Navigating the Information Management maze

The CIO of 2020

What will the role of Chief Information Officer (CIO) look like in 2020?

The CIO role is one that really appeared during the 1990s in response to the increasing profile of Information Technology (IT) in organisations.  Previously, the person in charge of IT was usually called an Information Technology, Information Services or Computer Services Director.  The creation of the “chief” title shows the world how critical IT is in the modern enterprise.

The problem is that the IT world is changing in a way that we haven’t seen in over a decade.  I argue that the first decade of the century was one in which little actually changed in the use of IT in business.  When I take this position in discussions I’m often met with many who disagree.

My argument is illustrated by comparing a typical professional worker’s desk in 2000 to the same desk in 2010.  The year 2000 desk probably had a laptop, telephone that was likely (or soon to be) based on IP telephony making them highly mobile.  It is also very likely that the business applications were little different to those we know today using Microsoft Windows, an ERP such as SAP for business operations and Microsoft Office for email and documents.  Sitting beside the computer was a mobile phone.  The 2010 picture is very similar.

Interestingly the comparison between the 1990 desk and the one at the turn of the century is much more dramatic.  The 1990 desk was very likely to have no computer, a terminal or if there was a PC it would have been deskbound.  The telephone was absolutely fixed to a point using a traditional PABX and there would not have been a mobile phone.  Any software being used would look very different to the products we commonly use today and likely to be bespoke and certainly character rather than graphics based.

This is a trend that we have seen before.  The 1970s saw massive change, while the 1980s was really a decade of consolidation.  While much happened in both the 1980s and the last decade, both were really dominated by a need to simplify and consolidate the role of IT in business.  As a result, we have been lulled into a view of the CIO which needs to focus first and foremost on the discipline of managing a complex but predictable portfolio of systems and projects.

Already in this new decade we’ve seen a move away from a single operating system (Windows) and end-user platform to a wide range of consumer-driven options ranging from tablets to mobile phones.   Similarly we’ve seeing a move away from enterprise servers to a much richer suite of options utilising cloud services.  Just as importantly, we’re seeing the long-predicted “internet of things” coming to life with embedded computing in everything from trucks to shopping trolleys.

No aspect of business value chains has been untouched by these changes.  The line between consumer technology and business systems has blurred to the point where customers expect to directly access their transaction data as it appears inside back-office applications.  This level of integration challenges the role of the CIO that has evolved during the last decade as being focused on business systems.  In this new world, the CIO is responsible for technology and information that is used by the businesses external stakeholders (including customers and suppliers).  This new CIO is as responsible for earning revenue as any divisional general manager.

The challenges will be substantial.  The CIO cannot hold onto the same number of staff that has been traditionally needed to run the infrastructure of the enterprise and still expect to take on revenue earning responsibilities.  The CIO is also going to need to lead large-scale innovation across the organisation with the goal of creating new products and finding new uses for the information that is the lifeblood of the enterprise.  This new CIO role doesn’t just serve the business, it also shapes it.

If CIOs don’t take on these challenges, then technology will be distributed across business divisions and an opportunity will be lost to innovate while maintaining the discipline that modern IT has fought to implement over the last thirty years.  This is a battle that is worth having.

Value of decommissioning legacy systems

Most organisations reward their project managers for achieving scope, within a given timeframe for a specified budget.  While scope is usually measured in terms of user functions most projects usually include the decommissioning of legacy systems.  Unfortunately it is the decommissioning step which is most often compromised in the final stages of any project.

I’ve previously written about the need to measure complexity (see CIOs need to measure the right things).  One of the pieces of feedback I have received from a number of CIOs over the past few months has been that it is very hard to get a business case for decommissioning over the line from a financial perspective.  What’s more, even when it is included in the business case for a new system, it is very hard to avoid it being removed during the inevitable scope and budget management that most major projects go through.

One approach to estimating the benefit of decommissioning is to list out the activities that will be simpler as a result of removing the system.  These can include duplicated user effort, reduced operational management costs and, most importantly, a reduction in the effort to implement new systems.  The problem is that last of these is the most valuable but is very hard to estimate deterministically.  Worse, by the time you do know, it is likely to be too late to actually perform the decommissioning.  For that reason, it is better to take a modelling approach across the portfolio rather than try to prove the cost savings using a list of known projects.

The complexity that legacy systems introduce to new system development is largely proportional to the cost of developing information interfaces to those systems.  Because the number of interfaces grow to the power of the number of systems, the complexity they introduce is a logarithmic function as shown below.

Any model is only going to provide a basis for estimating, but I outline here a simple and effective approach.

Start by defining c as the investment per new system and n as the number of system builds expected over 5 years.  Investment cost for a domain is therefore c times n.  For this example assume c as $2M and n as 3 giving an investment of $6M.

However the number of legacy systems (l) add complexity at a rate that rapidly increases most initially before trailing off (logarithmic).  The complexity factor (f), is dependent on the ratio of the cost of software to development (c) to the average interface cost (i):

f=log_c/i(l+1)

For this example assume l as 2 and i as $200K:

f=log₁₀(3)=0.48

The complexity factor can then be applied to the original investment:

c x n x (f+1)

In this example the five year saving of decommissioning the three systems in terms of future savings would be of the order of $2.9M.  It is important to note that efficiencies in interfacing similarly provide benefit.  As the cost of interfacing drops the logarithm base increases and the complexity factor naturally decreases.  Even arguing that the proportion of the ratio needs to be adjusted doesn’t substantially affect the complexity factor.

While this is only one method of identifying a savings trend, it provides a good starting point for more detailed modelling of benefits.  At the very least it provides the basis for an argument that the value of decommissioning legacy system shouldn’t be ignored simply because the exact benefits cannot be immediately identified.

Embracing the unexpected

The nineteen century belonged to the engineers.  Western society had been invigorated and changed beyond recognition by the industrial revolution through its early years and by its close the railroads were synonymous with the building of wealth.

The nineteen century was the era that saw the building of modern business with the foundation being established for many of the great companies that we know today.  The management thinkers who defined the discipline cluster around the first part of the twentieth century and it should be no surprise that they were heavily influenced by the engineers.

Business was built around the idea of engineered processes with defined inputs and outputs.  I’ve written before about the shift from process-driven to information-driven business.  In this post, though, I am really focusing on another consequence of the engineering approach to the running of businesses, the expectation of achieving planned outcomes.

There is a lot to be said for achieving a plan.  Investors dream of certainty in their returns.  Complex businesses like to be able to align production schedules.  Staff like knowing that they have a long-term job.

When you’re building a bridge or a railroad, there is certainty in the desired outcome.  Success is measured in terms of a completed project against time and budget.

When your business has a goal of providing products or services into a market, the definition of success is much harder to nail down.  You want your product or service to be profitable, but you are usually flexible on its exact definition.  However, internal structures tend not to have this flexibility built in.  Large businesses operate by ensuring each part of the organisation delivers their component of a new project as specified by the overall design.

This sounds fine until you look at these components in more detail.  Many are fiendishly complex.  In particular the IT can often involve many existing and new systems which have to be interfaced in ways that were never intended when they were originally created.  Staff trained to achieve a single outcome in the market keep on testing customers until they gain (or even bludgeon) acceptance for the product or service design.

Because of the scale of these projects, failure is not an option.  The business engineering philosophy that I’ve described will push the launch through regardless of the obstacles.  However, there is a growing trend in business to try and use “big data” to run experiments and confirm that the design of a new product or service is correct before this effort is undertaken.

There is also another trend in business.  Agile.  Agile methods are characterised by an evolutionary approach to achieving system outcomes.

Individually these trends make sense.  Taken together they may actually be starting to indicate a deeper change.  In a future world we may treat business as an experiment in its own right.  We know what the outcome is that we expect, but we will push our teams to embrace issues and look for systemic obstacles to guide us in new, and potentially more profitable, directions.

When customers don’t react positively to our initial designs, rather than adjust the design to their aesthetic, business should ask whether the product is appropriate at all and consider making a radical shift even at the last minute.

When IT finds that a system change is harder than they expected, they can legitimately ask whether there is a compromise that will deliver a different answer that might be equally acceptable, or sometimes even more useful.

One of the major differences between scientists and engineers is that the former look for the unexpected in their experiments and try to focus on the underlying knowledge they can get from things not going as planned.  Perhaps twenty-first century business needs less people thinking like engineers trying to railroad new products and services into the market and more who are willing to don the lab coat of a scientist who is willing to allow the complexity of modern business to flourish and support their innovation.

The future of social networks

When the telephone was invented the first networks were private, typically between rich individuals and their industrial interests.  Pretty quickly, though, people wanted to be able to talk to each other without the need to worry about multiple networks and, of course, we regard this as a basic requirement of any telephony solution today.

Similarly, when mobile networks were popularised, there were many attempts to increase subscriber numbers on individual networks by offering incentives to have family and friends connect through the same provider.  Those days are ending as people take advantage of ongoing commoditisation and the real cost of mobile phone calls becomes less significant.

Social networks have offered something truly new, the ability to communicate information seamlessly between groups and individuals.  MySpace, Facebook and LinkedIn have captured our imaginations as they've become a platform for sharing messages, rich media and even sophisticated games, collaboration tools as well as real time messaging and voice or video calls.  The products are increasingly becoming part of mainstream communications and look more like networks than online tools.  As such, they are facing the same stability, security and connectivity pressures that other commercial communications providers have to deal with.

If history is any guide, it is not the platform that makes them compelling, it is the ability to connect to others.  It is the network that attracts as much as any individual features.  Therefore it is worth asking: how long will the public accept private or isolated social networks?  How long before they demand that they be interconnected?

The alliance between Facebook and Skype is interesting because it completes the picture of the social network as a communications solution.  It is also one of the first examples where a social network (Facebook) has allowed another network (Skype) to manage “friends” across network boundaries.  In the next few years there will be a push to make this the norm rather than an exception.  You will be able to "friend" someone's Facebook profile from your LinkedIn account, contact a Google+ user directly from Skype and so on.  This is no different to making a call across phone networks.  If Facebook want their use of a calling platform to be anything more than a toy then this is inevitable and any networks resisting will be abandoned by their members.

Such a move, though, is a threat to the value of social networks.  Exclusivity and barriers ensure that the content generated remains exclusive to the network.  Facebook and LinkedIn run the risk of losing some of their inherent value when user information is open across networks.  There is also the potential for smaller players, such as Plaxo and MySpace, to get a second bite at popularity when the size of the network is less of an impediment (think about the role of niche phone companies today).

Reluctance by members to have their content completely tied-up on a platform is already something that both Google and Facebook have tried to assuage by providing services to allow users to download all of their data themselves through Google Takeout and Facebook’s user data download feature (under account settings).  Given that this does nothing more than provide a local backup, this will not quell the demands to open the networks up.

Investors increasingly realise that the value of a business is in the information that it holds and the level of exclusivity of that content.  Think of the data that Amazon holds about the buying habits of their customers or the music preferences that Apple tracks through iTunes.  As telephone networks have become increasingly commoditised, much of their value and premium has diminished and so it could be with the social networks unless they can find a way to allow their networks to open up without losing the premium and exclusive information that they track about you and me.

Paying for value rather than activity

Since the 1980s the costs associated with functions that are shared have been increasingly allocated to business units in such a way as to drive accountability.

For information technology this was relatively easy in the late 1980s as the majority of costs were associated with the expense of infrastructure or processing.  Typically the cost of the mainframe was allocated based on usage.  Through the 1990s, costs moved increasingly to a project focus with a model that encouraged good project governance and the allocation of infrastructure based on functions delivered.

Arguably, the unfortunate side effect of the allocation of project costs has been that many business units see information technology as being unnecessarily expensive – whereas many of the costs are really just reflecting the sheer complexity of business technology (see my previous post: CIOs need to measure the right things).  Such an approach to cost allocation has allowed business units to execute projects of increasing sophistication; however it may not be ensuring that information technology is being used in the way that will achieve the greatest possible strategic impact.

The other problem with the project-focused approach to cost recovery is that the CIO’s role is diminished to being that of a service provider.  In some organisations this has gone so far as to result in the CIO seeing external service providers as competitors.

Refocusing the cost recovery to the value achieved has the potential to deal the CIO back into the strategic debate.  As I’ve said before, information technology is extremely complex and requires experience and insight in order to identify the real opportunities to use it effectively to support and differentiate any business.  During the next decade, we are likely to see the continued blurring of the lines between internal business technology, joint ventures and the products that consumers use.  For instance, joint venture partners expect to see detailed financial reports across boundaries and consumers are used to helping themselves through the same interfaces that were previously restricted to call centre operators.

Recently on the web there has been some discussion on whether information should be valued.  At the same time there has been good progress in the development of techniques to value information assets (for instance, see the MIKE2.0 article on Information Economics).  The value of information is a very good way of predicting likely business value, even when the way that value will be realised has not yet been determined.  The disruption to previously stable businesses, such as retail, telecommunications and manufacturing, are very good examples of why it is important to understand value beyond the horizon of current revenue models.

Allocating at least some of the cost of an effective information technology department based on value focuses the budget debate on the development of revenue earning products that will leverage these new capabilities.  It also ensures that those units receiving the greatest potential value are motivated to realise it.  Finally, the move away from a largely activity-based approach to measuring cost reduces the tendency to continually cut project scopes to keep within defined budget.

A small idea with big implications

In the 1990s Philippe Kahn, a founder of Borland (a big name in programming languages), left and began a new enterprise called Starfish.  He talked in several interviews about creating small lightweight software that ran as part of the desktop or on mobile devices.  Today, this seems obvious, but back then it was anything but.

I remember reading about Starfish in 1994 and wondering how a company that made claim to reject the idea of the large software solution was actually going to generate any real money.  In fact, Starfish was bought by Motorola in 1998 and its intellectual property lives on in the form of the synchronisation that we use in many of our mobile devices.  The experiment in lightweight software that I doubted at the time has turned out to sit underneath some of the technology that today is changing the face of the industry.

When Kahn first talked about small agile software products for Starfish it was the time when big solutions were on the rise: ERP was becoming mainstream and office suites were covering more scope within the one big package.  More than fifteen years later, I don’t think anyone believes that developing small agile software is an experiment any longer, we even have a small name for it: the “app”.  In the consumer space we have become comfortable buying a number of apps to enable us to do the things we want our smartphones to do.  With the rise of the tablet, the apps have become the natural method by which we populate the device.  We use the tablet like a big smartphone rather than a small PC.

Increasingly, we are looking for our PCs to work in the same way with more online solutions blurring the line between desktop software and cloud-based services.  It seems inevitable that our first act when we pick-up a new computer in coming years will be to buy a whole series of small apps rather than one or two big home or small office solutions.  What’s more, we expect all of these apps to play well together and they largely do.  Thanks to information, synchronisation and format standards we can use the same information in many different apps and pick the tools that suit our personal preferences.

As has been the case of most of the recent waves of consumer technology, the enterprise follows closely behind.  PCs, the web, smartphones, tablets have all been positioned first as devices for the consumer but have been picked-up rapidly by corporations and government.  We are already starting to see the attraction of cloud-based services, not in the ability to buy infrastructure (the early sales push) but rather in the vast range of specialised solutions that can be rapidly deployed without needing to worry about where they fit in with the strategic software choices of the enterprise as a whole.

The role of these specialised solutions in organisations is gradually widening.  Starting from applications such as scheduling social events, organisations began then using these services for expenses, contracting and customer relationship management.  As the range of capabilities expand, the traditional enterprise software providers are not standing by and are increasingly providing compelling solution offerings of their own.

Far from being fragmented, this “small” approach to purchasing software is beginning to enable true enterprise-scale solutions.  Vendors, who are enabling apps to run across platforms, provide cloud-based deployment or simply deploy enterprise capabilities in manageable chunks, are also very aware of the need to adhere to standards.  The key for CIOs is not to avoid buying in this way, but rather to ensure that all of the players are following those standards and that information governance is central to business and technology strategy, not an afterthought.  With the right information capabilities in place, the power of the cloud can be realised.

The years 1990 to 2000, when Khan grew Borland to its greatest heights and then made his mark with Starfish, were a period of great change in the way we deployed technology across business and government.  Arguably, 2000 to 2010 did not see anywhere near the same amount of change.  The time seems right for a wave of change through this decade that will turn the approaches we take to deploying complex solutions on their head.

CIOs need to measure the right things

If you're a Chief Information Officer (CIO) there are three things that your organization expects of you: 1) keep everything running; 2) add new capabilities; and 3) do it all as cheaply as possible.  The metrics that CIOs typically use to measure these things include keeping a count of the number of outages, number of projects delivered and budget variances.  The problem with this approach is that it fails to take account of complexity.

When I talk with senior executives, regardless of their role, the conversation inevitably turns to the frustration that they feel about the cost and complexity of doing even seemingly simple things such as preparing a marketing campaign, adding a self-service capability or combining two services into one.  No matter which way you look at it, it costs more to add or change even simple things in organisations due to the increasing complexity that a generation of projects have left behind as their legacy.  It should come as no surprise that innovation seems to come from greenfield startups, many of which have been funded by established companies who's own legacy stymies experimentation and agility.

This doesn't have to be the case.  If a CIO accepts the assertion that complexity caused by the legacy of previous projects is the enemy of agility, then they should ask whether they are explicitly measuring the complexity that current and future projects are adding to the enterprise.  CIOs need to challenge themselves to engineer their business in such a way that it is both flexible and agile with minimal complexity compared to a startup.

The reason that I spend so much time writing about information rather than processes or business functions is that the modern enterprise is driven by information.  So much so, that metrics tracking the management and use of information are very effective predictors of issues with the development of new processes and obstacles to the delivery of new functionality.  There appear to be no accurate measures of the agility of enterprise technology that focus on just processes or functions without information but there are measures of information that safely ignore processes and functions knowing that well organized information assets enable new processes and functions to be created with ease.

The CIO who wants to ensure their organisation has the capability to easily implement new functions in the future should look to measure how much information the organization can handle without introducing disproportionate complexity.  The key is in structuring information assets in such a way as to ensure that complexity is compartmentalized within tightly controlled units with well understood boundaries and properly defined interfaces to other information assets.  These interfaces act as dampeners of complexity or turbulence, allowing for problems or changes to be constrained and their wider impact minimized.

Creating such siloes may seem to go against conventional wisdom of having an integrated atomic layer and enterprise approach to data.  Nothing could be further from the truth, it is simply ensuring that the largest possible quantity of information is made available to all stakeholders with the minimum possible complexity.

The actual measures themselves are described in my book, Information-Driven Business,  as the "small worlds data measure" for complexity and "information entropy" for the quantity.  Applying the measures is surprisingly easy, the question each CIO then needs to answer is how to describe these measures in a way that engages their business stakeholders.  If technology leaders are hoping to avoid difficult topics with their executive counterparts then this will be impossible, but if they are willing to share their inside knowledge on modern information technology then the "us and them" culture can start to be broken down.

The “four layer” model applied to unstructured content

In my book, Information-Driven Business, I introduce a four layer model for information.  You can also read more about this model in the MIKE2.0 article: Four Layers of Information.

As a reminder, the four layer model provides a way of describing information in every organisation.  The model explains how information is consumed (layer 1: metrics), navigated (layer 2: dimensional), held (layer 3: atomic) and created (layer 4: operational).  Using this model helps to organisation to understand where it is overly dependent on staff or customer knowledge to manage information at any of these layers (such as summarising to report, or slicing-up in spreadsheets to answer questions).

Some people have commented that the descriptions I use in the book, and are used in the MIKE2.0 article, are geared towards structured data.  To help readers understand how the model equally applies to both structured and unstructured data, the following definitions of each layer may help

Layer 1: Metrics
For information to be used for management decision making, it ultimately needs to be summarised into a score or metrics against which “good” or “bad” can be defined.  This is the same regardless of whether we are talking about structured data or summarising a collection of unstructured content.  The metric for documents could be as simple as a count (for example, the number of policies) or a combination of factors such as the number of processes covered by a particular type of policy.

Layer 2: Dimensional or Navigational
While formally described as the dimensional layer, it is perhaps better described as the way that the organisation can be navigated.  At this layer we are talking about structuring the content in way that we can find in a systematic way (via a taxonomy).  It is from here that metrics, such as a count of policies, can be derived.  It is also from here that we go to find content in its general form (“get me all procedures associated with disaster recovery”).  For instance, in this layer policies can be cross referenced against each other.

Layer 3: Normalised or Atomic
In the unstructured sense it is better to use the term “atomic” for this layer which contains the content in its original form reference by the event that created it rather than a business taxonomy.  This layer is often handled badly in organisations but can be as simple as recording the time, author and organisational hierarchy.  It can also be aligned to business processes.  For instance, in this layer, policies and procedures should be fully formed but only associated with the scope that they are covering.

Layer 4: Operational
The fourth layer is the front line and refers to the situation and technology context in which the content is created or updated.  Examples include: social media, documents on network drives and email within the inbox of the conversation participants.  For instance, in this layer, policies are created (maybe in many parts) but have no context.

Can we make the Information Revolution better for society?

It is easy to assume that access to massive amounts of information is good for society.  Perhaps we should also look at the role the move to an Information Economy is having on the reversal of generations of movement towards greater social equality.

The growth of the state between the early twentieth century and the 1970s brought with it higher taxes and a major a redistribution of wealth. In the UK the wealthiest 1% of the population saw their share of total wealth shrink from 70% in 1913 to 20% in 1980 (source: Deloitte Global Economic Outlook, 2nd quarter 2011).

What many people have not yet realised is that the trend towards greater equality has gone into reverse since the 1980s.  Also reported in the same Deloitte report, Credit Suisse estimates that today less than half of one percent of the world's adult population owns 36 percent of the world's private wealth.  The reasons in many countries for increasing inequality are complex but are significantly exacerbated by the shift to lower top rates of income tax around the world.

The reasons for this push to reduce the top rates are complex, but they aren't purely economic, they also relate to the ability of those who are paying the top rates to make their case in the political arena.

Does the move from an economy of production to one that is driven by information change the make-up of business leaders?  Has something changed about the makeup of the most financially successful members of society?

Globalisation and industrial change has reduced the returns to unskilled labour.  Knowledge based industries such as finance and technology have emerged as major employers and value creators in the economy.  Their demand for highly skilled workers have increased the payoff to employees with a university education. Cognitive skills are especially valuable in a knowledge economy.

Paying an increasing premium for well educated, articulate, informed and connected (in a information rather than a power sense) staff changes the dynamic of those in the top tier of remuneration in society.  When owners of factories, large farming establishments and transport businesses were in this position, they might have complained about the rate of tax that they paid, but they were no more equipped than society as a whole to influence change.

While it has always been true that education and access to information positioned citizens well for a good rate of pay, the correlation with remuneration is much stronger than it has ever been.  In effect, those who cannot navigate the information age and its resources are at a great disadvantage

The solutions to this inequality are many and complex, but the information management profession have an important role to play.  First, we need to recognise that access to complex information is the right of all within a society and these resources need to be structured in a way that are broadly accessible rather than obscured through technology.  Second, we need to simplify complex roles in organisations that require significant skill to link together disparate datasets from across the enterprise (opening-up information roles to a wider workforce).  Finally, we need to explain to politicians the changes in business and its impact on the wider economy.

In the 1960s, in response to the United Nations “Development Decade”, the then UN Secretary General, U Thant, said: "It is no longer resources that limit decisions.  It is the decision that makes the resources."  It was arguably becoming true in the 1960s.  It could not be more true in the twenty-first century.  Information management professionals can help enable those decisions to put more of the resources in the hands of as many people as possible.

Is Information Management an evolution or a revolution?

I was recently asked by ABC Radio National to explain the principles behind my book, Information-Driven Business.  The following is extracted from the program or you can listen to the full broadcast online.

I’ve spent more than twenty years looking at how having large quantities of complex information affects every part of our lives.  Whether it is your health and welfare, or the approval of your home loan, I cannot overstate how important the recent accumulation of vast quantities of complex data about each of us has been.  Just a few years ago, who would have imagined that a company like Google would have a photo of almost every house in major cities in Australia or that so many of us would share large amounts of personal information through Facebook?

I’ve also had a life-long fascination with science and mathematics.  I’ve watched the enormous development of ideas in computing and it has often occurred to me that we are particularly bad at learning from other, more mature fields – particularly science.  The last few decades of development of information technology has seen new generations of enthusiastic entrepreneurs develop their ideas as if nothing they did had ever been thought of before.

Online shopping sites might offer great new features, but they don’t really change the idea of a traditional store or a mail-order catalogue.  Banks may be offering us new forms of credit but the idea of a home loan hasn’t really been challenged.  In both cases, businesses have evolved an existing set of business processes without really challenging who holds what information and when they hold it.

To understand the opportunity that business, consumers and societies have today, we need to go right back to the industrial revolution.  The changes then triggered an exodus of people from agriculture to manufacturing, from rural to urban settings.  Today we are in the midst of an information revolution.  This revolution is triggering a move of many jobs across global borders and the removal of many unskilled roles from the workforce.

This revolution has also seen an enormous quantity of personal information move into private hands through social media, marketing databases and also more detailed credit checks.  Previously this would have just belonged to government, or if business held it they wouldn’t have been able to compile or analyse it as it would have been written on paper buried in filing cabinets.

If you watched the science fiction movie, Minority Report, in 2002 you might have wondered at the way Tom Cruise was able to sift through data with a wave of his hand and you were probably dazzled by the wall of the store that greeted him by name and knew what his last purchase was.  Both of these innovations aren’t the vision of a distant future, rather they are here now with products like the iPad which sweeps in the same way and customised messaging in stores based on our loyalty cards or even a connection with our mobile phone.

Modern business has evolved from the industrial revolution.  The problem we face today in navigating the information revolution is that the industrial revolution taught us to use the principles of processes.  Two centuries of business has slavishly adhered to the idea that commercial and government enterprises are nothing more than the aggregate output of thousands of individual business processes.  Because no-one alive today has experienced any other form of business interaction we can be forgiven for thinking that there is no other alternative.

But we should wonder whether it is the right approach.  By learning why we have a process-oriented approach to business, we can then question whether we have really thought deeply about it.  The trigger for my doubt is that very few other things that we experience in other fields are oriented around processes.

The telephone network is very efficient at joining two people together by analysing source and destination and finding the shortest path between the two.  Social networks are very efficient as evidenced by the small number of steps to required connect anyone with anyone else on the planet and it doesn’t seem to matter what culture or society norms are in place between the two people (just think “six degrees of separation”).

Traditional business, however, relies on processes and is really very inefficient.  Just ask anyone who has ever tried to change their utility bill details or arrange a new mortgage.

Most of science and mathematics does not lend itself well to this process paradigm.  Having said that, business borrows from the small number of such examples that we do have.  Think of terms like "an idea's half life" (borrowing from nuclear reactions to describe how new concepts need to be implemented quickly to have an impact) or “catalyst for change” (borrowing from chemistry to describe how certain actions in business have an additional and beneficial impact).  Hence, if the few examples we find already draw from the real world, then if there were more they would be likely to already appear as common business metaphors.

Of course, fields related to modern business do borrow from science.  The field of economics borrows from thermodynamics.  Modern fund managers are very familiar with using principles evolved from chaos mathematics which underpin predictive models used to support their investment in securities markets.

I argue though, that such ideas are limited to small aspects of business and by-and-large process-oriented organisations are not borrowing from science or any other field of human endeavour.  The information revolution provides the impetus to change.

Allow me to illustrate.  Consider a home loan that is written in a bank branch.  In years gone by, a paper application would have been provided to a supervisor who would have reviewed it when they had time.  If the amounts exceeded their approval threshold, they would have forwarded it upwards for further approval.  Today, this is all done electronically – but inevitably that electronic process mimics the paper one – we are continuing to use a paper process metaphor because it is what we know.  But an optimised business would have many eyes on the same application with the first available supervisor anywhere in the world being able to approve it if it met their desired criteria.

The result of the information revolution is a new paradigm.  The “information-driven business”, as opposed to the process-driven business.  This new form of enterprise is engineered around information without being tied to an individual process or activity.  Customer information doesn't really need to be defined by how it was collected as it usually is today.  When you provide your personal details through a call centre for an electricity utility company you shouldn’t need to repeat yourself a year later when you move again and use the internet to request a service at your new address.

Once business has been freed from its process straightjacket, we have the opportunity to create a much more dynamic organization that looks more organic than artificial.  Ideas (that is products or services) can be combined or divided at will and to achieve the best possible economic or social outcome.  In a world where processes are increasingly outsourced, and physical products are being manufactured en-mass by labour efficient countries, it is incredibly important that we value information more highly than any individual transaction or process that supports the transaction.  What is more important to a department store, the completion of the sale of an individual item or the knowledge of the customer that enables the store to service him or her for many years?

My book, Information-Driven Business, takes this concept to the logical conclusion and provides methods for estimating the quantity, usability and value of information that we interact with in all aspects of commercial and government business.  These techniques apply the principles of thermodynamics through entropy, mathematics through graph theory and physics through complexity theory.  I argue that the value of modern business is largely tied-up in its intangible information.  Consider what would happen to the value of any company if you reformatted every hard disk in the organisation.

Fortuitously, at the same time that we are reconsidering the role of information in business, many branches of science are beginning to see information not as a by-product of something physical but rather the important thing in its own right.  This should be no surprise when we consider quantum mechanics of the past eighty years where we have realised that the information we retrieve about an experiment means we have adjusted the result.  Increasingly information is not a window on our universe, rather it is our universe.

The comparison between physics and business is only valid because the organisations we have built today have become so complex that it is impossible to predict in advance how they will respond to any given event or change.  What we can do, though, is predict general behaviours by looking at what information relationships exist.

In my book I provide a technique for determining the information linkages within an organisation –that is how well connected information from one part of the organisation is to information in other parts of the enterprise.

As we get better at using all of the data and information, it has greater value and market forces have naturally encouraged more of these linkages.

This has continued a long-term trend to see business consolidate and continue to get larger. However something has now changed that we need to understand.  During the past decade information standards have begun to emerge and gain acceptance.  Perhaps the most important is the eXtensible Business Reporting Language, a data standard that is used by businesses and governments around the world – including in Australia.

With information standards we are now seeing businesses decide not to merge but rather form information alliances and to trade information in real-time to provide a customer with an integrated product.  Think, for instance, about travel products and the number of individual businesses that are typically now involved in a single transaction but all appearing under the one banner. These can include the airline’s flights, an alliance airline’s connecting flights, rental cars, hotel accommodation, travel insurance and airport valet parking.  This example might seem obvious, but it has far reaching implications in the segmentation of the value chain.  For the first time in a very long time, agility is likely to drive companies to get smaller without the balancing factor of scale being needed to take an integrated product to market.

The worth of each contributing business is in how it adds information value and how it enhances the product as a whole.  With such complex partnering of many organisations, there isn’t time for a waterfall business process to form.  There is time, if we’re not careful however, for a chaotic system to form, which by its nature will provide a result which the members of the joint venture cannot predict.

In the travel example, chaos could result from the combination of different accommodation and airline loyalty schemes participating in the same product with different rules.  Can I claim hotel points if I’ve paid by redeeming airline points?  Does a credit card provider, also providing points, get access to information about the whole transaction?  With these different combinations there might be different cost and margin implications which, in-turn, cause participants to add surcharges or provide further discounts.  Does each participant need to offer the best price at every point in time, or can they discount to different channels?  Even small changes in the rules of information exchange and associated pricing can completely change whether customers are better to go via the airline, hotel or bring their constituent parts together through individual travel websites – reducing the integrated value that businesses participating in the alliance are able to provide.

With such complex relationships, the participants can do well to learn from the synergies of a biological ecosystem rather than try to predict every process pathway that a customer might choose to use.  In some cases organisms within an ecosystem can be in competition, offer each other synergies and be “food” for one another all at the same time.  Business of the twenty-first century echoes these same biological relationships.

The information revolution provides us a unique opportunity to re-invent business.  The techniques we will use to develop new approaches to everything from supermarkets to airlines will borrow less from business processes of the twentieth century and far more from physics, chemistry, biology and mathematics.  The people who are going to be best placed to invent this new world of business are the very people who have often felt most alienated from it – science graduates.