Tag Archives: Australian Artificial Intelligence Institute

Taxonomies 1, Semantic Web (and Linked Data) 0

I’m not a big fan of Semantic Web{{1}}. For something that has been around for just over ten years — and which has been aggressively promoted by the likes of Tim Berners-Lee{{2}} — very little real has come of it.

Taxonomies, on the other hand, are going gangbusters, with solutions like GovDirect{{3}} showing that there is a real need for this sort of data-relationship driven approach{{4}}. Given this need, if the flexibility provided by Semantic Web (and more recently, Linked Data{{5}}) was really needed, then we would have expected someone to have invested in building significant solutions which use the technology.

While the technology behind Semantic Web and Linked Data is interesting, it seems that most people don’t think it’s worth the effort.

All this makes me think: the future of data management and standardisation is ad hoc, with communities or vendors scratching specific itches, rather than formal, top-down, theory driven approaches such as Semantic Web and Linked Data, or even other formal standardisation efforts of old.

[[2]]Tim Berners-Lee on Twitter[[2]]
[[4]]Peter Williams on the The Power of Taxonomies @ the Australian Government’s Standard Business Reporting Initiative[[4]]

The technologies behind the likes of Semantic Web and Linked Data have a long heritage. You can trace them back to at least the seventies when ontology and logic driven approaches to data management faced off against relational methodologies. Relational methods won that round — just ask Oracle or the nearest DBA.

That said, there has been a small number of interesting solutions built in the intervening years. I was involved in a few in one of my past lives{{6}}, and I’ve heard of more than a few built by colleagues and friends. The majority of these solutions used ontology management as a way to streamline service configuration, and therefor ease the pain of business change. Rather than being forced to rebuild a bunch of services, you could change some definitions, and off you go.


What we haven’t seen is a well placed Semantic Web SPARQL{{7}} query which makes all the difference. I’m still waiting for that travel website where I can ask for a holiday, somewhere warm, within my budget, and without too many tourists who use beach towels to reserve lounge chairs at six in the morning; and get a sensible result.

[[7]]SPARQL @ w3.org[[7]]

The flexibility which we could justify in the service delivery solutions just doesn’t appear to be justifiable in the data-driven solution. A colleague showed my a Semantic Web solution that consumed a million or so pounds worth of tax payer money to build a semantic-driven database for a small art collection. All this sophisticated technology would allow the user to ask all sorts of sophisticated questions, if they could navigate the (necessarily) complicated user interface, or if they could construct an even more daunting SPARQL query. A more pragmatic approach would have built a conventional web application — one which would easily satisfy 95% of users — for a fraction of the cost.

When you come down to it, the sort of power and flexibility provided by Semantic Web and Linked Data could only be used by a tiny fraction of the user population. For most people, something which gets them most of the way (with a little bit of trial and error) is good enough. Fire and forget. While the snazzy solution with the sophisticated technology might demo well (making it good TED{{8}} fodder), it’s not going to improve the day-to-day travail for most of the population.


Then we get solutions like GovDirect. As the website puts it:

GovDirect® facilitates reporting to government agencies such as the Australian Tax Office via a single, secure online channel enabling you to reduce the complexity and cost of meeting your reporting obligations to government.

which make it, essentially, a Semantic Web solution. Except its not, as GovDirect is built on XBRL{{9}} with a cobbled together taxonomy.

[[9]]eXtensible Business Reporting Language[[9]]

Taxonomy driven solutions, such as GovDirect might not offer the power and sophistication of a Semantic Web driven solution, but they do get the job done. These taxonomies are also more likely to be ad hoc — codifying a vendor’s solution, or accreted whilst on the job — than the result of some formal, top down ontology{{10}} development methodology (such as those buried in the Semantic Web and Linked Data).

[[10]]Ontology defined in Wikipedia[[10]]

Take Salesforce.com{{11}} as an example. If we were to develop a taxonomy to exchange CRM data, then the most likely source will be other venders reverse engineering{{12}} whatever Salesforce.com is doing. The driver, after all, is to enable clients to get their data out of Salesforce.com. Or the source might be whatever a government working group publishes, given a government’s dominant role in its geography. By extension we can also see the end of the formal standardisation efforts of old, as they devolve into the sort of information frameworks represented by XBRL, which accrete attributes as needed.

[[12]]Reverse engineering defined in Wikipedia[[12]]

The general trend we’re seeing is a move away from top-down, tightly defined and structured definitions of data interchange formats, as they’re replaced by bottom-up, looser definitions.

Consulting doesn’t work any more. We need to reinvent it.

What does it mean to be in consulting these days? The consulting model that’s evolved over the last 30 – 50 years seems to be breaking down. The internet and social media have shifted the way business operates, and the consulting industry has failed to move with it. The old tricks that the industry has relied on — the did it, done it stories and the assumption that I know something you don’t — no longer apply. Margins are under pressure and revenue is on the way down (though outsourcing is propping up some) as clients find smarter ways to solve problems, or decide that they can simply do without. The knowledge and resources the consulting industry has been selling are no longer scarce, and we need to sell something else. Rather than seeing this as a problem, I see it as a huge opportunity; an opportunity to establish a more collaborative and productive relationship founded on shared, long term success. Sell outcomes, not scarcity and rationing.

I’m a consultant. I have been for some time too, working in both small and large consultancies. It seems to me that the traditional relationship between consultancy and client is breaking down. This also appears to be true for both flavours of consulting: business and technology. And by consulting I mean everything from the large tier ones down to the brave individuals carving a path for themselves.

Business is down, and the magic number seems to be roughly a 17% decline year-on-year. One possible cause might be that the life blood of the industry — the large multi-year transformation project — has lost a lot of its attraction in recent years. If you dig around in the financials for the large publicly listed consultancies and vendors you’ll find that the revenue from IT estate renewal and transformation (application licenses, application configuration and installation services, change management, and even advisory) is sagging by roughly 17% everywhere around the globe.

SABER @ American Airlines

Large transformation projects have lost much of their attraction. While IBM successfully delivered SABER back in the 60s, providing a heart transplant for American Airlines ticketing processes, more recent stabs at similarly sized projects have met with less than stellar results. Many more projects are quietly swept under the carpet, declared a success so that involved can move on to something else.

The consulting model is a simple one. Consultants work on projects, and the projects translate into billable hours. Consultancies strive to minimise overheads (working on customer premises and minimising support staff), while passing incidental costs through to clients in the form of expenses. Billable hours drive revenue, with lower grades provide higher margins.

This creates a couple of interesting, and predictable, behaviours. First, productivity enhancing tooling is frowned on. It’s better to deploy a graduate with a spreadsheet than a more senior consultant with effective tooling. Second, a small number of large transactions are preferred to a large number of small transactions. A small number of large transactions requires less overhead (sales and back-office infrastructure).

All this drives consultancies to create large, transformational projects. Advisory projects end up developing multi-year (or even multi-decade) roadmaps to consolidate, align and optimise the business. Technology projects deliver large, multi-million dollar, IT assets into the IT estate. These large, business and IT transformation projects provide the growth, revenue and margin targets required to beat the market.

This desire for large projects is packaged up in what is commonly called “best practice”. The consulting industry focuses on did it, done it stories, standard and repeatable projects to minimise risk. The sales pitch is straight-forward: “Do you want this thing we did over here?” This might be the development of a global sourcing strategy, an ERP implementation, …

Spencer Tracy & Katharine Hepburn in The Desk Set
Spencer Tracy & Katharine Hepburn in The Desk Set

This approach has worked for some time, with consultancy and client more-or-less aligned. Back when IBM developed SABER you were forced to build solutions from the tin up, and even small business solutions required significant effort to deliver. In the 1957, when Spencer Tracy played a productivity expert in The Desk Set, new IT solutions required very specific skills sets to develop and deploy. These skills were in short supply, making it hard for an organisation to create and maintain a critical mass of in-house expertise.

Rather than attempt to build an internal capability — forcing the organisation on a long learning journey, a journey involving making mistakes to acquire tacit knowledge — a more pragmatic approach is to rent the capability. Using a consultancy provides access to skills and knowledge you can’t get elsewhere, usually packaged up as a formal methodology. It’s a risk management exercise: you get a consultancy to deliver a solution or develop a strategy as they just did one last week and know where all the potholes are. If we were cheeky, then we would summerize this by stating that consultancies have a simple value proposition: I know something you don’t!

It’s a model defined by scarcity.

A lot has changed in the last few years; business moves a lot faster and a new generation of technology is starting to take hold. The business and technology environment is changing so fast that we’re struggling to keep up. Technology and business have become so interwoven that we now talk of Business-Technology, and a lot of that scarce knowledge is now easily obtainable.

The Diverging Pulse Rates of Business and Technology
The Diverging Pulse Rates of Business and Technology

The scarce tacit knowledge we used to require is now bundled up in methodologies; methodologies which are trainable, learnable, and scaleable. LEAN and Six Sigma are good examples of this, starting as more black art than science, maturing into respected methodologies, to today where certification is widely available and each methodology has a vibrate community of practitioners spread across both clients and consultancies. The growth of MBA programmes also ensures that this knowledge is spread far and wide.

Technology has followed a similar path, with the detailed knowledge required to develop distributed solutions incrementally reified in methodologies and frameworks. When I started my career XDR and sockets were the networking technologies of the day, and teams often grew to close to one hundred engineers. Today the same solution developed on a modern platform (Java, Ruby, Python …) has a team in the single digits, and takes a fraction of the time. Tacit knowledge has be reified in software platforms and frameworks. SaaS (Software as a Service) takes this to a while new level by enabling you to avoid software development entirely.

The did it, done it stories that consulting has thrived on in the past are being chewed up and spat out by the business schools, open source, and the platform and SaaS vendors. A casual survey of the market usually finds that SaaS-based solutions require 10% of the installation effort of a traditional on-premsis solution. (Yes, that’s 90% less effort.) Less effort means less revenue for the consultancies. It also reduces the need for advisory services, as provisioning a SaaS solution with the corporate credit card should not require a $200,000 project to build a cost-benefit analysis. And gone are the days when you could simply read the latest magazines and articles from the business schools, spouting what you’d read back to a client. Many clients have been on the consulting side of the fence, have a similar education in the business schools, and reads all the same articles.

I know and you don’t! no longer works. The world has moved on and the consulting industry needs to adapt. The knowledge and resources the industry has been selling are no longer scarce, and we need to sell something else. I see this is a huge opportunity; an opportunity to establish a more collaborative and productive relationship founded on shared, long term success. As Jeff Jarvis has said: stop selling scarcity, sell outcomes.

Updated: A good friend has pointed out the one area of consulting — one which we might call applied business consulting — resists the trend to be commoditized. This is the old school task of sitting with clients one-on-one, working to understand their enterprise and what makes it special, and then using this understanding to find the next area or opportunity that the enterprise is uniquely qualified to exploit. There’s no junior consultants in this area, only old grey-beards who are too expensive to stay in their old jobs, but that still are highly useful to the industry. Unfortunately this model doesn’t scale, forcing most (if not all) consultancies into a more operational knowledge transfer role (think Six Sigma and LEAN) in an attempt to improve revenue and GOP.

Updated: Keith Coleman (global head of public sector at Capgemini Consulting) makes a similar case with Time to sell results, not just advice (via @rpetal27).

Updated: I’ve responded to my own post, tweaking my consulting page to capture my take on what a consultant needs to do in this day and age.

Innovation and the art of random

A little while ago I was invited to speak at an event, InnoFuture, which, for a mixture of reasons, didn’t end up happening. The theme for the event was Ahead of the trends — the random effect. My take on it was that innovation is not random, it’s just happening faster than you can process, and that ideas are commoditized making synthesis, the creation of new solutions to old problems, what drives innovation. I was pretty happy with the outline I put together for my talk, that I ended up reusing the content and breaking it into three blog posts, rather than letting it go to waste.

Innovation seems to be the topic of the day. Everyone seems to want some, thinking that it’s the secret sauce which will help them (or their company) bubble to the top of the heap. The self help and consulting communities have responded in force, trying to bottle lightening or package the silver bullet (whichever metaphor you prefer).

It was in this environment that I was quite taken by the topic of a recent InnoFuture event when I was asked to speak.

Ahead of trends — the random effect.
When a concept becomes a trend, you are a not the leader. How to tap into valuable ideas for products, services and communication before they are seen as trends, when they are just … random? Albert Einstein said that imagination is more important than knowledge. Let’s open the doors and let the imagination in for it seems that in the current crisis, the right brain is winning and we may be rationalized to death before things get better.

I’ve never seen the random effect, though I have been delightfully surprised when something unexpected pops up. Having been involved in a bunch of companies and projects that, I’m told, where innovative, I’ve always thought innovation was not so much random, as the result of obliquity. What makes it seem random is the simple fact that your are not aware of the intervening steps from interesting problem through to novel solution.

I figured I’d mash together a few ideas that capture this thought, and provide some (hopefully) sage advice based on what I do to deal with random. I ended up selecting:

  • John Boyd on why rapidly changing environments are confusing,
  • Peter Drucker‘s insight that insight (the tacit application of knowledge) is not a transferable good,
  • the struggle for fluency that we all go through as we learn to read,
  • John Boyd (again, but then he had a lot of good ideas) on the need for synthesis,
  • KK Pang (and old lecturer of mine) on the need to view problems from multiple contexts,
  • the need to follow a consistent theme of interest as the only tractable way of finding interesting problems to solve, and
  • my own experiences in leveraging a network of like and dissimilar minds as a way of effectivly out-sourcing analysis.

The result was called Of snow mobiles and childhood readers: why random isn’t, and how to make it work for you. I ended up having far to much content to fill my twenty minute slot, so it’s probably for the better that the event didn’t go ahead, as it would have taken a lot of time to cut it down.

Given that I had a fairly well developed outline, I decided to make it into a series of blog posts (plus my slides these days don’t have a lot of text on them, so if I just dropped the slides online they wouldn’t make any sense). The blog posts ended up breaking down this way:

  1. Innovation should not be the race for the new-new thing.
    Points out that innovation only seems random, unexpected, as you don’t see the intervening steps between a problem and new solution, and that innovation is the result of many small commoditized steps. This ties into one of my earlier posts of dealing with the speed of change.
  2. The role of snowmobiles in innovation.
    Argues that ideas are a common commodity, and that the real challenge with innovation is synthesis rather than ideation.
  3. Childhood readers and the art of random.
    Argues that the key to innovation is to find interesting problems to solve, and suggests that the best approach is to be fluent in a range of domains (sectors, geographies, activities, …) to provide a broader perspective, focus on a line of inquiry to provide some structure, and build a network of people with complimentary interests, providing you with the time, space and opportunity to focus on synthesis.

I expect that these are more productive if taken as a whole, rather than individual posts.

If you look at the path I’ve charted over my career then this is the approach I’ve taken, and my topic of choice is how people communicate and decide as a group, leading me to John Boyd, Cicero, human-computer interaction, agent technology, biology (my thesis was mathematically modelling nerves in a cat), and so on.

I still have the slides, so feel free to contact me it you’re interested in my presenting all or part of this topic.