be safe than sorry) if there is anything on any of the denunciation websites that deserves any attention.

Given that this kind of check is a very small concern of many CIOs, it is surely more efficient and effective for many firms to share the costs of a trusted analyst wading through all this prophetic material, which saves everyone else the trouble. Is that a reasonable business model for industry analysis? Does that help answer the question: why should anyone pay for prophecy?

Industry Analyst as Prophet

2009-07-04T17:11:00.004+01:00

@j4ngis (A Jangbrand) asks

What are "analysts"? Problem Solvers or Prophets? Long-term-researchers? Consultants? All of the above? All the time?

I think industry analysts generally think of themselves as modern secular prophets, providing a combination of forecasting and evangelism. According to Wikipedia, "prophets are regarded as having a role in society that promotes change due to their messages and actions". The Hebrew word for Prophet literally means Spokesperson - in other words, the prophet is an intermediary.

As Wikipedia explains, there may be issues with the authenticity of a prophet: it is suggested that some prophets may have been schizophrenic. For a modern technology analyst, the authenticity of the prophecy may be compromised to the extent that the analyst turns out to be merely a spokesman.

Bob Dylan wrote a song about prophecy, which could also be interpreted as a song about software industry analysis.

There's too much confusion, I can't get no relief.
None of them along the line, Know what any of it is worth.
There are many here among us, Who feel that SOA is just a joke.
Let us not talk falsely now, The hour is getting late.

So who is the joker and who is the thief?

The future sounds like schizophrenia.

A Value Proposition for Industry Analysis

2009-07-04T15:01:00.005+01:00

@mcgoverntheory Following my last post on Industry Analysis by Survey, James McGovern asks for a blog entry on other low questions analyst firms ask.

"Low questions" may be an inevitable consequence of the way much so-called industry analysis is funded. What I really want is to find a viable business model in which analysts can ask the "high questions" they should be asking.

Software industry analysis is basically a two-sided market. Analysts provide value (of different kinds) to the software vendors and to the software users. Some of this value is funded by the vendors, for example by sponsorship, commissioning white papers, keynote presentations and other consultancy work. Some of this value is funded by the software users, for example by purchasing reports and training, subscribing to materials, and consultancy work again.

Analysts also receive value from both sides of the market. They get detailed briefings from vendors, and detailed case studies from users. Analysts under tight deadlines may sometimes be tempted to use this kind of material without thorough critical evaluation; after all, such sources of easy material might dry up if the analysts were too critical. As I said in my post on Industry Analyst Coverage, vendors can influence analysts not just by giving them money but also by doing their work for them. Users don't have the same commercial interest, but they typically block publication of wart-and-all case studies.

Software users sometimes seem to want to have things both ways. On the one hand, they want a high level of quality and independence, and complain when industry analysts fail to cover the things they want covered. But they often aren't willing to provide sufficient funding for this to happen.

Two-sided markets always introduce a level of complexity that is not present in single-sided markets. Like a double pendulum.

Last month I asked about A Value Proposition for Enterprise Architecture. So here's a similar question: what exactly is the value that software industry analysts deliver or should deliver, to whom? Given the obvious doubts about the transparency of how some industry analyst firms operate, is there something that doesn't quite add up in the current business model? Is it possible to formulate a transparent and viable business model for rigorous industry analysis?

Technology Hype Curve 2

2009-07-03T20:11:00.005+01:00

I wrote a critique of the #Gartner Technology Hype Curve (it's not a cycle) back in September 2005, pointing out some of the reasons why it shouldn't be taken too seriously.

Obviously I'm not arguing with the existence of the phenomenon of hype, but the evidence that this phenomenon follows a standard curve looks extremely weak. The hype curve appears to make falsifiable predictions about the expected hype-status of a given technology on a given future date. If we are being asked to take this curve as serious empirical science, we need to see some kind of scientific proof - for example, looking at the accuracy of these predictions, and using empirical data to calibrate the shape of the curve.

But although this curve has been used by Gartner for over twenty years, I have not seen any statistical analysis, whether from Gartner or anyone else, that would help us to assess how accurate these predictions have been. The shape of the curve seems to have remained remarkably stable, despite a widespread belief that innovation has been getting faster. I made all these points in my earlier post.

I understand that some people use the hype curve as a planning tool, to decide the appropriate investment and placement of technology. I'd be very interested to know how this works, and what practical conclusions can be drawn from the curve.

Another methodological problem with tracking technology hype through time is that technological jargon isn't always stable - the meaning and identity of the hyped items shift over time. So the same buzzword on the curve in different years doesn't necessarily refer to the identical technology - we might collectively change our minds as to what exactly a given buzzword really signifies. As Vinnie Mirchandani puts it: "Category names morph as they mature".

Technology concepts may emerge slowly through a complex social process; the sociologist Bruno Latour refers to these emerging concepts as Black Boxes. If we accept that there may be a separation between the perceived progress of technology (as represented through hype and jargon) and the actual progress of technology (which we may sometimes only be able to infer indirectly), then the hype curve presumably measures the first of these. And if that's true, what value can the hype curve provide to whom?

Parts of this post were contributed to a discussion on The Enterprise Architecture Network, via Linked-In.
See also Jorge Aranda: Cheap Shots at the Gartner Hype Curve (October 2006)
See also Vinnie Mirchandani: Un-hyping the Gartner Hype Cycle (August 2009)
And see my later posts Technology Hype Curve 3, Magic Quadrant or Sorting Hat

Industry Analysis by Survey

2009-07-03T14:30:00.003+01:00

@pgiblett @chrisdpotts @seabird20 @

Following a recent poll of 900 CIOs, Gartner concludes "IT Spending Outlook Still Uncertain". Peter B. Giblett adds "... not necessarily recession related".

Chris Potts comments: "CIOs need to actively resist being cast as primarily interested in IT spending" and adds a hint to CIOs: "If a research organisation asks you how much your company is spending on IT, ask 'why does that matter?'". Chris Bird suggests that a more interesting question would be "What value are you delivering?". Chris Potts then adds a further question: "Which corporate strategy are you leading?"

Excellent questions Chris-and-Chris, but we know that surveys like these generally restrict themselves to asking numerical and multiple-choice questions, because the answers can then be "analysed" using simple Excel. As ChrisB points out, most of the hard numbers (?!) analysis is around purchasing.

The question "Why does that matter?" prompts the question "To whom does that matter?" So who cares about IT spending? Why would a CIO care what percentage of her peers are spending what amount on a given buzzword? Safety in numbers?

Perhaps, as ChrisB suggests, the people most interested in quantifying IT spend are the vendors and investors. But they can't learn much from an unqualified total figure. What they really need is a detailed breakdown, based on a consistent method of cost accounting, and they are not going to get that from surveys like these.

The problem is not just lack of detail, but lack of reliability. As ChrisB points out, people don't always tell the truth. Some CIOs may deliberately distort their answers, while others may simply guess the numbers in order to get the researcher off their backs.

In my opinion, then, the correct retort to "how much do you spend?" is "what meaningful conclusions can you possibly draw from whatever number I give you?"

Industry Analyst Coverage

2009-06-22T14:17:00.006+01:00

@mcgoverntheory (James McGovern) complains about the completeness, balance and objectivity of industry analyst coverage. He believes that certain areas are neglected (security, open source), and attributes this to a commercial bias.

How important is it for industry analysts to include security analysis in their SaaS research?
Does non-commercial open source have a fighting chance to be mentioned by industry analysts to their customers? How can customers understand analyst transparency when it comes to coverage of non-commercial open source?

James has always been particularly exercised about the fact that OWASP lacks coverage. When he raised this issue with me last year, I responded by posting some questions on the OWASP wiki and the OWASP Linked-In group, as well as several posts on this blog. I'm still waiting for answers.

If there is something in the product offering from any of the large vendors that I don't understand, I can contact one of my analyst relations "minders" and get a reasonably quick answer. If it's a small vendor, I can usually get an answer straight from the CTO. In contrast, my questions to OWASP go into a black hole. One person even suggested that if I wanted to know something about OWASP I needed to start a project. No thanks. (And, to answer Jim's comment below, I don't want to join a mailing list either.)

Industry analysts simply cannot invest that amount of time in chasing non-existent information. If OWASP wishes to be taken seriously by industry analysts, then it needs to put some energy into briefing industry analysts properly, instead of expecting us to root around the OWASP website and complaining when we don't.

Large vendors may sometimes try to influence industry analysts by commissioning work, and many analysts declare this when they deem it relevant. (I think that's what James means by transparency.) But a much more subtle influence can be achieved simply by providing better quality information and making our lives easier.

Layered Architecture of Technology Adoption

2009-05-27T22:00:00.003+01:00

@colin_jack asked whether companies ever really change, ignoring situations where there is a big change of staff (one group leaves, another group joins). People seem to want to slip back into their old way of working within weeks or months. Thinking particularly of the fast big bang changes companies go for. Agile, SOA, etc.

Companies do often change their nature as they get larger and older, but this is a slow process. Managed organization change involves several loosely-coupled streams of activity, which operate on different timetables. Installing new software, sending everyone on a training course, renegotiating project charters and external service contracts, building experience and confidence in new practices - these things all happen at different speeds.

A key principle of evolutionary change is that the slow-moving layers generally dominate the faster-moving layers. If your organization wishes to adopt "agile" or "service-orientation" or anything like that, this requires attention to the slow-moving layers as well.

When I was working with CASE tools in the late 1980s, I and a few colleagues constructed an adoption roadmap to help with planning technology adoption. This roadmap was designed in layers or streams, not just to aid with separation of concerns, but also to manage the different characteristic pace of change in each stream. This is architectural thinking applied to organizational change. And nearly twenty years layer, exactly the same principles were used by the CBDI Forum in constructing a roadmap for SOA adoption.

Factoring in Barriers to Entry

2009-05-27T15:57:00.002+01:00

@toddbiske and @djbressler make some interesting points about the adoption of software tools and platforms (Factoring in Barriers to Entry). Todd's specific example is applying BPM and BPMN tools to support EA processes, but his remarks would apply in many other contexts.

Todd's basic argument is that adoption is more important than sophistication. Better to get people started with simple tools and platforms - for example Visio and Sharepoint - than do anything that requires the IT department to get its hands dirty. (In an earlier post, Todd identified the IT department as one of the Barriers to SOA Adoption.)

But I don't think of adoption as a simple binary event (from "unadopted" to "adopted") but as a curve (from shallow occasional use to sophisticated and seamless integration into working practice). And although that's not how Todd is using the word "adoption", I think his argument is consistent with a richer notion of adoption. For example, he acknowledges a concern that "low barrier to entry eventually become a boat anchor".

If a vendor boasts thousands of users, and then I discover this merely means installing the trial version of the software and playing with it once, then I'm not very impressed. If a vendor has a dozen customers at the top of the curve, that's much more impressive than a thousand at the bottom of the curve.

From this point of view, lowering the barriers to entry is only half the story. What I'm interested in is the shape of the whole adoption curve, which enables people to find an appropriate level of adoption and not get stuck on the nursery slopes. That's where I think software like Visio and Sharepoint falls down - they may be easy to get started, but they can get hairy if you want to do anything more interesting.

Technologies for the Intelligent Business

2009-05-05T00:07:00.002+01:00

#orgintelligence

A number of vendors have started to introduce their own terms for different aspects of organizational intelligence. In the past week or so, I've picked up the following terms.

Collaboration Networks (Cisco, via Padmasree Warrior)

Continuous Intelligence (Aleri + Coral8 via Brenda Michelson)

Smart SOA (IBM concept that pulls together SOA, BPM, Collaboration + business architecture, via Neil Ward-Dutton)

As far as I can see, none of these concepts covers all aspects of Organizational Intelligence, but I need to do a more detailed mapping.

Any other vendor or independent concepts I should look at?

Technologies for Organizational Intelligence

View more presentations from Richard Veryard.

Reflections On Twittering at The Open Group

2009-05-02T10:22:00.006+01:00

#ogadc

Using Twitter at The Open Group conference in London this week was a new experience for me, so I thought I'd reflect on it here.

Firstly the mechanics. There was free wifi in the venue; however, many people had difficulty connecting on the first day, and I used my pay-as-you-go dongle instead. Someone proposed a hashtag #ogadc and nearly everyone used that, even though the correct abbreviation for the conference should have been #ogapc.

A number of people including myself started to post 140 character tweets during the sessions. Highlighting key sentences, summarizing or commenting. It was like we were all taking notes into the same notebook. The conference organizers put a large Twitter display screen in the coffee area, so people could read the Tweets from the previous session.

You can see the results here. http://search.twitter.com/search?q=#ogadc

Some people said they found it distracting. For myself, I found that it required a more concentrated listening to the speaker, in order to capture the important points into 140 character Tweets. (Some people continue a single thought over multiple Tweets, but I think that's cheating.)

It also led to new conversations, as Twitter conversations during the sessions developed into face-to-face conversations during the breaks. Sometimes I found I was sitting next to a fellow Twitterer, and could see my Tweets appearing on his screen and vice versa. Thus I made a lot of new friends.

People also posted links to photos as well as video from the evening dinner. I've experienced that at previous conferences via blogging and Technorati and hashtags on Flickr, but Twitter seems to be more effective platform for this kind of thing.

What about people who were not present at the conference? In the recent past, I have picked up interesting Tweets from conferences, so I hoped my followers would be somewhere between tolerant and interested in the unusually high volume of my Tweets. (I probably lost some followers, but I gained some as well. Swings and roundabouts won't break my bones as the saying goes.) Some friends who were not physically present were engaged enough to post Tweets into the conference stream - asking questions or making further comments - and I hope to see more of that kind of virtual participation.

The End of the Maintenance Endgame

2009-04-29T21:39:00.003+01:00

When Marc Benioff (Salesforce CEO) calls for the end of maintenance payments (ComputerWorld, PCWorld), he obviously wants to draw attention to one of the apparent advantages of the Software-as-a-Service (SaaS) model of software consumption.

As Judith Hurwitz points out, this advantage is more apparent than real. SaaS vendors like Salesforce still need to maintain their software assets, and to pass the costs of this maintenance to their customers, one way or another.

A significant fraction of software maintenance is required simply to keep up with the latest platforms and standards without delivering any new features or other innovation, and this is especially true for companies that have large portfolios of fragmented software assets.

Companies that fail to innovate may still retain a high percentage of their customers, at least in the short term, because of the high switching costs. This is not just a factor with traditional software products, but can be true of SaaS as well.

One key differentiator here is not between SaaS and more traditional software delivery and pricing, but between software companies that maintain their software assets intelligently and effectively and those that don't. Another key differentiator is between products and services with high switching costs (vendor lock-in) and those with very low switching costs (open market).

As Judith also points out, "many software companies have become increasingly dependent on maintenance revenue to keep revenue growing". In addition, there has been a trend in the software industry of companies acquiring mature software products in order to milk the maintenance revenues, with no real intention of innovation. (See my post on Innovation or Refinement.) This can be regarded as similar to securitization - treating a software product as a financial product, based on its expected income stream.

To the extent that open market SaaS exists, this represents a major challenge to this endgame, and this could possibly mean much quicker termination of declining products and services. But only a chess player would dare to predict how this will play out over time.

Open Group Boston Grid

2009-04-29T11:11:00.003+01:00

At the Open Group Architecture Practitioner Conference, I caught up with Allen Brown, President and CEO of The Open Group, to talk about TOGAF and the other activities of The Open Group. I also spoke with Chris Harding, Forum Director for SOA and Semantic Interoperability.

The Open Group originated as a merger of two UNIX standards bodies (X/Open and Open Software Foundation); and UNIX certification (e.g. Apple Leopard) is still its best-known product and cash cow.

The two rising stars in The Open Group portfolio are Architecture and Security.

At the core of Architecture is The Open Group Architecture Framework (TOGAF). TOGAF 9.0 is now available. It was launched in the US in February, and this conference represents the European launch. There are several forums and groups working in parallel with the main TOGAF Architecture Forum, including Business Architecture, SOA and ArchiMate.

Clearly there may be a temptation in some quarters to see TOGAF as a bucket for everything that is remotely architectural. The latest TOGAF guide does contain material on business architecture and SOA and security, as well as the core architectural framework and process. However, the working groups operate on a loosely-coupled basis - for example, the SOA working group timetable is not synchronized to the Architecture Forum timetable - and this probably makes a more modular structure inevitable, at least in publication and possibly also curriculum.

There is common interest and a desire for harmonization between The Open Group and other standards bodies, notably OMG and OASIS. (See minutes of SOA Summit from February 2009, which may go some way to addressing David Sprott's concerns on SOA Concept Standards from January 2009.)

Security brings together a number of forums and groups, including the Jericho Forum and Identity Management. Again there is common interest with other standards bodies.

At some point, these two "rising stars" may become "cash cows". Looking into the future, The Open Group may need to seek new initiatives. Semantic Interoperability may be a "problem child" at the moment, but this presumably creates a common interest with W3C, especially given Tim Berners-Lee's interest in the Semantic Web.

And maybe a few more problem children we don't know about yet.