In addition to standard risk management processes such as credit, foreign exchange and market risk, CFOs are increasingly being asked to report on ways to minimize risk in a wide variety of other areas including- new product investments, acquisitions, HR, brands, market share, customer acceptance and satisfaction and product liability- in fact all operational and strategic processes across the enterprise. This is causing a rethink on the systems required to monitor such broad-based risks.
A string of corporate disasters such as Enron, Worldcom, Ford and GM has transformed the status of risk management to a central role. Up until five years ago risk management was handled by actuaries and internal auditors. Now the discipline incorporates high-level corporate risk officers reporting directly either to the CEO or a board level risk management committee.
This trend is encapsulated by the emerging discipline of ERM- ‘enterprise risk management’- a set of broad-based management processes that integrates all risk areas from- insurance financial derivatives, foreign exchange and trade to credit, market, political, brand and image risks, to corporate governance, regulatory and legal issues and now escalating environmental impacts.
ERM aims to achieve systematic reduction in all risk outcomes facing enterprises today, but with the goal of creating balance between realizing opportunities and minimizing adverse impacts.
The quality of an organisation’s information technology architecture plays a pivotal role in this area both by both processing and integrating the data needed to manage risk and by ensuring that the company’s risk policy and planning is rigorously implemented.
However to date, the challenges in managing risk on an enterprise wide basis have proved daunting. According to a recent Deloitte Global Risk Management Survey, less than a quarter of businesses surveyed were able to integrate risk across any of the major functional dimensions- risk type, business unit or geographical area.
There is also the tendency for financial and manufacturing institutions to focus primarily on areas of traditional risk where data analysis and statistical techniques have been developed. This is a natural response, but in an environment where new and potentially lethal risks can emerge suddenly triggered for example by major catastrophes such as bird flu or a surge in the oil price impacting large vehicle sales, as in the case of Ford, it is important to look at the bigger picture and seek to anticipate and avoid those submerged risks that can abruptly sink even the largest enterprise.
Future Trends
Managing such potential risks in the future enterprise environment will require new architectures and information system safeguards to constantly and automatically monitor the quality of decision outcomes; in other words implementing a sophisticated Deep Decision Risk Audit Framework.
Even when when risk and audit plans are implemented, the associated critical decision processes that need to be activated, are either not integrated into the control architecture or the outcomes are ignored because of lack of substantive risk cost estimates.
Risk outcomes are inevitably associated with all decision-making processes and the quality of those decisions largely determine the survival and productivity of the enterprise. A deeper decision assessment process ensures that the risks associated with critical decisions, including those governing potentially catastrophic outcomes, are better anticipated, highlighted and quantified. This allows intervention before, not after critical thresholds are breached and before serious and chaotic escalation occurs as with the recent global financial meltdown.
Wednesday, June 25, 2008
Tuesday, June 24, 2008
Smart Business Networks
Recent research in network science triggered by the boom in social networks on the internet, has made a significant contribution to a more profound understanding of networked behaviour in business ecosystems.
Networked ‘swarm’ behaviour for example can demonstrate an increase in collective intelligence. Such collective behaviour in complex self-organising systems exhibits impressive ‘smarter’ problem solving capability as well as greater agility.
By linking together in strategic and operational networks, enterprises are therefore able to gain synergy and achieve superior operational performance than was previously achievable using more rigid organisational models. By combining skills and resources as part of a larger networked entity, they have the potential to become much more agile and flexible, reacting to and taking advantage of emerging opportunities.
For example, In less than 10 years Amazon has moved from book retailing to become the world’s leading e-tailer, offering a complete business platform to support a networked model for traditional retailers including- facilitating searching by buyers and sellers, helping set pricing, managing logistical processes, settling payments, arranging fund transfers and authenticating the quality of goods and the credibility of buyers and sellers.
Thousands of retailers join the Amazon network every month to benefit from Amazon's accumulated experience and information relating to retail goods, buyers and sellers. Such new platforms demonstrate strong network characteristics- for example, the more users in the network, the more useful it becomes for all players and the more difficult it becomes for members to switch to another network.
Organisations are increasingly moving from today’s relatively slow and hierarchical model of a self-contained business based on a small number of closely coupled partners, to an open digital platform where business is conducted across rapidly created networks. This open model allows opportunistic linking to a wider range of global partners, connecting to different processes and information systems. The disadvantage of not moving to such loosely-coupled networks includes the inability to provide support for more complex, bundled and rapidly delivered products and services in a fast changing and demanding business environment
Future Trends
The key characteristics of the smart business network of the future will be its ability to rapidly react by picking, plugging and playing business processes and partners, reconfiguring rapidly to meet specific objectives.
In addition such networks will need to quickly and opportunistically connect and disconnect relationships, at the same time establishing business rules and operational logic for participating members on the basis of risk and reward. This ‘on the fly’ capacity to reconfigure new decision rules governing decision and operational processes, will be a crucial dynamic governing the success of tomorrow’s future enterprise.
Future enterprise IT managers must also learn to span the architectural boundaries between their own networked organisation and the increasingly complex social, financial and economic networked environments in which their organisations are embedded and must operate.
Networked ‘swarm’ behaviour for example can demonstrate an increase in collective intelligence. Such collective behaviour in complex self-organising systems exhibits impressive ‘smarter’ problem solving capability as well as greater agility.
By linking together in strategic and operational networks, enterprises are therefore able to gain synergy and achieve superior operational performance than was previously achievable using more rigid organisational models. By combining skills and resources as part of a larger networked entity, they have the potential to become much more agile and flexible, reacting to and taking advantage of emerging opportunities.
For example, In less than 10 years Amazon has moved from book retailing to become the world’s leading e-tailer, offering a complete business platform to support a networked model for traditional retailers including- facilitating searching by buyers and sellers, helping set pricing, managing logistical processes, settling payments, arranging fund transfers and authenticating the quality of goods and the credibility of buyers and sellers.
Thousands of retailers join the Amazon network every month to benefit from Amazon's accumulated experience and information relating to retail goods, buyers and sellers. Such new platforms demonstrate strong network characteristics- for example, the more users in the network, the more useful it becomes for all players and the more difficult it becomes for members to switch to another network.
Organisations are increasingly moving from today’s relatively slow and hierarchical model of a self-contained business based on a small number of closely coupled partners, to an open digital platform where business is conducted across rapidly created networks. This open model allows opportunistic linking to a wider range of global partners, connecting to different processes and information systems. The disadvantage of not moving to such loosely-coupled networks includes the inability to provide support for more complex, bundled and rapidly delivered products and services in a fast changing and demanding business environment
Future Trends
The key characteristics of the smart business network of the future will be its ability to rapidly react by picking, plugging and playing business processes and partners, reconfiguring rapidly to meet specific objectives.
In addition such networks will need to quickly and opportunistically connect and disconnect relationships, at the same time establishing business rules and operational logic for participating members on the basis of risk and reward. This ‘on the fly’ capacity to reconfigure new decision rules governing decision and operational processes, will be a crucial dynamic governing the success of tomorrow’s future enterprise.
Future enterprise IT managers must also learn to span the architectural boundaries between their own networked organisation and the increasingly complex social, financial and economic networked environments in which their organisations are embedded and must operate.
Thursday, June 12, 2008
Decision Re-engineering
Decision Re-engineering
The emerging Decision Engineering Architecture of the 21st century represents a major shift in managing the operations of the future enterprise. By optimising the decision networks of an organisation, greatly improved levels of efficiency, adaptivity and quality of decision-making can be achieved beyond current
Process and service oriented architectures. Combined with the new organisational model of intelligent and flexible knowledge processing, decision-engineering techniques are well positioned to accelerate major gains in the performance and productivity of the future enterprise.
Scientists are striving to more fully understand the ways in which network components interact with one another to influence complex processes. Thus attention has turned to the analysis of networks that operate at many levels.
The network model is well established in the social, biological and environmental sciences providing a much more realistic and powerful model of real world interactions.
This evolutionary model is now beginning to permeate the business and technology environments offering the next major step in their evolution.
The core of this framework in relation to the future adaptable enterprise is the capacity to dynamically route information and intelligence resources to critical decision nodes in the enterprise.
The most basic feature of any network is its architecture or topology, which places boundaries on how it acts and how it might have been formed. Network models are underpinned by Graph Theory, which defines the rules of network topology.
Future Trends
The classes of networks that exhibit different global features will be examined in future updates, to determine the architecture that will best fit the evolution of the adaptive enterprise together with techniques available within the emerging class of Decision Engineering Methodologies- to map, optimise and apply decision networks within an enterprise environment.
Applied to the new enterprise model of intelligent and flexible knowledge processing, decision engineering techniques are well positioned to accelerate major gains in the performance and productivity of the future enterprise
Re-engineering the decision processes of an organisation will be essential to the future unlocking of potential value and reducing operational and planning risk.
The emerging Decision Engineering Architecture of the 21st century represents a major shift in managing the operations of the future enterprise. By optimising the decision networks of an organisation, greatly improved levels of efficiency, adaptivity and quality of decision-making can be achieved beyond current
Process and service oriented architectures. Combined with the new organisational model of intelligent and flexible knowledge processing, decision-engineering techniques are well positioned to accelerate major gains in the performance and productivity of the future enterprise.
Scientists are striving to more fully understand the ways in which network components interact with one another to influence complex processes. Thus attention has turned to the analysis of networks that operate at many levels.
The network model is well established in the social, biological and environmental sciences providing a much more realistic and powerful model of real world interactions.
This evolutionary model is now beginning to permeate the business and technology environments offering the next major step in their evolution.
The core of this framework in relation to the future adaptable enterprise is the capacity to dynamically route information and intelligence resources to critical decision nodes in the enterprise.
The most basic feature of any network is its architecture or topology, which places boundaries on how it acts and how it might have been formed. Network models are underpinned by Graph Theory, which defines the rules of network topology.
Future Trends
The classes of networks that exhibit different global features will be examined in future updates, to determine the architecture that will best fit the evolution of the adaptive enterprise together with techniques available within the emerging class of Decision Engineering Methodologies- to map, optimise and apply decision networks within an enterprise environment.
Applied to the new enterprise model of intelligent and flexible knowledge processing, decision engineering techniques are well positioned to accelerate major gains in the performance and productivity of the future enterprise
Re-engineering the decision processes of an organisation will be essential to the future unlocking of potential value and reducing operational and planning risk.
The Virtual Metaverse
The Web is now beginning to host an immersive 3D sensory environment that combines elements of social and virtual worlds such as Second Life with increasingly dense geographical mapping applications using Google Earth and Microsoft's Virtual Earth.
Representations of the earth’s natural and urban environments can create increasingly detailed mirror worlds or models of reality. Combined with virtual worlds, they represent an emerging Metaverse of realised virtual earths, projected to have an increasing impact on business and society.
Such meshing of the virtual and real is already standard within Second Life, using repesentations of the social realities with which humans can interact- for example- a virtual Planetarium, a walk-in weather map and an International Spaceflight Museum where visitors can fly alongside life-size NASA rockets- all driven by real world data streaming technologies.
Users can routinely create avatars that hover and zoom over a world with computer generated human clones and scenery, social facilities, urban infrastructure and services, including shopping with real convertible currency.
Such virtual earths are also becoming increasingly common in consumer computer games utilising the enormous power of today's inexpensive graphic processors.
Future Trends
This increasingly immersive Virtual Metaverse will soon be accessible in 3D hologram form and on mobile media and will also be capable of integrating with augmented reality- a third stream of enhanced reality.
Augmented reality is created by integrating or mixing real objects and natural spaces with layers of associated computer-generated images and designs; so that in the future real, virtual and augmented scenarios can be seamlessly combined.
An architect for example could visualise the impact of a virtual building overlaid on a real landscape or perform a virtual tour around a planned or existing building with a client. Auto designers will see how small changes would affect an existing car body design or surgeons the effects of cosmetic surgery on a real patient. At a simpler level, coffee or pizza shop fronts captured in the Google Street application are already being linked to videos and images of the shop's internal experience as well as Google maps.
Such integrated real, virtual and mirror worlds will offer a major creative challenge for the future enterprise- providing the opportunity to amplify its tactical and strategic competitive reach, better manage global resources through logistical virtual simulations and explore novel and radical marketing scenarios. At this point in time business has been slow to realise this potential as marketing and planning departments play catchup with the more mature consumer virtual experience.
Eventually there will be many different second earths in our future- within an expanding virtual Metaverse. Businesses are already utilising virtual worlds for simulation and promotional purposes and in the future will develop and control their own cyber worlds. Over time these will overlap, merge, spawn and evolve into a seamless surreal metaverse with unlimited potential for both the enterprise and humanity.
Representations of the earth’s natural and urban environments can create increasingly detailed mirror worlds or models of reality. Combined with virtual worlds, they represent an emerging Metaverse of realised virtual earths, projected to have an increasing impact on business and society.
Such meshing of the virtual and real is already standard within Second Life, using repesentations of the social realities with which humans can interact- for example- a virtual Planetarium, a walk-in weather map and an International Spaceflight Museum where visitors can fly alongside life-size NASA rockets- all driven by real world data streaming technologies.
Users can routinely create avatars that hover and zoom over a world with computer generated human clones and scenery, social facilities, urban infrastructure and services, including shopping with real convertible currency.
Such virtual earths are also becoming increasingly common in consumer computer games utilising the enormous power of today's inexpensive graphic processors.
Future Trends
This increasingly immersive Virtual Metaverse will soon be accessible in 3D hologram form and on mobile media and will also be capable of integrating with augmented reality- a third stream of enhanced reality.
Augmented reality is created by integrating or mixing real objects and natural spaces with layers of associated computer-generated images and designs; so that in the future real, virtual and augmented scenarios can be seamlessly combined.
An architect for example could visualise the impact of a virtual building overlaid on a real landscape or perform a virtual tour around a planned or existing building with a client. Auto designers will see how small changes would affect an existing car body design or surgeons the effects of cosmetic surgery on a real patient. At a simpler level, coffee or pizza shop fronts captured in the Google Street application are already being linked to videos and images of the shop's internal experience as well as Google maps.
Such integrated real, virtual and mirror worlds will offer a major creative challenge for the future enterprise- providing the opportunity to amplify its tactical and strategic competitive reach, better manage global resources through logistical virtual simulations and explore novel and radical marketing scenarios. At this point in time business has been slow to realise this potential as marketing and planning departments play catchup with the more mature consumer virtual experience.
Eventually there will be many different second earths in our future- within an expanding virtual Metaverse. Businesses are already utilising virtual worlds for simulation and promotional purposes and in the future will develop and control their own cyber worlds. Over time these will overlap, merge, spawn and evolve into a seamless surreal metaverse with unlimited potential for both the enterprise and humanity.
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