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Planning should not require a Gantt chart

2010/09/03 in Business-Technology, IT Strategy by peg | View Comments

There’s a standard slide in my bag of tricks which finds it’s way into a surprising number of presentations. It’s a simple slide, one allowing me to explore the idea of planning as a spectrum of possible methodologies rather than treating planning as an either-or choice: either be bottom-up reactive, or requiring us to engage is a major top-down planning processes. By combining elements of both top-down and bottom-up approaches we can modulate how reactive, or how proactive and predetermined, our execution is. The idea is to set the slider where we want it, at the position that best suits what we are trying to achieve, instead of being forced to one end of the spectrum or the other in a purely reactive or purely deliberative mode.

A slide for our times

A slide for our times

Planning has a bad name. How many projects get stuck in that endless spiral of planning (and re-planning) as they try to find their way to the middle of the project hedge maze? It doesn’t seem to matter if we’re planning the expansion of our business into a new geography or a major IT transformation, the process drives us all nuts; wasted days and nights spent constructing (and then deconstructing and reconstructing) elaborate Gantt charts which we’re all sure will never be used.

All of this runs counter to what could be called the first rule of management:

Make a timely decision, and then make it work.

Most organisations’ first thought is to focus on being reactive and deal with the problems of here and now. Unfortunately this too has its own challenges. The Agile software movement can be seen as one well documented reactive methodology which has seen mixed success. Where time, scope and cost are negotiable, taking a reactive approach is the same as choosing to put scope up for grabs. The result of the project will be whatever the project manages to deliver, unsurprisingly. This might be enough to realise the original business case, or it might not.

A top-down, deliberative, approach is planning as a chess game (the untimed[1] rather than the timed variety). We assume that we have complete information and can take as long as we want to formulate our next few moves. The more we know about our opponent — the more tacit knowledge we have about what might go wrong (and right) on a project — the better and more accurate our plans will be and the further into the future we can plan. We can measure and evaluate our current situation, use tools like scenario planning[2] to anticipate the future, or even hire an innovation consultancy to identify our next, disruptive move. In a perfect world the only limitation to our planning ability is our own ability to comprehend the problem at hand (or the number of tasks we can cram into a Gantt chart, whichever comes first).

The problem is the unexpected — the unpredicted (and possibly unpredictable) event — which makes our plans unravel. It’s the event that we didn’t manage to anticipate, invalidating our assumptions and converting a carefully crafted plan into wasted effort. The faster the environment changes the more likely it is that something unexpected will happen between the plan’s conception and the delivery of its final outcome. Even worse, we might not even finish planning before something unexpected pops up which invalidates our work to date, causing us to restart the planning process.

Take your average major IT transformation: a multiyear project involving a massive investment in both time and money. To kick-start the project we need to predict what the business will need when the transformation is finally delivered (and as I’ve said elsewhere, this is a challenge in itself[3]). If we’re lucky, then assumptions we’ve made about the business’s requirements will still hold true all the way through to the end. However, what’s more likely to happen is that the change orders will start arriving well before we’ve finished, possibly even we’ve completed requirements gathering. The team then struggles to divide their time between scheduled work and change orders before re-planning (and often re-planning again and again) to try and regain control of the project. Try as we may though, the end result is often more like coughing up a fur ball than the slick solution we originally imagined.

A reactive approach, on the other hand, doesn’t worry having about complete information. The focus is on reacting to events as they are encountered, with little thought to long term goals or strategy. A shotgun approach, as it were. We craft our strategy by creating a set of rules covering what we should do in all the circumstances we care about. See a stop sign? Stop. And so on. The challenge is to craft a set of rules which cover most eventualities, and this is a major focus of the “agile” methodologies. They try and craft their manifestos and playbooks to document the tactics — the rules — which they think will drive their projects in the right direction.

playbook [ˈpleɪˌbʊk]
n

  1. (Team Sports / American Football) a book containing a range of possible set plays
  2. a notional range of possible tactics in any sphere of activity

The American Heritage Dictionary of the English Language, Fourth Edition.

The unexpected is not a problem for a reactive approach: you simply deal with problems as they arrive. If you’re not expecting anything in particular, then whatever turns up must have been what your were expecting. (There is logic in there.) However, this puts you at the mercy of what does turn up; as you’re focused on reacting to events, the events which arrive (and the order they arrive in) determine where you end up. While cost and time (i.e. effort) might be fixed, scope (and therefor the final result) is up for grabs, making it hard to drive a reactive approach to planning to deliver a well defined outcome.

With it’s focus on incremental delivery and improvement, a reactive approach is not an obvious bedfellow for your major IT transformation. It’s modus operandi is to focus on shot term demands, understand what the business needs next, build that, and then iterate. The IT estate evolves (somewhat) organically as we add things here, patch things there, and generally muddle our way through. Yes, we are reacting to short term business needs, but at what cost? Its a bit like taking our hands off the tiller to leave ourselves to the mercy of the wind; our boat will probably stay afloat, as long as the weather isn’t too bad, but we have little control over where we end up. Without the ability to drive toward a clear, long term goal, we soon find that all the well meaning tactical decisions we’ve made have resulted in a giant fur ball, just like those occasions where we tried to drive the project forward with a giant Gantt chart.

Neither of these two approaches to planning are necessarily wrong; they’re just not suited to solve the sort of problems we’re dealing with in the new normal[5]. They represent two extremes — proactive and reactive planning — but we need to balance proactive and reactive, and find a middle path.

First we need to admit that we’re resource constrained. This might be in terms of time, the funds we have available, or even simply the number of people we can usefully bring to bear on a problem. (As Frederick Brooks[6] pointed, it might take one woman nine months to produce a baby, but we can’t expect nine woman to deliver a baby in one month.) And this is in an environment where meaningful business change is measured in months, if not weeks. The effort required to develop our plan needs to fit into the time available, and our approach needs to provide opportunities to regularly revisit our assumptions and allow us to react to changes within and without the project. We need need to be reactive, but not too reactive, as we need to work within an overarching framework so that we can have some confidence that we are working toward our long term goals.

People — that’s you and I — take a more pragmatic approach to planning. If we didn’t, then I couldn’t imagine that we would manage to make it through the day with everything we need to get done and the disruptions that we all deal with. Think about how you went to work this morning. (Or how you went to the local café for a coffee, if it’s the weekend.) You weren’t purely reactive. If you were then I expect you would still be lying in bed trying to sort out you manifesto and playbook, hoping for something to happen which will prod you in the right direction. Nor do you take an exclusively top-down, deliberative approach, popping open the laptop on your knee whilst in bed and firing up your favourite planning tool. You’d probably still be stuck in bed, working at the never-ending ending task of plotting exceptions and eventualities. (What should I do if the case of divine intervention?).

People take a middle road. We establish a clear goal, usually something quite prosaic, like:

Get to work (on time)

We have a clear understanding — a set of beliefs, things we expect to be true — of the context we need to do this in.

  • I’m lying in bed
  • it’s a weekday
  • the alarm has just gone off
  • the weather forecast was for a clear sky and sun
  • I’m feeling a bit pudgy today

We also have a library of plans — short patterns of behaviour — which we know that, either from experience or by design, will drive us toward our goal. For example, to get to work we might usually follow the pattern:

  1. get up
  2. shower
  3. get dressed
  4. eat
  5. commute to the office

where each of the steps in this pattern can also be goals themselves.

We might, for example, have a few different plans for commuting: one each for by car, by bike, via public transport, and so on. When it comes time to commute, we consider our beliefs (it’s sunny and I need the exercise) and choose what we think is the most suitable option (I’ll ride). If the option turns out to be a bad choice (one tyre on my bike is unexpectedly flat) or unsuitable due to some change in the environment (it starts raining when I’m less than a block from home), then you discard the plan and pick another (heading back to the garage to take the car). After all, we hadn’t invested much in developing or executing the plan so we’re not losing a lot by throwing it away.

The twisty path between us and our goal

The twisty path between us and our goal

The gap after each step provides us with time to pause and reflect, consider our goal, and respond to the environment by selecting how best to execute the next step. This ability to revisit our decisions frequently — at each step on the journey between the office and home — allows us to be reactive, but not too reactive, while the knowledge that each step is part of a large plan provides us with the confidence that we’re working toward our longer term goals. The more granular we make our plans the more opportunities we provide to react to changes in our environment, but at the cost of being less deliberative and proactive, and potentially less efficient. The more coarse grained we make our plans, the fewer opportunities we create for being reactive, by it allows us to be more deliberative and efficient in delivery.

By modulating the size of our plans — the size of the effort we commit to — we can set the slider where we want it on that planning scale, with reactive on one end, and top down deliberative. This lets us align our planning with the degree of uncertainty and change we’re seeing in the environment around us.

I’ve been using this approach to plan and manage business and IT strategies for some time, with a great deal of success. Most of the tooling required already exists in the business business world, tools such as strategy maps[8], mission statements[9], and project portfolio management tools. Using these tools we can clearly identify our goals, articulate the tactics we want to use to drive ourselves toward them, and then create a portfolio of work which realises the tactics.

For example, the mission of being a low cost service provider might result in a goal of having efficient operations (which we can measure via a benchmark), and the tactics we can use to deliver more efficient operations might include consolidation (reducing the number of offices, data centres, or event tools). We can realise this need for consolidation by identifying a set of small projects (such as shutting down a small data centre, and consolidating its servers into a major one), each of which delivers one step on the journey. These projects then become part of a larger portfolio of work, with the resources available and business priorities determining which projects are executed next.

Just like the example above of each one of us finding our way to work in the morning, this approach enables us to balance how reactive or proactive we are at any time. We can easily re-proritise in response to business change by updating the mix of projects to be executed, rather than through a major re-planning effort. At the same time, we can be sure that the portfolio of work is driving us toward our long term goals, as each project aligns with an organisational goal. Planning without a major Gantt chart.

References
1. Types of chess games defined at Chess.netMartin Börjesson has put together some nice resources on Scenario planningI’ve already told you 125% of what I know @ PEGThe new normal @ McKinsey QuarterlyFrederick Brooks on the Mythical Man MonthStrategy map defined @ Value Based Mangement by Kaplan & NortonMission statement defined @ The Centre for Business Planning↑

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Some new rules for IT

2010/06/15 in IT Strategy, Mailing List by peg | View Comments

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):

  • 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.

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

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.

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.

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”.)

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

References
1. The rules of Enterprise IT @ PEGLEO: Lyons Electronic Office. The first business computer. @ WikipediaThe IT department we have today is not the IT department we’ll need tomorrow @ PEGThe new normal @ McKinsey QuarterlyManeuver warfare @ WikipediaJohn Boyd @ WikipediaDecisions are more important than data @ PEGHaving too much SOA is a bad thing (and what we might do about it) @ PEGUnderstanding the sport: Tyres @ formula1.com↑

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The rules of enterprise IT

2010/06/08 in IT Strategy by peg | View Comments

As I’ve pointed out before (possibly as I’m quite fond of games[1]) the game of enterprise IT has a long an proud history. I’ve also pointed out that the rules of this game need to change if enterprise IT — as we know it — is to remain relevant in the future[2]. This is triggered a few interesting conversations at the pub on just what are the old rules of IT.

Enterprise IT, as we know it today, is an asset management business, the bastard son of Henry Ford’s moving production line. Enterprise IT takes the raw material of business processes and technology and turns them into automated solutions. From those first card tabulators through to today’s enterprise applications, the focus has been on delivering large IT solutions into the business.

The rules of enterprise IT are the therefore rules of business operations. After a fair amount of coffee and beer with friends, the following 4 ± 2 rules seems to be a fair minimum set (in no particular order).

Keep the lights on. Or, put more gently, the ticket to the strategy table is a smooth running business. Business has become totally reliant on IT, while at the same time IT is still seen as something of a black art run by a collection of unapproachable high priests. The board might complain about the cost and pain of an ERP upgrade, but they know they have to find the money if they want to successfully close the books at the end of the financial year. While this means that the money will usually be found, it also means that the number one rule of being a CIO is to keep the transactions flowing. Orders must be taken, products shipped (or services provided), invoices sent and cash collected. IT is an operational essential, and any CIO who can’t be trusted to keep the lights on won’t even have time to warm up their seat.

Save money. IT started as a cost saving exercise: automatic tabulation machines to replace rooms full of people shuffling papers, networks to eliminate the need to truck paper from one place to another. From those first few systems through to today’s modern enterprise solutions, applications have been seen as a tool to save time and money. Understand what the business processes or problem is, and then support the heavy information lifting with technology to drive cost savings and reduce cycle time. Business cases are driven by ideas like ROI, capturing these savings over time. Keep pushing the bottom line down. These incremental savings can add up to significant changes, such as Dell’s make-to-order solution[3] which enabled the company to operate with negative working capital (ie. they took your cash before they needed to pay their suppliers), but the overall approach is still based on using IT to drive cost savings through the automation of predefined business processes.

Build what you need. When applications are rare, then building them is an engineering challenge. You can’t just go to the store and by the parts you need, you need to create a lot of the parts yourself in your own machine shop. I remember the large teams (compared to today) from the start of my career. A CORBA project didn’t just need a team to implement the business logic, it needed a large infrastructure team (security guy, transaction guy …) as well. Many organisations (and their strong desire to build – or at least heavily customise – solutions) still work under this assumption. IT was the department to marshal large engineering teams who deliver the industrial grade solutions which can form the backbone of a business.

Ferrero Rocher

Crunch on the outside, soft and chewy in the middle.

Keep the outside outside. It’s common to have what is called a Ferrero Rocher[4] approach to IT: crunchy on the outside while soft and chewy in the middle. This applies to both security and data management. We visualise a strong distinction between inside and outside the enterprise. Inside we have our data, processes and people. Outside is everyone else (including our customers and partners). We harvest data from our operations and inject it into business intelligence solutions to create insight (and drive operational savings). We trust whatever’s inside our four walls, while deploying significant security measures to keep the evil outside.

It’s a separate question of whether or not these rules are still relevant in an age when business cycles are measured in weeks rather than years, and SaaS and cloud computing are emerging as the dominate modes of software delivery.

References
1. Capitalise: A game for the whole company to play!People don’t like change. (Or do they?)Dell’s make to order solution leaves competitors in the dust.Ferrero↑

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Business is like a train…

2010/06/01 in Business Intelligence, Business Process Management, IT Strategy by peg | View Comments

The following analogy popped up the other day in an email discussion with a friend.

Running a business is a bit like being the Fat Controller, running his vast train network. We spend our time trying to get the trains to run on time with the all too often distraction of digging the Troublesome Trucks out of trouble.

Improvement often means upgrading the tracks to create smoother, straighter lines. After years of doing this, any improvement to the tracks can only provide a minor, incremental benefit.

What we really need is a new signalling system. We need to better utilise the tracks we already have, and this means making better decisions about which trains to run where, and better coordination between the trains. Our tracks are fine (as long as we keep up the scheduled maintenance), but we do need to better manage transit across and between them.

Swap processes for tracks, and I think that this paints quite a nice visual picture.

Years of processes improvement (via LEAN, Six Sigma and, more recently, BPM) had straightened and smoothed our processes to the point that any additional investment has hit the law of diminishing returns. Rather than continue to try and improve the processes on my own, I’d outsource process maintenance to a collection of SaaS and BPO providers.

The greater scale of these providers allows them to invest in improvements which I don’t have the time or money for. Handing over responsibility also creates the time and space for me to focus on improving the decisions on which process to run where, and when: my signalling system.

This is especially important in a world where it is becoming rare to even own the processes these days.

We forget just how important a good signalling system is. Get it right and you get the German or Japanese train networks. Get it wrong and you rapidly descend into the second or third world, regardless of the quality of your tracks.

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Danger Will Robinson!

2010/05/20 in Business-Technology, IT Strategy by peg | View Comments

Ack! The scorecard's gone red!

Ack! The scorecard's gone red!

Andy Mulholland has a nice post over at the Capgemini CTO blog, which points out that we have a strange aversion to the colour red. Having red on your balanced scorecard is not necessarily a bad thing, as it tells you something that you didn’t know before. Insisting on managers delivering completely green scorecard is just throwing good information away.

Unfortunately something’s wrong with Capgemini’s blogging platform, and it won’t let me post a comment. Go and read the post, and then you can find my comment below.

Economists have a (rather old) saying: “if you don’t fail occasionally, then you’re not optimising (enough)”. We need to consider red squares on the board to be opportunities, just as much as they might be problems. Red just represents “something happened that we didn’t expect”. This might be bad (something broke), or it might be good (an opportunity).

Given the rapid pace of change today, and the high incidence of the unexpected, managing all the red out of your business instantly turns you into a dinosaur.

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Decisions are more important than data

2010/05/13 in Business-Technology, IT Strategy, Mailing List by peg | View Comments

Names and categories are important. Just look at the challenges faced by the archeology community as DNA evidence forces history to be rewritten when it breaks old understandings, changing how we think and feel in the process. Just who invaded who? Or was related to who?

We have the same problem with (enterprise) technology; how we think about the building blocks of the IT estate has a strong influence on how approach the problems we need to solve. Unfortunately our current taxonomy has a very functional basis, rooted as it is in the original challenge of creating the major IT assets we have today. This is a problem, as it’s preventing us to taking full advantage of the technologies available to us. If we want to move forward, creating solutions that will thrive in a post GFC world, then we need to think about enterprise IT in a different way.

Enterprise applications – the applications we often know and love (or hate) – fall into a few distinct types. A taxonomy, if you will. This taxonomy has a very functional basis, founded as it is on the challenge of delivering high performance and stable solutions into difficult operational environments. Categories tend to be focused on the technical role a group of assets have in the overall IT estate. We might quibble over the precise number of categories and their makeup, but for the purposes of this argument I’m going to go with three distinct categories (plus another one).

SABER

SABER @ American Airlines

First, there’s the applications responsible for data storage and coherence: the electronic filing cabinets that replaced rooms full of clerks and accountants back in the day. From the first computerised general ledger through to CRM, their business case is a simple one of automating paper shuffling. Put the data in on place and making access quick and easy; like SABER did, which I’ve mentioned before.

Next, are the data transformation tools. Applications which take a bunch of inputs and generate an answer. This might be a plan (production plan, staffing roster, transport planning or supply chain movements …) or a figure (price, tax, overnight interest calculation). State might be stored somewhere else, but these solutions still need some some serious computing power to cope with hugh bursts in demand.

Third is data presentation: taking corporate information and presenting in some form that humans can consume (though looking at my latest phone bill, there’s no attempt to make the data easy to consume). This might be billing or invoicing engines, application specific GUIs, or even portals.

We can also typically add one more category – data integration – though this is mainly the domain of data warehouses. Solutions that pull together data from multiple sources to create a summary view. This category of solutions wouldn’t exist aside from the fact that our operational, data management solutions, can’t cope with an additional reporting load. This is also the category for all those XLS spreadsheets that spread through business like a virus, as high integration costs or more important projects prevent us from supporting user requests.

A long time ago we’d bake all these layers into the one solution. SABER, I’m sure, did a bit of everything, though its main focus was data management. Client-server changed things a bit by breaking user interface from back-end data management, and then portals took this a step further. Planning tools (and other data transformation tools) started as modules in larger applications, eventually popping out as stand alone solutions when they grew large enough (and complex enough) to justify their own delivery effort. Now we have separate solutions in each of these categories, and a major integration problem.

This categorisation creates a number of problems for me. First and foremost is the disconnection between what business has become, and what technology is trying to be. Back in the day when “computer” referred to someone sitting at a desk computing ballistics tables, we organised data processing in much the same way that Henry Ford organised his production line. Our current approach to technology is simply the latest step in the automation of this production line.

Computers in the past

Computers in the past

Quite a bit has changed since then. We’ve reconfigured out businesses, we’re reconfiguring our IT departments, and we need to reconfigure our approach to IT. Business today is really a network of actors who collaborate to make decisions, with most (if not all) of the heavy data lifting done by technology. Retail chains are trying to reduce the transaction load on their team working the tills so that they can focus on customer relationships. The focus in supply chains to on ensuring that your network of exception managers can work together to effectively manage disruptions in the supply chain. Even head office focused on understanding and responding to market changes, rather than trying to optimise the business in an unchanging market.

The moving parts of business have changed. Henry Ford focused on mass: the challenge of scaling manufacturing processes to get cost down. We’re moved well beyond mass, through velocity, to focus on agility. A modern business is a collection of actors collaborating and making decisions, not a set of statically defined processes backed by technology assets. Trying to force modern business practices into yesterdays IT taxonomy is the source of one of the disconnects between business and IT that we complain so much about.

There’s no finer example of this than Sales and Operations Planning (S&OP). What should be a collaborative and fluid process – forward planning among a network of stakeholders – has been shoehorned into a traditional n-tier, database driven, enterprise solution. While an S&OP solution can provided significant cost saving, many companies find it too hard to fit themselves into the solution. It’s not surprising that S&OP has a reputation for being difficult to deploy and use, with many planners preferring to work around the system than with it.

I’ve been toying with a new taxonomy for a little while now, one that tries to reflect the decision, actor and collaboration centric nature of modern business. Rather than fit the people to the factory, which was the approach during the industrial revolution, the idea is to fit the factory to the people, which is the approach we use today post LEAN and flexible manufacturing. While it’s a work in progress, it still provides a good starting point for discussions on how we might use technology to support business in the new normal.

In no particular order…

Fusion solutions blend data and process to create a clear and coherent environment to support specific roles and decisions. The idea is to provide the right data and process, at the right time, in a format that is easy to consume and use, to drive the best possible decisions. This might involve blending internal data with externally sourced data (potentially scraped from a competitor’s web site); whatever data required. Providing a clear and consistent knowledge work environment, rather than the siloed and portaled environment we have today, will improve productivity (more time on work that matters, and less time on busy work) and efficiency (fewer mistakes).

Next, decisioning solutions automate key decisions in the enterprise. These decisions might range from mortgage approvals through office work, such as logistics exception management, to supporting knowledge workers workers in the field. We also need to acknowledge that decisions are often decision making processes which require logic (roles) applied over a number of discrete steps (processes). This should not be seen as replacing knowledge workers, as a more productive approach is to view decision automation as a way of amplifying our users talents.

While we have a lot of information, some information will need to be manufactured ourselves. This might range from simple charts generated from tabular data, through to logistics plans or maintenance scheduling, or even payroll.

Information and process access provide stakeholders (both people and organisations) with access to our corporate services. This is not your traditional portal to web based GUI, as the focus will be on providing stakeholders with access wherever and whenever they need, on whatever device they happen to be using. This would mean embedding your content into a Facebook app, rather than investing in a strategic portal infrastructure project. Or it might involve developing a payment gateway.

Finally we have asset management, responsible for managing your data as a corporate asset. This looks beyond the traditional storage and consistency requires for existing enterprise applications to include the political dimension, accessibility (I can get at my data whenever and wherever I want to) and stability (earthquakes, disaster recovery and the like).

It’s interesting to consider the sort of strategy a company might use around each of these categories. Manufacturing solutions – such as crew scheduling – are very transactional. Old data out, new data in. This makes them easily outsourced, or run as a bureau service. Asset management solutions map very well to SaaS: commoditized, simple and cost effective. Access solutions are similar to asset management.

Fusion and decisioning solutions are interesting. The complete solution is difficult to outsource. For many fusion solutions, the data and process set presented to knowledge workers will be unique and will change frequently, while decisioning solutions contain decisions which can represent our competitive advantage. On the other hand, it’s the intellectual content in these solutions, and not the platform, which makes them special. We could sell our platform to our competitors, or even use a commonly available SaaS platform, and still retain our competitive advantage, as the advantage is in the content, while our barrier to competition is the effort required to recreate the content.

This set of categories seems to map better to where we’re going with enterprise IT at the moment. Consider the S&OP solution I mention before. Rather than construct a large, traditional, data-centric enterprise application and change our work practices to suit, we break the problem into a number of mid-sized components and focus on driving the right decisions: fusion, decisioning, manufacturing, access, and asset management. Our solution strategy becomes more nuanced, as our goal is to blend components from each category to provide planners with the right information at the right time to enable them to make the best possible decision.

After all, when the focus is on business agility, and when we’re drowning in a see of information, decisions are more important than data.

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Complexity isn’t (at least in enterprise IT)

2010/05/11 in Business-Technology, IT Strategy by peg | View Comments

There’s a lot of talk these days about complexity in enterprise IT. The heterogeneous solutions we’re building today seem more complex than the monolithic solutions of the past. But are they really? I’ll grant you that a lot of what is being built at the moment is complicated. Complex though? I don’t think so. The problem is that we’re building new things in old ways when we need to be building new things in new ways.

I’ve always used a simple rule of thumb when thinking about complexity. Some folk like to get fancy with two and three dimensional models that enable us to ascribe degrees of complexity to problems. While I find these models interesting, my focus has always been on how do I solve the problem in front of me. What is the insight that will make the hard easy? For me, one simple distinction seems to provide the information I need. Is a solution complex? Or is it complicated?

Something is complicated if the model we use to understand the problem requires patches, exceptions to make it work. The model might be simple and well understood, but we’re forced to patch the model for it to succeed when confronted by the real world; we’re adding epicycles. It’s not a complex system, but it is complicated.

Adding epicycles didn't manage to keep the earth at the centre of the universe

Adding epicycles didn't manage to keep the earth at the centre of the universe

On the other hand, something is complex if it’s difficult to develop a consistent model for the problem. While we might have a well understood model, it’s definitely not simple, requiring a great deal of academic and tacit knowledge to understand. There’s no epicycles, but there are a large number of variables involved, and their interactions are often non-linear.

While this binary separation might not be strictly true (the complicated can sometimes be complex), I find that the truly complex problems are rare enough that the rule of thumb is useful most of the time. After all, that’s what a rule of thumb is. The few times that it breaks down, experience comes to the rescue.

Distinguishing between the complex and the complicated is not hard; just look for the epicycles. Planning engines – such as material planning or crew scheduling – are a good example of a complex solutions. Business processes management is a good example of a complicated solution. Psi calculus – the model at the heart of a modern BPM engine – is well understood and BPM engines work as described. However, managing business exceptions is a mess as support for them is tacked on rather than an inherent part of the model. Smashing together psi calculus, transactions and number of other models has resulted in epicycles.

Most of the problems we’re seeing in enterprise IT are complicated, but not complex. Take the current efforts to create IT estates integrating SaaS and public cloud with more traditional enterprise IT tools, such as on-premesis applications and BPO. Conventional approaches to understanding and planning IT estates are creaking at the seems. The model – the enterprise integration patterns – which we’ve used for so long is well understood, but it’s creaking at the seams as we bolt on more epicycles to cope with exceptions as they arise.

Dr. Khee Pang

Dr. Khee Pang

A great piece of advice from a former lecturer of mine always comes to mind in situations like this. As I’ve mentioned before:

If you don’t like a problem, then change it.
KK Pang

Our solution is complicated because we’re trying to solve the wrong problem. We need to change it.

The problem with BPM is that business exceptions are not exceptional, but are simply alternative ways of achieving the same goals. To resolve the epicycles we need to shift the problems centre of gravity, moving the earth from the centre of the universe to a more stable orbit. If business exceptions are not exceptional, then we should simply consider them as different business scenarios, and use a scenario based approach to capturing business processes. The epicycles then melt away.

I think we can use a similar approach to help us with the challenges we’re seeing in today’s IT estates, the same challenges which are trigger some of the discussion on complexity. The current approach to planning and provisioning IT is data centric; most applications are, after all, just large data management engines. This data-centric approach is forcing us to create epicycles as we attempt to integrate SaaS, cloud, and a whole raft of new tools and techniques. The solution is to move from a data-centric approach, to decision-centric approach. But that’s a different blog post.

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Having too much SOA is a bad thing (and what we might do about it)

2010/05/06 in Business-Technology, IT Strategy by peg | View Comments

SOA enablement projects (like a lot of IT projects) have a bad name. An initiative that starts as a good idea to create a bit more flexibility in the IT estate often seems to end up mired in its own complexity. The problem is usually too much flexibility, as flexibility creates complexity, and complexity exponentially increases the effort required to manage and deliver the software. Without any solid guidance on how much flexibility to create (and where to create it) most SOA initiatives simply keep creating flexibility until either the project collapses under its own weight, or the projected development work to create all the services exceeds the available CAPEX budget. A little flexility is good, but too much is bad. How can we scope the flexibility, pointing it where it’s most needed while preventing it from becoming a burden?

The challenge with SOA enablement is in determining how much flexibility to build into the IT estate. Some flexibility is good – especially if it’s focused on where the business needs it the most – but too much flexibility is simply another unnecessary cost. The last decade or so is littered with stories of companies who’s SOA initiatives were either brought to an early close or canned as they had consumed all the cash the business was prepared to invest into a major infrastructure project. Finance and telecoms seem particularly prone of creating these gold-plated SOA initiatives. (How many shelf-ware SDFs – service delivery frameworks – do you know of?)

The problem seems to be a lack of guidance on how much flexibility to build, or where to put it. We sold the business on the idea that a flexible, service-oriented IT estate would be better then the evil monolithic applications of old, but the details of just how flexible the new estate would be were a little fuzzy. Surely these details can be sorted out in service discovery? And governance should keep service discovery on track! We set ourselves up by over-promising and under-delivering.

Mario Batali: Too much is never enough!

Mario Batali

This much was clear: the business wanted agility, and agility requires flexibility. As flexibility comes from having more moving parts (services), we figured that creating more moving parts will create more agility. Service discovery rapidly became a process of identifying every bit of (reusable) functionality that we can pack into a service. More is better, or, as the man with the loud shoes says:

Too much is never enough!
Mario Batali

The problem with this approach is that it confuses flexibility and agility. It’s possible to be very flexible without being agile, and vica versa. Think of a formula one car: 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. They might have an eye for detail, such as nitrogen in the tyres, but unnecessary moving parts that might reduce reliability or performance are eliminated.

This gold plated approach to SOA creates a lot of unrequired flexibility, this additional flexibility increases complexity, and the complexity becomes the boat anchor that slows you down and stops you from being agile. Turning the car is no longer a simple of tugging on the steering wheel, as we need governance to stop us from pulling the wrong lever in the bank of 500 identical levers in front of us.

It's really that simple!

It's really that simple!

We’ve made everything too complicated. Mario was wrong: too much is too much.

What we need is some guidance – a way of scoping and directing the flexibility we’re going to create. Governance isn’t enough, as governance is focused on stopping bad things from happening. We have a scoping problem. Our challenge is to understand what flexibility will be required in the future, and agreeing on the best way to support it.

To date I’ve been using a very fuzzy “business interest” metric for this, where services are decomposed until the business is no longer interested. The rational is that we put the flexibility only were the business thinks it needs to focus. This approach works fairly well, but it relies too much on the tacit judgement of a few skilled business analysts and architects, making it too opaque and hard to understand for the people not involved in the decision making process. It’s also hard to scale. We need something more deterministic and repeatable.

Which brings me to a friend’s MBA thesis, which he passed to me the other week. It’s an interesting approach to building business cases for IT solutions, one based on real options.

The problem with the usual approaches to building a business case, using tools like net present value (NPV) and discounted cash flow, is that we assume that the world doesn’t change post the decision to build the solution (or not). They don’t factor in the need to change a solution once it’s in the field, or even during development.

The world doesn’t work this way: the solution you approved in yesterday’s business environment will be deployed into a radically different business environment tomorrow. This makes it hard to justify the additional investment required for a more flexible SOA based solution, when compared to a conventional monolithic solution. The business case doesn’t include flexibility as a factor, so more flexible (and therefore complex and expensive) solutions lose to the cheaper, monolithic approach.

Real options address this by pushing you down a scenario planning based approach. You estimate the future events that you want to guard against, and their probabilities, creating a set of possible futures. Each event presents you with options to take action. The action, for example, might be to change, update or replace components in the solution to bring them in line with evolving business realities. The options are – in effect – flex-points that we might design into our solutions SOA. The real options methodology enables us to ascribe costs to these future events and the create a decision tree that captures the benefits of investing in specific flex points, all in a clear and easily understandable chain of reasoning.

The decision tree and options provide us with a way to map out where to place flex points in the SOA solution. They also provide us with strong guidance on how much flexibility to introduce. And this is the part I found really interesting about the approach. It also provides us with a nice framework to govern the evolution of the SOA solution, as changes are (generally) only made when an option is taken: when it’s business case is triggered.

It’s a bit like those formula one cars. A friend of mine used to work for one F1 manufacturer designing and testing camshafts. These camshafts had to fall within a 100,000 lifetime revolution window. An over-designed camshaft was unnecessary weight, while an under-designed one means that you wouldn’t win (or possibly even finish) the race. Work it out: a 100,000 revolutions is a tiny window for an F1 car, given the length of a race.

An approach like real options helps us ensure that we only have the flexibility required in the solution, and that it is exactly where it is required. Not too much, and not too little. Just enough to help us win the race.

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The IT department we have today is not the IT department we’ll need tomorrow

2010/04/21 in Business-Technology, IT Strategy, Mailing List by peg | View Comments

The IT departments many of us work in today (either as an employee or consultant) are often the result of thirty or more years of diligent labour. These departments are designed, optimised even, to create IT estates populated with large, expensive applications. Unfortunately these departments are also looking a lot like dinosaurs: large, slow and altogether unsuited for the the new normal. The challenge is to reconfigure our departments, transforming them from asset management functions into business (or business-technology) optimisation engines. This transformation should be a keen interest for all of us, as it’s going to drive a dramatic change in staffing profiles which will, in turn, effect our own jobs in the no so distant future.

Delivering large IT solutions is a tricky business. They’re big. They’re expensive. And the projects to create them go off the rails more often than we’d like to admit. IT departments have been built to minimise the risks associated with delivering and operating these applications. This means governance, and usually quite a lot of it. Departments which started off as small scale engineering functions soon picked up an administrative layer responsible to the mechanics of governance.

More recently we’ve been confronted with the challenge with managing the dependancies and interactions between IT applications. Initiatives like straight-through processing require us to take a holistic, rather than a pieces-parts, approach, and we’re all dealing with the problem of having one of each application or middleware product, as well as a few we brewed in the back room ourselves. Planning the operation and evolution of the IT estate became more important, and we picked up an enterprise architecture capability to manage the evolution of our IT estate.

It’s common to visualise these various departmental functions and roles as a triangle (or a pyramid, if you prefer). At the bottom we have engineering: the developers and other technical personnel who do the actual work to build and maintain our applications. Next layer up is governance, the project and operational administrators who schedule the work and check that it’s done to spec. Second from the top are the planners, the architects responsible for shaping the work to be done as well as acting as design authority. Capping of the triangle (or pyramid) is the IT leadership team who decide what should be done.

The departmental skills triangle

While specific techniques and technologies might come and go, the overall composition of the triangle has remained the same. From the sixties and seventies through to even quite recently, we’ve staffed our IT departments with many technical doers, a few less administrators, a smaller planning team, and a small IT leadership group. The career path for most of us been a progression from the bottom layers – when we were fresh out of school – to the highest point in the triangle that we can manage.

The emergence of off-shore and outsourcing put a spanner in the works. We all understand the rational: migrate the more junior positions – the positions with the least direct (if any) contact with the business proper – to a cheaper country. Many companies under intense cost pressure broke the triangle in two, keeping the upper planning and decision roles, while pushing the majority of the manage and all the do roles out of the country, or even out of the company.

Our first attempt at out-sourcing

Ignoring whether or not this drive to externalise the lower roles provided the expected savings or not, what it did do is break the career ladder for IT staff. Where does you next generation of senior IT personnel come from if you’ve pushed the lower ranks out of the business? Many companies found themselves with an awkward skills shortage a few years into an outsourcing / off-shore arrangement, as they were no longer able to train or promote senior personnel to replace those who were leaving through natural attrition.

The solution to this was to change how we brake-up the skills triangle; rather than a simple horizontal cut, we took a slice down the side. Retaining a portion of all skills in-house allows companies provide a career path and on the job training for their staff.

A second, improved, go at out-sourcing

A second, improved, go at out-sourcing

Many companies have tweaked this model, adding a bulge in the middle to provide a large enough resource pool to manage both internal projects, as well as those run by out-sourced and off-shore resources.

Factoring in the effort required to manage out-sourced projects

Factoring in the effort required to manage out-sourced projects

This model is now common in a lot of large companies, and it has served us well. However, the world has a funny habit of changing just when you’ve everything working smoothly.

The recent global financial criss has fundamentally changed the business landscape. We are experiencing not merely another turn of the business cycle, but a restructuring of the economic order. Many are even talking about the emergence of a new normal. The impact this will have on how we run our businesses (and our IT departments) is still being discussed, but we can see the outline of this impact already.

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 internal capabilities. While this trend might have initially started as a cost saving, most of the benefit is in management time saved, which can then be used to focus on more important issues. We’re all finding that the limiting factor in our business is management time, so being able to hand off the management of less important tasks can help provide that edge you need.

We’re also seeing faster 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. Nowhere is this more evident than the regulated industries (finance, utilities …), where updates in government regulation has changed from a generational to a quarterly occurrence as governments attempt to use regulation change to steer the economic boat.

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.

We can draw a few general conclusions on the potential impact on IT departments of these trends.

  • The increase reliance on partners, the broader partner ecosystem this implies, and an increasingly global approach to business will create more complex operational environments, increasing the importance of planning the IT estate and steering a company’s IT in the right direction.
  • The need to reduce leverage, and free up working capital, is pushing companies toward BPO and SaaS solutions, rather than the traditional on-premisses solutions, where the solution provider is paid per-seat, or might even be only paid a success fee.
  • The need for rapid project turn-around is pushing us toward running large portfolios of small projects, rather than a small number of large projects.
  • A lot of the admin work we used to do is now baked into web delivered solutions (BaseCamp et al).

This will trigger us to break up a the skills triangle in a different way.

A skills/roles triangle for the new normal

A skills/roles triangle for the new normal

While we’ll still take a slice down the side of the triangle, the buldge will move to the ends of the slice, giving it a skinny waist. The more complex operational environment means that we need to beef up planning (though we don’t want to get all dogmatic about our approach, as existing asset-centric IT planning methodologies won’t work in the new normal). A shift to large numbers of small projects (where the projects are potentially more technically complex) means that we’ll beef up our internal delivery capability, providing team leads with more autonomy. The move to smaller projects also means that we can reduce our administration and governance overhead.

We’ll replace some skills with automated (SaaS) solutions. Tools like BaseCamp will enable us to devolve responsibility for reporting and management to the team at the coalface. It will also reduce the need to develop and maintain infrastructure. Cloud technology is a good example of this, as it takes a lot of the tacit knowledge required to manage a fleet of servers and bakes it into software, placing it in the hands of the developers. Rumor has it that that a cloud admin can support 10,000 servers to a more traditional admin’s 500.

And finally, our suppliers act as a layer through the middle, a flex resource for us to call on. They can also provide us with a broader, cross-industry view, of how to best leverage technology.

This thinning out of the middle ranks is part of a trend we’re seeing elsewhere. Web2.0/E2.0/et al are causing organisations to remove knowledge workers — the traditional white collar middle layers of the organisaiton – leaving companies with a strategy/leadership group and task workers.

Update: Andy Mulholland has an interesting build on this post over at the Capgemini CTO blog. I particularly like the Holm service launched by Ford and Microsoft, a service that it’s hard to imagine a traditional IT department fielding.

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With cloud computing, the world is not flat

2010/03/09 in Cloud & SaaS, IT Strategy, Mailing List by peg | View Comments

Does location matter? Or, put another way, is the world no longer flat? Many cloud and SaaS providers work under the assumption that where we store data where it is most efficient from an application performance point of view, ignoring political considerations. This runs counter to many company and governments who care greatly where their data is stored. Have we entered a time where location does matter, not for technical reasons, but for political reasons? Is globalisation (as a political thing) finally starting to impact IT architecture and strategy?

Just who is taking your order?

Just who is taking your order?

Thomas Friedman‘s book, The World is Flat, contained a number of stories which where real eye openers. The one I remember the most was the McDonald’s drive through. The idea was simple: once you’ve removed direct physical contact from the ordering process, then it’s more efficient to accept orders from a contact centre than from within the restaurant itself. We could event locate that contact centre in a cheaper geography such as another state, or even another country.

Telecommunications made the world flat, as cheap telecommunications allows us to locate work wherever it is cheapest. The opportunity for labour arbitrage this created drove offshoring through the late nineties and into the new millenium. Everything from call centres to tax returns and medical image diagnosis started to migrate to cheaper geographies. Competition to be the cheapest and most efficient service provider, rather than location, determines who does the work. The entire world would compete on a level playing field.

In the background, whilst this was happening, enterprise applications went from common to ubiquitous. Adoption was driven by the productivity benefits the applications brought, which started of as a source of differentiation, but has now become one of the many requirements of being in business. SaaS and cloud are the most recent step in this evolution, leveraging the global market to create solutions operating at such a massive scale that they can provide price points and service levels which are hard, if not impossible, for most companies to achieve internally.

The growth of the U.S. enterprise application market

The growth of the U.S. enterprise application market (via INPUT)

Despite the world being laser levelled within an inch of its life, many companies are finding it difficult to move their operations to the cost-effective nirvana that is cloud and SaaS services. Location matters, it seems. Not for technical reasons, but for political ones.

Where we store our assets is important. Organisations want to put their assets somewhere safe, because without assets these the organisations don’t amount to much. Companies want to keep their information — their confidential trade secrets — hidden from prying eyes. Governments need to ensure they have the trust of their citizens by respecting their privacy. (Not to mention the skullduggery this is international relations.) While communications technology has made it incredibly easy to move this information around and keep it secure, it has yet to solve the political problem of ensuring that we can trust the people responsible for safeguarding our assets. And all these applications we have created — both the traditional on-premesis, hosted or SaaS and cloud versions — are really just asset management tools.

We’re reached a point where one of the a larger hidden assumptions of enterprise applications has been exposed. Each application was designed to live and operate within a single organisation. This organisation might be a company, or it might be a country, or it might be some combination of the two. The application you select to manage your data determines the political boundary it lives within. If you use any U.S. SaaS or cloud solution provider to manage your data, then your data falls under U.S. judicial discovery laws, irregardless of where you yourself are located. If your data transits through the U.S., then assume that the U.S. government has a copy. The world might be flat, but where you store your assets and where you send them still matters.

Country-specific regulations governing privacy and data protection vary greatly.

Global data protection heat map (via Forrester)

We can already see some moves by the vendors to address this problem. Microsoft, for example, has developed a dedicated cloud for the U.S. government, known as BPOS Federal, which is designed to meet the government’s stringent security and privacy standards. Amazon has also taken a portion of the cloud it runs and dedicated it to, and located it in, the EU, for similar reasons.

If we consider enterprise applications to be asset management tools rather than productivity tools, then ideas like private clouds start to make a lot of sense. Cloud technology reifies a lot of the knowledge required to configure and manage a virtualised environment in software, eliminating the data centre voodoo and empowering the development teams to manage the solutions themselves. This makes cloud technology simply a better asset management tool, but we need to freedom to locate the data (and therefore the application) where it makes the most sense from an asset management point of view. Sometimes this might imply a large, location agnostic, public cloud. Other times it might require a much smaller private cloud located within a specific political boundary. (And the need to prevent some data even transiting through a few specific geographies – requiring us to move the code to the data, rather than the data to the code – might be the killer application that mobile agents have been waiting for.)

What we really need are meta-clouds: clouds created by aggregating a number of different clouds, just as the Internet is a network of separate networks. While the clouds would all be technically similar, each would be located in a different political geography. This might be inside vs. outside the organisation, or in different states, or even different countries. The data would be stored and maintained where it made the most sense from an asset management point of view, with few technical considerations, the meta-cloud providing a consistent approach to locating and moving our assets within and across individual clouds as we see fit.

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