Tag Archives: driver

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.

Some new rules for IT

The other week I had a go at capturing the rules of enterprise IT{{1}}. The starting point was a few of those beery discussions we all have after work, where we came to wonder how the game of enterprise IT was changing. It’s the common refrain of big-to-small, the Sieble to Saleforce.com transition which sees the need for IT services (internal or external) change dramatically. The rules of IT are definitely changing. Now that I’ve had a go at old rules, I thought I’d have a go at seeing what the new rules might be.

As I mentioned before, enterprise IT has historically been seen as an asset management function, a production line for delivering large IT assets into the IT estate and then maintaining them. The rules are the therefore rules of business operations. My attempt at capturing 4 ± 2 rules (with friends) produced the following (in no particular order):

[[1]]The rules of Enterprise IT @ PEG[[1]]

  • Keep the lights on. Much like being a trucker, the trick is to keep the truck rolling (and avoid spending money on tyres). Otherwise known as smooth running applications are the ticket to the strategy table.
  • Save money. Business IT was born as a cost saving exercise (out with the rooms full of people, in with the punch card machines), and most IT business cases are little different.
  • Build what you need. I wouldn’t be surprised if the team building LEO{{2}} blew their own valve tubes. You couldn’t buy parts of the shelf so you had to make everything. This is still with us in some organisations’ strong desire to build – or at least heavily customise – solutions.
  • Keep the outside outside. We trust whatever’s inside our four walls, while deploying security measures to keep the evil outside. This creates an us (employees) and them (customers, partners, and everyone else) mentality.

[[2]]LEO: Lyons Electronic Office. The first business computer. @ Wikipedia[[2]]

Things have changed since these rules were first laid down. From another post of mine on a similar topic{{3}} (somewhat trimmed and edited):

[[3]]The IT department we have today is not the IT department we’ll need tomorrow @ PEG[[3]]

The recent global financial criss has fundamentally changed the business landscape, with many are even talking about the emergence of a new normal{{4}}. We’ve also seen the emergence of outsource, offshore, cloud computing, SaaS, Enterprise 2.0 and so much more.

Companies are becoming more focused, while leaning more heavily on partners and services companies (BPO, out-sourcers, consultants, and so on) to cover those areas of the business they don’t want to focus on. We can see this from the global companies who have effectively moved to a franchise model, though to the small end of town where startups are using on-line services such as Amazon S3, rather than building their own internal capabilities.

We’re also seeing more rapid business change: what used to take years now takes months, or even weeks. The constant value-chain optimisation we’ve been working on since the 70s has finally cumulated in product and regulatory life-cycles that change faster than we can keep up.

Money is also becoming (or has become) more expensive, causing companies and deals to operate with less leverage. This means that there is less capital available for major projects, pushing companies to favour renting over buying, as well as creating a preference for smaller, incremental change over the major business transformation of the past.

And finally, companies are starting to take a truly global outlook and operate as one cohesive business across the globe, rather than as a family of cloned business who operate more-or-less independently in each region.

[[4]]The new normal @ McKinsey Quarterly[[4]]

So what are the new 4 ± 2 rules? They’re not the old rules of asset management. We could argue that they’re the rules of modern manoeuvre warfare{{5}} (which would allow me to sneak in one of my regular John Boyd references{{6}}), but that would be have the tail wagging the dog as it’s business, and not IT that has that responsibility.

[[5]]Maneuver warfare @ Wikipedia[[5]]
[[6]]John Boyd @ Wikipedia[[6]]

I think that the new rules cast IT as something like that of a pit crew. IT doesn’t make the parts (though we might lash together something when in a pinch), nor do we steer the car. Our job is to swap the tyres, pump the fuel, and straighten the fender, all in that sliver of time available to us, so that the driver can focus on their race strategy and get back out on track as quickly as possible.

With that in mind, the following seems to be a fair (4 ± 2) minimum set to start with.

  • Timeliness. A late solution is often worse than no solution at all, as you’ve spent the money without realising any benefit. Or, as a wise sage once told me, management is the art of making a timely decision, and then making it work. Where before we could take the time to get it right (after all, the solution will be in the field for a long time and needs to support a lot of people, so better to discover problems early rather than later), now we just need to make sure the solution is good enough in the time available, and has the potential to grow to meet future demand. The large “productionisation” efforts of the past need to be broken into a series of incremental improvements (à la Gmail and the land of perpeputal beta), aligning investment with both opportunity and realised value.
  • Availability. Not just up time, but ensuring that all stakeholders (both in and outside the company, including partners and clients) can get access to the solutions and data they need. There’s little value in a sophisticated knowledge base solution if the sales team can’t use it in the field to answer customer questions in real time. Once they’ve had to fire up the laptop, and the 3G card, and the VPN, the moment has passed and the sale lost. Or worse, forcing them to head back to the bricks and mortar office. As I pointed out the other week, decisions are more important than data{{7}}, and success in this environment means empowering stakeholders to make the best possible decisions by ensuring that the have the data and functions they need, where they need, when they need it, and in a format that make it easy to consume.
  • Agility. Agility means creating an IT estate that meet the challenges we can see coming down the road. It doesn’t mean creating an infinitely flexible IT estate. Every bit of flexibility we create, every flex point we add, comes at a cost. Too much flexibility is a bad thing{{8}}, as it weighs us down. Think of formula one cars: they’re fast and they’re agile (which is why driving them tends to be a young mans game), and they’re very stiff. Agility comes from keeping the weight down and being prepared to act quickly. This means keeping things simple, ensuring that we have minimum set of moving parts required. The F1 crowd might have an eye for detail, such as putting nitrogen{{9}} in the tyres, but unnecessary moving parts that might reduce reliability or performance are eliminated. Agility is the cross product of weight, speed, reliability and flexibility, and we need to work to get them all into balance.
  • Sustainability. Business is not a sprint (ideally), and this means that cost and reliability remain important factors, but not the only factors. While timeliness, availability and agility might be what drive us forward, we need still need to ensure that IT is still a smooth running operation. The old rules saw cost and reliability as absolutes, and we strived to keep costs as low, and reliability as high, as possible. The new rules see us balancing sustainability with need, accepting (slightly) higher costs or lower reliability to provide a more timely, available or agile solution while still meeting business requirements. (I wonder if I should have called this one “balance”.)

[[7]]Decisions are more important than data @ PEG[[7]]
[[8]]Having too much SOA is a bad thing (and what we might do about it) @ PEG[[8]]
[[9]]Understanding the sport: Tyres @ formula1.com[[9]]

While by no mean complete or definitive, I think that’s a fair set of rules to start the discussion.

Is Generation X/Y/Z irrelevant?

Generational distinctions seem to make less and less sense every year. While my grandmother never learnt to drive a car, my mother happily uses a computer and the Internet. Yes, the pace of change has sped up, but it appears that so have we. Age is a very crude factor, and as we shift to increasing personalisation age looks less and less relevant as a driver for change.

Why then do we persist in reporting on how each generations’ habits and predilections will transform the workplace, school or retirement village, when in reality these institutions seem to becoming closer together rather than further apart? Competition in the workplace is the main driver for change, with individuals adopting the tools and techniques they need to get the job done, whatever generation they are from.

There’s been a lot of talk about how the next generation (whichever that happens to be) is going to change the world. We had it with the Greatest Generation. We had it with the Pre-Boomers and Baby Boomers. We had it with Gen X. Now we have it with Gen Y. This might have made sense some time ago, when changes in social mores and practices took longer than a single generation. Change takes time, and if the pressure is only gentle then we can expect significant time to pass before the change is substantial.

I remember my grandmother who never learn’t to drive. Back in the day, before World War II, women driving was not the done thing. My grandmother never learnt to use a video recorder, computer, or the Internet, either. The pressure to change was gentle, and she was happy with her lot.

Sociologists now tell to that the differences between populations is often less than the differences within populations. Or, put another way, on aggregate we’re all pretty much the same. The same is true for my grandmothers. While one never learn’t to drive (among other things), my other grandmother charted a different course. No, she never learnt to use the Internet, but she did take the time when her husband went off to war to learn how to drive, and the both had a bit of a crush on Cary Grant.

If we wizz forward to the present day, then we can see the same dynamics at work. My parents have, in the course of only a few years, leapt from a technology-free zone to the proud owners of laptops, a wireless network, and a passion for doing their own video editing. Even mother-in-law, who has zero experience with technology, bought a Wii recently. She also seems to have more luck with the Wii than her video recorder which she’s never been able to work.

The idea that technology adoption is generational seems to have eroded to the point of irrelevance. There was even a report recently (by Cisco I think, though I can’t find the link) where the researchers could find no significant correlation between new technology adoption and generational strata.

Why then do we persist in pigeon holing generations when it is proven to be counter productive? Not all Gen X’s want to kill themselves. I’m a Gen X, I even like Nirvana, and I’ve yet to have that urge. Not all Gen Y’s want to publish their lives on Facebook. And not all baby boomers want to be helicopter parents. The only accomplishment this type of media story achieves by promoting these stereotypes is to massage the ego of their target demographic. To divide people into generations and say that this generation likes certain tools and techniques, and this generation doesn’t, and will never adapt, is naive.

If we must categorise people, then it makes more sense to use something like NEOs to divide the population into vertical groups based on how we approach life. Do you like change? Do you not? Do you value your privacy? Are you willing to put everything out in public? And so on…

The pace of change has accelerated to the point that everyone’s challenge, from Pre-Boomers and Baby Boomers through to Generation Z, is how to cope with significant change over the next ten year. If we are, as some predict, moving to an innovation economy, then it is the ability to adapt that is most important. Those betting their organisation on a generational change will be sadly disappointed as no generation has a monopoly on coping with change.

A more productive approach is to seek out the people from all generations who thrive in change, and aim for a diverse workforce so that you can tap into the broad range of skills this diversity will provide. Ultimately competition in the workplace is the main determinant for change, with individuals adopting the tools and techniques they need to get the job done, whatever generation they are from.

Updated: Elliot Ross pointed out some interesting research and analysis by Forrester. Forrester coins the term Technographics in their Groundswell work, capture how different people adopt social technologies. There’s even a nice tool which enables you to slice-and-dice the demographics. I’ve added the tool below, and highly recommend taking a look at Forrester’s work.

Updated: Mark Bullen over at Net Gen Skeptic does a nice job of bring some evidence to the debate, with Six reasons to be sceptical.

We can be our own worst enemy

The only certainties in life are death and taxes, or so we’ve been told on numerous occasions. I’d like to add “change” to the list. Change, be it business change or change in our personal lives, has accelerated to the point that we can expect the environment we inhabit to change significantly in the immediate future, let along over the length of our careers. If we want our business to remain competitive in this ever evolving landscape, then overcoming our (and our team’s) own resistance to change is our biggest challenge.

The rules we have built our careers on, rules forged back in the industrial revolution, are starting to come apart. Most folk—from the Baby Boomers through to Gen Y—expect the skills they acquired in their formative years to support them well through to retirement. How we conduct business might change radically, driven by technological and societal change, but what we did in business could be assumed to change at a slower than generational pace. We might order over the internet rather than via a physical catalogue, or call a person via a mobile rather than call a place via a landline, but skills we learnt in our formative years would still serve us well. For example, project managers manage ever increasingly complex projects over the length of their career, even though how they manage projects has migrated from paper GANTT charts to MS Project, and now onto BaseCamp.

Which is interesting, as it is this what, the doctrine, which most people use to define themselves. A project manager manages projects, and has (most likely) built their career by managing increasingly larger projects and, eventually, programs. Enterprise architects work their way toward managing ever larger transformation programs. Consultants work to become stream leads, team leaders, finally running large teams across entire sectors or geographies. An so on. The length of someones career sees them narrowing their focus to specialise in a particular doctrine, while expanding their management responsibilities. It is this doctrine which most people define themselves by, and their career is an constant investment in doctrine to enhance their skills, increasing their value with respect to the doctrine they chose to focus on.

This is fine in a world when the doctrines a business needs to operate change slower than the duration of a typical career. But what happens if the pace of change accelerates? When the length of the average career becomes significantly longer than the useful life of the doctrines the business requires.

We’ve reached an interesting technological inflection point. Information technology to date could be characterized as the race for automation. The vast bulk of enterprise applications have been focused on automating a previously manual task. This might be data management (general ledger, CRM, et al) or transforming data (SAP APO). The applications we developed were designed as bolt-ons to existing business models. Much like adding an after-market turbo charger to your faithful steed. Most (if not all) of the doctrines in the technology profession have grown to support this model: the development and deployment of large IT assets to support an existing business.

However, the role of technology in business is changing. The market of enterprise applications has matured to the point where a range of vendors can supply you with applications to automate any area of the business you care to name, making these applications ubiquitous and commoditized.The new, emerging, model has us looking beyond business technology alignment, trying and identify new business models which can exploit synergies between the two. A trend Forrester has termed, Business-Technology.

The focus has shifted from asset to outcome, changing the rules we built our careers on. Our tendency to define ourselves by the doctrine we learnt/developed yesterday has become a liability. We focus on how we do something, not why we do it, making it hard to change our habits when the assumptions they are founded on no longer apply. With our old doctrines founded on the development and management of large IT assets, we’re ill-equipped to adapt to the new engagement models Business-Technology requires.

The shift to an outcome focus is part of the acceleration of the pace of business. The winners in this environment are constantly inventing new doctrine as they look for better ways to achieve the same outcome. How we conduct business is changing so rapidly that we can’t expect to be doing the same thing in five years time, let alone for the rest of our career. What we learnt to do in our mid 20’s is no longer (entirely) relevant, and doesn’t deliver the same outcome as it used to. Isn’t the definition of insanity continuing to do something the we know doesn’t work? So why, then, do we continue to launch major transformation programmes when we know they have a low chance of success in the current business and social environment? Doctrine has become dogma.

We need to (re)define ourselves along the lines of “I solve problems”: identifying with the outcomes we deliver, at both personal and departmental levels. This allows us to consider a range of doctrines/options/alternatives and look for the best path forward. If we adopt “I am an TOGAF enterprise architect” (or SixSigma black belt, or Prince2, or …) then they will just crank the handle as the process has become more important than the goal. If we adopt “how can I effectively evolve this IT estate the with tools I have”, then we’ll be more successful.

Rolls-Royce and Craig’s List are good examples of organisations using a focus on outcomes to driver their businesses forward. Bruce Lee might even be the poster child of this problem solving mentality. He studies a wide range of fighting doctrines, and designed some of his own, in an attempt to break his habits and find a better way.

Accelerate along the road to happiness

Our ability to effectively manage time is central to success in today’s hype-competitive business environment. The streamlined and high velocity value-chains we’ve created are designed to invest as little time (and money) as possible in unproductive business activities. However, being fast, being good at optimizing our day-to-day operations, is no longer enough. We’ve reached a point where managing the acceleration of our business—the ability to change direction, redeploy resources to meet new opportunities more rapidly than our competition—is the driver for best in category performance. If we can react faster than our competition then we can capitalize on a business opportunity (or disruption, as they are often the same) and harvest any value the opportunity created.

Time is our overarching business driver at the moment. We hope to be the first to approve a mortgage, capturing the customer before our competitors have even responded to the original application. We strive to be first to market with a new portable music device (Walkman or iPod), establishing early mover advantage and taking the dominant position in the market. Or we might simply want to quickly restore essential services—power, gas or water—to our customers, as they have become intensely dependent upon them. Globalization has leveled the playing field, as we’re all working from the same play book and leveraging the same resources. The most significant factor for success in this environment is the ability to execute faster than our competition—harvesting the value in an opportunity before they can.

This focus on time is a recent phenomena. Not long ago, no further back than the early nineties, we were more concerned with mass. The challenge was too get the job done. Keep the wheels turning in the factories. Keep the workers busy in their cubicles. Time is money, so we’re told, and we need to ensure that we don’t waste money by laying idle. Mass was the key to success—ensuring that we had enough work to do, enough raw materials to work on, to keep our business busy and productive.

When mass is the focus, then bigger is better. This is a world where global conglomerates rule, as size is the driver for success. Supply chains were designed so that enough stuff was available right next to the factory, where supply can be ensured, that the factory would never run out of raw materials and grind to a halt. Whether shuffling paperwork or shifting widgets, the ability to move more stuff around the business was always seen as an improvement.

This is also the world that created a pile of shipping containers too behold in the Persian Gulf, during the Gulf War in the early nineties. With no known destination, some containers couldn’t be delivered. Without a clear understanding of where they came from, others couldn’t be returned. A few of these orphaned containers were opened in an attempt to determine their destination or origin; however the sweltering Arabian sun was not kind to their contents, which included items such as raw poultry, so a stop was soon put to that. The containers just kept piling up. 22,000 of 50,000 containers simply became invisible, collecting in a pile that went by the jaunty name of Iron Mountain.

Iron Mountain: 22,000 containers that became invisible
Iron Mountain: 22,000 containers that became invisible

Our answer was to stop focusing on mass, on having enough stuff on hand to keep the wheels of industry turning. We have to admit that Iron Mountain proves that we could move sufficient mass. The next challenge was to ensure that materials arrived at just the right time for them to be consumed by the business. We moved from worrying about mass, to managing velocity.

Total quality management and process improvement efforts finally found their niche. LEAN and Six Sigma rolled through the business landscape ripping cost out businesses where-ever they went. Equipped with books on Toyota’s Production System and kanban cards, we ripped excess material from the supply chain. Raw materials arrive just-in-time, and we avoid the costs associated with storing and handling vast warehouses of material, as well as the working capital tied up in the stored material itself. Quality went up, process cycle times shrunk, and the pace of business accelerated. Much like the tea clippers from China in the 1800s, with the annual race to get the first crop back to London for the maximum profit (with skipper paid a profit share as an incentive along with their salary), we’re focused on cranking the handle of business as fast as possible.

Zara, a fashion retailer, is the poster child for this generation of business. The fashion industry is built around a value-chain that tries to push out regular product updates, beating up demand via runway shows and media coverage to support a seasonal marketing cycle. Zara takes a different approach, tracking customer preferences and trends as they happen in the stores and trying to deliver an appropriate design as rapidly as possible, allowing customer demand to pull fashion. By focusing on responding to customer demand, wherever it is, Zara has built an organization designed too minimize time from design to marketed product. For example, onshore, high-tech, agile production is preferred to low-tech but low cost, offshore production which involves long production delays. Zara takes two weeks to take a product to market, where the industry average is six months; the lifetime of Zara’s products is measured in weeks, rather than months; and the products offered in each store are tailored to the interests of the community it serves rather than a long term marketing plan.

The change in product life-cycle has created a material change to customer buying habits. Traditionally customers’ will visit a fashion store a few times a year to see what a new season brings. There is no real pressure to buy in any particular visit, as they know they can return to buy the same garment later. Zara, however, with it’s dramatically shortened product cycles, drives different behavior. Customer visit more often, as they can expect to see a new range each visit. They are also more likely too buy, as they know that there is little chance of the same garment being available the next time. This approach has made Zara the most profitable arm of Inditex, a holding company of eight retail brands, and one of the biggest success stories in Spanish business.

The dirty secret of high velocity, lean businesses is that they are fragile: small disturbances can create massive knock-on effects. As we’ve ripped fat from the value chain, we’ve also weakened its ability to react to, and resolve, disruptions. A stockout can now flow all the way back along the supply chain to the literal coal face, stalling the entire business value-chain. Restoring an essential service is delayed while we scramble to procure the vital missing part. Mortgage approvals are deferred while we try reallocate the work load of a valuer dealing with a personal emergency. Or our carefully synchronized product launch falls apart for what seems like a trivial reason somewhere on the other side of the globe.

Our most powerful tools in creating todays high velocity businesses—tools like straight-through processing, LEAN and Six Sigma—worked by removing variation from business processes to increase throughput. The same tools prevent us from effectively responding to these disruptions.

Opportunities today are more frequent, but disruptive and fleeting. An open air festival in the country might represent an opportunity for a tolling operator to manage parking in an adjacent field, if the solution can be deployed as sufficient scale rapidly enough. Or the current trend for pop-up retail stores (if new products rapidly come and go, then why not stores) could be moved from an exceptional, special occasion marketing tool, into the mainstream as a means to optimize sales day-by-day. Responding to these opportunities implies reconfiguring our business on the fly—rapidly integrating business exceptions into the core of our business. This might range from reconfiguring our carefully designed global supply chain, through changing core mortgage approval criteria and processes to modifying category management strategies in (near) real time.

Sam: Waiting while his bank sorts itself out
Sam: Waiting while his bank sorts itself out

We’re entering a time when our ability to change direction, adapting to and leveraging changes in the commercial environment as they occur, will drive our success. If we can react faster than the competition then we can capitalize on a business opportunity and harvest any value the opportunity creates. Our focus will become acceleration: working too build businesses with the flexibility and spare energy required to turn and respond rapidly. These businesses will be the F1 cars of business, providing a massive step in performance over more conventional organizations. And, just like F1, they will also require a new level of performance from our knowledge workers. If acceleration is our focus, then our biggest challenge will be creating time and space required by our knowledge workers to identify these opportunities, turn the steering wheel and leverage them as they occur.

Update: A friend of mine just pointed out that the logical progression of mass → velocity → acceleration naturally leads to jerk, which is an informal unit of measurement for the third derivative.