A POINT OF VIEW ON BUSINESS INTELLIGENCE AND SERVICE ... · A POINT OF VIEW ON BUSINESS INTELLIGENCE & SERVICE ARCHITECTURES A White Paper on real time event driven Business Intelligence

A POINT OF VIEW ON BUSINESS INTELLIGENCE AND

SERVICE ARCHITECTURES A WHITE PAPER ON REAL TIME EVENT DRIVEN

BUSINESS INTELLIGENCE

Origin/Author : ANDY MULHOLLAND Approved by : JON GIBBS Date Approved : 1.0

Capgemini UK plc No 1 Forge End Woking Surrey GU21 6DB Phone +44 (0)1483 764 764 Fax +44 (0)1483 786 104

Reference: A PoV on Business Intelligence with Service Architectures Version 1.o – July 2004

A POINT OF VIEW ON BUSINESS INTELLIGENCE & SERVICE ARCHITECTURES

A White Paper on real time event driven Business Intelligence

Contents

1. Context of this White Paper 2

2. Disclaimer 4

3. Executive Summary – defining and benefiting from BI 5

4. The growing requirement for BI – Knowledge has no value till it is used 7

5. The current driving issues – Why is BI a ‘hot’ issue now? 9

6. BI Today – Current ways to implement compared 12 6.1 BI from the Data Warehouse 12 6.2 Right Time Reporting from a Production Database 12 6.3 Right Time Reporting from an Operational Data Store 13 6.4 Summary 13

7. Enterprise Business Intelligence – Using Client Services and SOA 15 7.1 A Use Case Example 18

8. Tactical, Strategic and Enterprise BI – How to deliver as ‘Services’ 20

9. People, Collaboration, and BI – the missing link in BI projects 23

APPENDICES 24 Appendix 1 – Real Time IT from Client Services using SOA 25 Appendix 2 – An overview on Agent technology 28 Appendix 3 – A Glossary of Mainstream Major Standards 31 Document Control 34

THIS DOCUMENT CONTAINS 35 PAGES INCLUDING TITLE PAGE

Reference: A PoV on Business Intelligence and Service Architectures Version 1.0 - July 2004

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1. Context of this White Paper

This white paper is part of a series from Capgemini that identify the individual elements of technologies that either will, or have already become, commercially feasible, and then provides a definition of the overall impact that their combination implies for both Business and MIS IT systems. The terms ‘Collaborative Business’, ‘Adaptive IT’ and ‘Adaptive Enterprise’ refer to Capgemini Points of View on behaviour, whilst the terms ‘Adaptive Architecture’ and ‘Collaborative Architecture’ refer to a detailed method of using, and integrating technology to build the capabilities. The white papers may be major, i.e. setting out a point of view about the overall development of technology for MIS IT systems, or specialised, examine in detail a particular technology element, such as designing and using Architecture. It is perhaps desirable to have some understanding of the background that the three major white papers have laid out in terms of the capabilities that technology will provide. The work is sequential with each building on the one before to outline a further change in capabilities, with identifiable business benefits, that has in time become commercially feasible and desirable. Those who have used Capgemini work in this area have been able to benefit from a consistent sense of strategic direction built by tactical deployments offering individual benefit cases. In addition this approach builds a growing set of capabilities that support lower cost flexible business support. This work first produced the term ‘adaptive’, which together with the term ‘agile’ as since become a standard industry wide term of reference for the capabilities, products and methods. A summary of the three major white papers is as follows;

1. AA1, (Adaptive Architecture1), released in early 1999, developed the concept of the three layer, sometimes referred to as ‘N’ layer, architectural model as a replacement for the then ubiquitous two layer client server model. The term ‘Adaptive IT’ was used to denote the ability for regular and frequent change in the manner that IT capability was delivered, moving beyond the application centric two layer client server monolithic model to a process centric three layer flexible architectural model. Five years later in 2004 this has become the industry standard, with the term ‘adaptive’, referring to behaviour, or ‘agile’, referring to the capability, being used by all major technology vendors. The ‘commercialisation’ of the concepts of Adaptive Architecture 1 range from individual packaging of technology elements such as the ‘application server’, to the launching of compliant architectural frameworks from major vendors such as the HP ‘adaptive infrastructure’.

2. AA2, (Adaptive Architecture2), released in early 2001, built upon the use of AA1 as an internal to

the enterprise model for delivering predetermined processes, to add the external to enterprise concept of ‘services’. The notion of ecosystem based commerce for effective market interaction precludes the concept of any ‘proprietary’ architecture as this suggests one technology vendor would need to be selected and adopted by all members of the ecosystem market, unlikely and impractical for many reasons. The term ‘Services Orientated Architecture’ is now used to denote an environment where interaction and combination takes place around agreed definitions of the interchange necessary. This implies a ‘loose coupled’ architecture for ‘any to any’ service interaction as opposed to traditional system integration ‘tight coupled’ principles, as used in AA1.

‘Web Services’ are now emerging rapidly, building on the concepts identified in AA2. More importantly perhaps is the business understanding of the way that pervasive IT can be used to support a new generation of shared technology interaction, or ‘collaboration’. This movement is led by the biggest and most successful players in each vertical market coming together to agree common working structures for interaction. Starting with data using XML schemas to ensure files interchanged can be read, but now rapidly moving to develop standardised business language, and therefore processes, for common, undifferentiated ecosystem activities such as invoicing and payments, as in ‘ebXML’ open standard. This has tremendous implications for the speed of adoption, but also for the internal enterprise and its own processes, together with the supporting IT.


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3. CA1, (Collaboration Architecture1), released in March 2004, moves beyond Web Services as a

single technology aspect, and into a total technology refresh. This will be as fundamental to changing the role of technology in respect of the way that Business is organised as PC-Networking was to changing internal organisational structures in the early 90s. It also considers the implications of a wholly new phenomena, that of a combination of external business and IT standards not just affecting, but driving, individual enterprises internal standards. Taken together this has the possibility to link the concept of a business service, the real world of a business activity, and the provision of IT technology by it defining the service as well. Collaboration Architecture 1 is the Capgemini conceptual architecture to address this providing the capability for the ‘Collaborative Business Experience’.

This white paper explores what Business Intelligence is today inside enterprises which are still largely defined by Applications for historical recording of transactional data, and what it can be, indeed will need to be, when used with Service Orientated Architectures. The ability to reconcile ‘events’ and orchestrate ‘responses’ will initially be internal, but as business moves to grasp the significant, hither too unrealised, advantages to be gained by external ‘intra-enterprise’ interactions this will soon change. The goal will be to identify any relevant events, internal or external, and then to ‘optimise’ the business response through ‘collaboration’ with other market players. This white paper expresses a Point of View as to how this may be achieved in through the development of new forms of ‘Business Intelligence’. A person, operating alone can make decisions in response to events in isolation, choosing to acknowledge only those aspects that affect only themselves, but in fact few things can be achieved in this mode. The interaction with, and assistance of, others is a vital part of life. Knowingly, or unknowingly, we all work with others to achieve whatever we need, by transactions that are based on ‘win-win’, where both, or all parties benefit, these are more normally successful than selfish ‘win-lose’ transactions. ‘Collaboration’ is the name that is used to denote this ability and it depends above all on the ability to understand each others respective positions and needs, as well as being able to communicate and make decisions in a mutually acceptable time. As an example Capgemini defines its relationship with its clients as ‘The Business Collaborative Experience’, and believes that the client’s goals are best reached by true teamwork between its own staff and Capgemini staff. Surely this is an obvious creed of many years standing? It is, but the ability to actually achieve this is a mixture of the desire to behave differently as well as the capability to actually do so. This later area has been changing as the technologies to allow the sharing of information in a secure and selective manner; the ability to build different forms of process rapidly to suit work teams; as well as to connect to existing structures have all improved. Extend the principle to an entire market ecosystem as suppliers and purchasers have the capability to work together achieving win-win deals on a continuous trading basis rather than on a deal by deal basis, and, the market and way of doing business becomes transformed. In essence this is the principle behind e-Bay, including a collaboration trust model where other members of the market ecosystem advise on their experience of trading with any partner. e-Bay represents an entire collaborative trading environment comprising of many different markets sectors, and continues to expand rapidly as more and more users become convinced of the advantages of doing business this way. But, e-Bay also relies on the knowledge of its users to determine what they want to buy, and if the price being offered is good or bad. For collaboration to work then knowledge is essential, and in order to make the optimal transaction at the right time, Business Intelligence is a crucial winning factor.

To be able to ‘read and respond’ to ‘events’ in the right time frame with an ‘optimal’ set of actions requires the ability to be able to be ‘Adaptive’ in processes, ‘Collaborative’ in relationships and above all

to be able to use ‘Business Intelligence’ to determine when and what to react to. This white paper seeks to add the ‘Business Intelligence’ capabilities to the previous work of Capgemini in the areas of defining technology change around the principles of ‘Adaptive’ and ‘Collaborative’.


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2. Disclaimer

All advice given and statements and recommendations made in this document are: 1) Provided in good faith on the basis of information provided by third parties and/or otherwise generally available or known to Capgemini at the time of writing; and 2) Made strictly on the basis that in no circumstances shall they constitute or deemed to constitute a warranty by Capgemini as to their accuracy or completeness. Capgemini shall not be liable for any loss, expense, damage or claim arising out of, or in connection with, the making of them in this document or for any omission from them.” The information contained within this document is and shall remain the property of Capgemini UK plc. This White Paper is supplied in strict confidence and must not be reproduced in whole or in part, used in tendering or for manufacturing purposes or given or communicated to any third party without the prior consent of Capgemini UK plc.

© Capgemini plc 2004


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3. Executive Summary – defining and benefiting from BI

Business Intelligence, or BI, which has been a hot topic recently though it is not so easy to define what is meant by the term. Often it has been defined by the choice of a specialist product from one of the many small vendors who describe themselves as being in this market. Now Oracle, SAP and Siebel have all stepped forward offering ‘integrated’ Business Intelligence within their own product suites. Microsoft as an example describes Business Intelligence as being a key part of collaboration; industry analysts say it is an essential part of many market requirements to solve common issues ranging from Business Performance Improvement, or BPI, to Sarbanes Oxley, as well as specific vertical requirements, i.e. the financial sector for Basel II. There are several drivers as to why Business Intelligence is needed, these include; to handle the increasing amounts of data from an increasing range of sources, this also includes new technologies such as RF-ID; the shrinking time between creating data and the need to use the data, the ‘read and respond’ issue; the need to meet legislative requirements such as Sarbanes Oxley; and finally the simple need when sharing resources between collaboration partners to be able to take advantage of more opportunities, thus being able to ‘optimise’ decisions by using available data in near real time, some times referred to as ‘right time’. These collectively add up to a need to make BI analytics a part of both existing operational processes through integration with the core enterprise transaction systems, as well as a support for event driven Real Time computing. Some examples of key drivers are; • Corporate Accountability in various industry sectors such as Health care HIPPA, or Sarbanes-Oxley in

the USA, and equivalents elsewhere, driving a wave of ‘compliance BI’ solutions. • Customer Relationship Management updating to real time actionable customer data to prompt

individual dialogue thereby optimising each engagement individually both on the customer, and the supplier sides.

• Business Activity Monitoring, BAM, as enterprises become increasing driven by short term reporting of operational results, and need to be able to ‘manage’ that is in more places in a more decisive manner.

• Mobility devices, including RFID, producing an unmanageable avalanche of data that must be sifted into immediate optimisable opportunities that, if answered, will benefit the management of all aspects of stock, from logistics to merchandising, backwards down the entire supply chain management system.

• Data and Storage Management, both as a cost and, as an availability issue, through reworking data warehouses, or data marts, into lower cost, higher impact, data on demand capabilities.

Gartner talks about BAM, Business Activity Monitoring, being the big payoff, stating that this is a mixture between BI analysis of operational data kicking off the notification of an issue, linked to Collaboration tools in order to promote the ‘managing’ of a response from those who have the authority to make decisions. Looking specifically at Financial Services and the legal compliance regulations such as Basel II, or the Supply Chain Market linked to Real-time Enterprise Manufacturing Systems the value of doing this is clear. However there can be no meaningful Collaboration without shared meaningful data, and the challenge of creating this in a shortened time frame, from a wider pool of disparate data, as and when needed, drives Business Intelligence to be thought of in a new way. On one hand as less specialised and better integrated to existing processes, and on the other, able to spot the significant, but hidden opportunity. All of this is part of an industry wide redefinition of the role of Business Intelligence in providing decision support to Business Collaboration in Real-Time. The new role of Business Intelligence as being both the input of data from events that are currently happening, and the basis, using past experience for guidance, challenges established principles. However, the what, when and where of data creation and use varies significantly in different areas of an Enterprise, something that is now becoming more clear as the role of the ‘front office’ versus the ‘back office’ has become established over the last few years. A new enterprise model is needed to establish what, where and how, these things fit together. It should indicate the differences in the role data plays in different areas of the business as much as the way to move


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from data to response, it will need to determine the time frames of business processes, and will not look like an IT architecture map in terms of detailed integration architecture, but more a frame of reference for the type of approach needed. The following diagram has been developed to help with this; the terms AA1 and AA2 refer to the types of IT architecture to use in the different areas being based on Capgemini Adaptive Architecture versions. The important definitions are at the bottom and refer to the characteristics of ‘services’ in each zone;

Applications, ERP & EAI Processes, Services & EAI Events, Service Architect.

AA1 AA2

Internal Use & Managmt. Shared Use with Control Free Access & No Control

Cost & Stability Optimised Value & Agility Investment Effectiveness by Adapting

Captured Historical Data Predictive Knowledge Info. Real Business Intelligence

System Integration. Process Definition Event Context

BackOffice

FrontOffice

MarketEcosystem


AA1 AA2





BackOffice

FrontOffice

MarketEcosystem

Established data based on recorded transactions is on the left, (typically ERP and applications built over many years). To the right is event driven information from the market ecosystem, (the new sources of information from outside the enterprise), and in the middle the two are brought together in order to make business decisions and responses via processes. What should be striking about this framework is the extent to which Business Intelligence must come to address externalised data, as opposed to current BI being focussed on internal data. Most dramatic changes in business today are around using the Internet to be able to communicate and interact with a wide range of market players, both to buy and sell, in a faster time frame. ‘Online’ interaction, being able to communicate in a variety of ways, and at various levels of sophistication, from e mail to a full ebXML, electronic business extensible mark-up language, based process suite, (the so called ‘book to bill’ set of eight common processes), is developing rapidly. Whilst initially some of these interactions will be between a predetermined set of partners soon this will expand to an ‘any to any’ interaction occurring around an ‘event’. An event could be anything from the need to buy from, to a logistics problem, to a sales query, all require a rapid decision in the context of the event, and most probably a series of reiterative communications to ‘negotiate’ the final answer. Businesses need to learn how to collaborate with, and to manage the form of the collaborations with, a wide variety of partners in order to be successful. Business Collaboration is about being able to pool resources for common good, but what resources, the definition of ‘good’ individually, and then collectively, needs the assistance of Business Intelligence, as the provider of real-time, or right-time, information to be able to make the optimal decision to each event.

The ability to make, and then to process, the right decision at the right time in collaboration with the right partner(s) is the definition of the successful use of BI


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4. The growing requirement for BI – Knowledge has no value till it is used

The wish to be able to understand situations is a normal human response to having to make decisions when confronted with events. The challenge is to have the right information at the right time to be able to make the right decision. The inability to do this is not necessarily a factor of not having enough data, generally one of the issues is having too much data to be able to see exactly what is needed. Businesses have spent years and a great deal of money in capturing data, in the hope of turning this into ‘Knowledge’, and perceive the problem as being their inability to make use of all of this data. The phrase ‘Knowledge has no value till it is used’ expresses their frustration in trying to make valuable use of this asset. Actually, an older phrase from the last century might be more accurate, ‘shutting the stable door after the horse has bolted’, expresses the frustration of knowing the answer after the event, when it is of no use. Business Intelligence serves to provide the ability to link together these two desires; the information on which to act; and the action itself, to ensure an optimised outcome. Currently this is not achieved, or achievable, as a cohesive process. There are a wide variety of solutions to individual aspects of this challenge to the extent that the term Business Intelligence today lacks any real definition. This white paper seeks to try to determine exactly what is the current state of the market for Business Intelligence, what are the current approaches, how to develop from these tactical solutions the desired cohesive proactive, or at least interactive, capability. It is intended to help those making choices today, to understand the difference between the approaches, but also to understand how, and why, the overall approach is likely to change in association with the introduction of external Web Services to complement the move to internal processes. Tactical benefits in the short term, with increasing strategic gains in the long term. The ‘front office’ with its Adaptive IT architecture built around Application Servers introduces processes, and is different to the ‘back office’, which is built around large scale functions captured through complex applications that produce copious amounts of data. It’s not only a technology difference either; it’s a difference in the functional role in the Business too. Today, neither IT, nor Business, stops at the boundary of the enterprise so there is a further set of characteristics, generally called the “Market Ecosystem”. The diagram below appeared full size in the executive summary setting out the fundamental roles of each of the organisational areas. The role of applications has been to provide the recording of transactions in the form

of relevant data within a database. As this is entirely within the enterprise, and for its own use, this is now known as the ‘back office’. Originally the data was recorded within the application, over time this often migrated to being held in a central and shared database for access by multiple applications. Due to the overall size and complexity of an enterprise there is usually more than one database, the size and type may vary from a full size data warehouse to series of smaller and more specialised data marts. It is a challenge to manage this

proliferation of records and updates to ensure one up to date version of the ‘truth’ is used by all.






BackOffice

FrontOffice

MarketEcosystem

Internal Standards External StandardsService Orientated Architecture






BackOffice

FrontOffice

MarketEcosystem

Internal Standards External StandardsService Orientated Architecture

The data coming from the ‘market ecosystem’ is very different in nature as it is generally not the result of a back office application recording transactions in its own customised way. This data is more in the form of a protocol with the structure clearly laid out to enable it to be read and interpreted by anyone, or any machine, that needs to. It is here that eXtensible Mark-up Language, XML and associated protocols such as Simple Object Access Protocol, SOAP, and Web Services Description Language, WSDL, have changed the rules.


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Being able to understand data originating outside the enterprise that has some degree of immediacy in addition to having access to historical data from within the enterprise creates real Business Intelligence, as opposed to Data Mining, which is more concerned with the examination of internally held data. Information has no value unless it can be acted upon, and this is the role of the ‘Front Office’, a term that really started to emerge with Customer Relationship Management, CRM, and Supplier Relationship Management, SCM. All of these topics are mostly, if not solely, the result of the technology shift that the Internet and the World Wide Web has brought. The Internet effectively ensures that anyone, or anything, is networked, and therefore connected through a set of open and standardised protocols. The World Wide Web provided both technologies, in the form of the Browser and Web Server, together with associated standards to ensure that content access and display was universally enabled, but more importantly it changed the thinking about the use of IT. The impact of seeing the benefits of standardisation as opposed to customisation for the use of IT, together with the realisation of the benefits of building ‘Services’ using the same concept of simple standardised defined interfaces that hide the complexity of the process within a ‘Service Orientated Architecture’, has changed the nature of IT. It has, and will continue, to change the nature of business too. This technology shift generically known as ‘Client Services’ (as opposed to ‘Client Server’), has changed the role and the abilities of Business Intelligence, even perhaps the importance of Business Intelligence. Why? There is also the capability to provide ‘responses’ as well as the capability to be able to ‘read’ in the ‘Front Office’. The shift towards building around ‘Processes’ to tie together the flow of data into the Back Office applications in a lower cost more flexible manner than using yet another application and expensive integration is well established. The Capgemini view of ‘Adaptive IT’, the concept of managing the provision of ‘services’ has become an accepted fact, and ‘Adaptive Architecture 1’ the use of a three layer architecture built around an Application Server to separate the management of people, processes and applications is now the norm. (Adaptive Architecture 2, is a conceptual architectural definition of Web Services for external use). It is therefore possible to use the data of both the market place event, and the enterprise records, with market facing processes to be able to both ‘Read and Respond’ internally, and increasingly externally as well. This

diagram takes the concept of the previous diagram of the three circles and redefines it using the technologies identified. The market ecosystem on the right is the provider of common standardised data much of which will be shared, i.e. the arrival of the aircraft carrying the load in question. The ability to interact with other external businesses through standardised processes allows a logistics provider to be contacted and given directions, etc. This diagram also explains the increasing role of ‘Open Source’ for building the necessary shared software, as well as ‘Open Standards’ for the agreement of standardised processes. ebXML as an

example provides a framework for individual industry sectors to customise as a market ecosystem for such interactions as ordering, call off on orders, shipping notification, receiving notification, invoicing and paying.

Common StandardisedAnd Shared Data

Industry SpecificStandardised Processes

Common StandardisedAnd Shared Data

Industry SpecificStandardised Processes

Enterprise UniqueCompetitive Processes

Enterprise UniqueCompetitive Processes

In this well informed and connected trading society, sharing information and processes efficiently, the ability to be able to read and react as quickly, or even more quickly, than others becomes a significant advantage. The technology shift to the use of the Internet and Web Services for external commerce creates

new forms of data to ‘read’ and new abilities to ‘react’ that make BI an essential capability


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5. The current driving issues – Why is BI a ‘hot’ issue now?

Recent surveys and articles in a variety of magazines, both the USA and Europe, suggest that up to 25% of Enterprises are at some stage of a Business Intelligence deployment, and that the figure for those intending to deploy in the near future may take this up to more than 60%. Given the relatively sluggish levels of activity in the technology market these seem to be remarkable figures, so just why is there such interest and enthusiasm for Business Intelligence? At least in part the figures owe something to the relatively poor defined nature of exactly what is Business Intelligence, covering everything from data base activities to workflow it sweeps in a wide range of projects, so it is perhaps better to define the problems that Business is looking to Business Intelligence to solve. These fall into three primary groups from which it is possible to determine four detailed types of project categories.

• ‘Packaged based’ Business Intelligence; The need to improve, or refine, the massive investments in Enterprise Resource Programmes, ERP, Customer Relationship Management, CRM, or Supply Chain Management, SCM, software made over the last five to ten years. These have individually, or jointly, produced extensive data that needs to be better utilised to drive commercially beneficial actions. Not surprisingly this is the area that Business Intelligence products from these vendors focus upon, offering integration with the already installed software, which will add further sophistication to the existing capabilities.

• ‘Data based’ Business Intelligence; The wish to better understand and make use of the vast, and growing, amounts of data of all types that Enterprises have, and are continually creating. It seems obvious that there must be value to be found from extracting statistics, or previously unrecognised relationships. As financial and transactional data has to be classified and held for legislative reasons over longer period of times with a corresponding rise in costs, looking to find a return on this cost has become a management focus. The data management companies focus their Business Intelligence products here.

• ‘Management information or Workflow based’ Business Intelligence; The requirement for more efficient operation in a period when all Business activities are subject to a tougher market. The ability not just to find, but to act in areas where activities overlap, and the existing systems and applications are relatively inefficient, has driven Enterprises’ interest in improving management of ‘workflow’. The response to understanding more about the actions required to optimise a given situation. In some senses this is a furtherance of the move some years ago for management reporting systems through ‘dash boards’, into being able to move to react, and act, quickly upon the information provided, a weak link in the past. This is the area where most innovation in Business Intelligence is taking place with the suppliers, or their employees, tending to come from either Management Information, or Workflow, backgrounds focussing on moving these capabilities into new areas.

Adding the above drivers together the obvious conclusion is that Business Intelligence represents an overlay onto existing applications, or data bases, that is required to provide a means to identify actions that will directly improve business performance. These words could equally be used to describe the reasons why Enterprises have moved to adopting ‘processes’ built around ‘application servers’, and are moving towards ‘Service Orientated Architecture’ using ‘Services’ to still further their abilities to rapidly connect together existing applications into flexible responses to market identifiable needs, or ‘Events’. However the background of existing BI product suppliers is often poorly aligned to this change, BI solutions will need to be chosen with some care, or they may further reinforce the inflexibility of the ‘old’, rather than the flexibility of the ‘new’ Adaptive IT.


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A more detailed look at individual project drivers breaks down into the following four categories; 1. Legislation; Possibly the biggest single driver overall. The impact of Sarbanes

Oxley on USA listed business with the legal requirement to comply within a fixed time frame with prescriptive new measures cannot be under estimated as to its short term impact. Other multi national businesses trading within the USA are finding that their auditors are pushing for them to comply as well. One of the three key requirements is to be able to identify and report within 48 hours an event that will have a material impact on financial results. This together with the immense amount of data and process change has led to an up take in the use of various forms of Business Intelligence. In Europe, Basel 2 in the Financial Services Industry makes similar demands on event detection and increases the need for understanding overall ‘financial positions’, causing the same need for extensive data and process change. Ironically, this has become necessary due to the increasing speed and complexity of the external trading market ecosystems, and the use of Business Intelligence in the Front office. This has out paced the Back office ability to maintain transaction records, and reports, in a timely manner, therefore a Bank can have traded itself into a position of capital inadequacy before any of its standard reporting methods based on daily, weekly, or monthly compilations from its trading records would be available to alert its management. In other vertical industries a selection of legislation to control various aspects of specific markets have appeared, usually in the form of different legislation from different regulatory bodies in Europe and the USA, thus adding to the complexity for multi national businesses in ‘managing’ their compliance. Interestingly all seek in one way, or another, to manage the interaction of market trading between businesses to ensure that some form of abuse does not occur. It can therefore be expected that as faster so called ‘real time’ electronic trading becomes increasingly the norm there will be more market legislation, and therefore more need to be able to detect, and act, around events using Business Intelligence. 2. E based Trading Processes and Mobility; There is no doubt that the numbers, and types, of trading transactions carried out through electronic processes are increasing at a linear rate. The improvement in operating efficiency in buying, and selling, in a more responsive manner to meet current circumstances, and demand, as opposed to a pre determined schedule based on past history, is obvious. The capability these systems deliver is part of the story, and as the number of transactions increase, the need for Business Intelligence to provide the ability for success becomes clearer. The topics of optimisation, and collaboration, within the trading market ecosystem are dealt with more fully elsewhere, but the consequences of ‘Mobility’ are the other project driving force. The term ‘Mobility’ is much misunderstood having nothing to do with cell phones, but referring to a ‘client’ that has no fixed relationship with any particular server, as in ‘client server’ architecture, but is able to work with any ‘service’, as and when needed, within a ‘services orientated architecture’. An obvious example being a ‘web browser (client)’, and its ability to work with any ‘web server (service)’ in response to a command as opposed to having a permanent single ‘server’ providing an application. ‘Mobility’ can thus mean ‘mobile workers’ using cellular or WiFi to gain access on a periodic basis when the service is available, or when an event has happened and there is a need to communicate with a


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particular ‘client’ or ‘service’, or it can mean ‘sensor technology’ such as Radio Frequency Identification, RFID, when the sensor tag communicates with a reader in proximity. Either way the result is more information being available on what is really happening in terms of workers in the field, or goods in transit. Early RFID pilots soon recognised that the immense amount of ‘small data’ this produces adds little to no value if it is written to a database, and then historical mined to discover trends. Being able to spot anominalies, and take action in ‘real time’, actually in the ‘right time’ frame is a better description, has great value. A similar case exists for ‘mobile workers’ where standard recording automation does not lead to productivity increases in the workers concerned whereas being able to manage the activities better in response to actually knowing what is happening can create major productivity improvement. Either way Business Intelligence to manage the flow of ‘event’ data and offer decision support for activity planning is required.

3. Vendor Created Opportunities; The advent of the previous sets of requirements

has not gone unnoticed by the major software vendors, or by new start-ups offering innovative approaches to the requirements. The approach being offered for Business Intelligence achieving more from the investments already made, a seductive business pitch, and accordingly there has been a strong sales effort with good results that has still further lifted the awareness of Business Intelligence. Whilst these are often good investments in terms of extending the functionality of the existing software, usually ERP, sometimes Database, they are often less than effective as a genuine approach to handling data from a variety of sources, including from the open market place. Instead of forming the basis for genuine Business Intelligence across all areas of the enterprise and its external markets they may well become a barrier due to adding the need for more specialised integration.

The Innovators from software start-ups tend to take a more focussed approach to solving a particular issue often with in an industry vertical sector, or around a piece of legislation. As such their products are easy to form a business case around, and in many cases to implement, but again the danger is in the ability to expand the basis for ‘enterprise business intelligence’. This is not to say that all products either from innovators, or mainstream software vendors are bad, and indeed some are strikingly able to answer the challenge of offering an immediate focussed implementation together with forming the basis for long term open integration. It is to say that care needs to be taken in both the product choice, and the subsequent method of implementation, to ensure that this is the outcome providing a long term success for Business Intelligence.

4. Business as Usual Requirements; Finally, there are all the usual pressures facing any

business at this time driving the effort to find more effective and efficient ways of working. Mostly these are based on some form of consolidation in order to remove individual functional isolation inefficiencies, and gain a clearer view across larger areas of the enterprise together with a view as to resulting changes to actions. This could be required for any number of normal operation reasons such as cost reduction, consolidation, merger and acquisitions, as much as for better management generally in an economically constrained period tight period.

In summary businesses are looking for ways to ‘read and respond’ faster through using

‘Adaptive IT.’ ‘Business Intelligence’ has become a key way of providing IT solutions to do this.


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6. BI Today – Current ways to implement compared

There have become several clearly defined approaches to providing Business Intelligence based on exploiting existing technology within other MIS systems already in use, or on focussing on a particular specialised requirement, such as legislation, in a vertical industry. These may be grouped under the following three main technology approaches; 6.1 BI from the Data Warehouse

In itself a data warehouse is a form of Business Intelligence implementation as it gathers together and categorises the data from a number of different systems to form a common data holding. This can both be used by any applications, including ERP systems, as well as permitting various forms of searches to be made on the entire data held. The ability to construct, and deliver to schedule, various predefined report formats is most attractive, more complex queries can be handled using On Line Analytical Programmes, OLAP, which, though time consuming to build, can address special requirements that may be able to create meaningful insights from using large scale analysis. Against these plus points are four possible negatives; firstly the cost and time of building a comprehensive data repository of this type. Many enterprises having spent millions in cash, and years of time, trying to perfect their data warehouses; secondly to maintain the data warehouse requires extraction, transformation and the load (ETL) of data from across the selected systems. A time consuming and expensive ongoing commitment that also normally carries a delay in actually making the data available within the data warehouse for use introducing the issue of the age of available data; Thirdly the tools for analysing and mining are specialised and require the services of skilled staff in order to build the reports that the users require. This makes it time consuming, and expensive, to change searches and reports on a regular basis in response to changing internal and external conditions, in some cases the availability of the staff may also be a further bottleneck. Finally, many organisations create multiple data warehouses with different roles, frequently driven by individual departments. This typically leads to silod solutions with replication of data and multiple versions of “the truth”, increased complexity of change, multiple vendors and a lack of visibility on the ROI or TCO of the organisations BI solutions. In addition there is the obvious charge that any such query, or report, is inevitably based on the historical past record of what has been transacted, and not the current events that are being reported for consideration. The past being a transactional record also means that it is a selective record, and cannot reveal the options that were available, but were not transacted. Business Intelligence from the Data Warehouse is essentially a trade off between the desirability to be able to perform complex analysis versus the age of the data on which it is performed. For those with existing investments in extensive data marts or data warehouses and needing analysis of past transactions then the correct Business Intelligence product well implemented will be a success. 6.2 Right Time Reporting from a Production Database

If the limitations inherent in a data warehouses, or even data marts, including needing to build one to get started, are to be avoided then another approach is to use a Business Intelligence product that can operate directly on, and with, the data that has been, or is being, written into a conventional database possibly even an application database. The benefit of this approach is the current nature of


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data available, when considered against the older extracted data in the data warehouse. However though this approach has attractions for its simplicity and directness by working on a limited set of the data being used in a few functional applications, it has had in the past serious limitations due to the inevitable impact on the performance of the database while supporting the original applications. With multiple applications as well as a Business Intelligence product all requiring access on a single database the demand for processing cycles can exceeded supply with the consequence that every thing slows down. This has been a widely observed difficulty with the approach, leading to having to restrict the numbers of users to the Business Intelligence service, or controlling the numbers of queries, both of which remove much of the virtue of Business Intelligence for providing ‘right time’ responses. The rise of MIPS ‘on demand’ using some form of ‘Grid Computing’ architecture, (on demand, utility computing, etc, all being different names for the same approach), suggests that this could be overcome thus making this a viable low cost approach for simple focussed Business Intelligence requirements. Adoption of ‘Grid Computing’ is also associated with the adoption of ‘Services Orientated Architecture’ in order to make the best use of the MIPS; therefore careful consideration of the best method to implement this approach can pay dividends in the longer term as well. 6.3 Right Time Reporting from an Operational Data Store

In the past the method to gain the benefits of ‘Right Time’ reporting whilst avoiding the performance issues was to provide a duplicate of the data in a form known as an ‘Operational Data Store’, or sometimes a ‘Report Server’. In effect this is a mirrored data base that can be used solely for Business Intelligence queries with out impacting the original database that is supporting the operational applications. This has been seen in the past as the most sophisticated approach to Business Intelligence as it gains the benefit of using the latest version of the data, but with out having any effect on actual operations. The difficulty, and the expense, in the approach lie in the implementation of the data synchronisation. Top quality database products from companies such as Oracle provide the necessary replication product, but it is not cheap or simple to implement. (The latest version of the database software from Oracle provides ‘Grid computing’ support to allow increased flexibility in the usage of MIPS). Assuming that the database in question cannot be supported by ‘Grid Computing’ alone ,and an ‘Operational Data Store’ is required, then in order to get the expected maximisation of performance it is not a simple matter of producing a mirror of the existing database. This will be optimised for the access of the applications it supports, the data should be mirrored in terms of content, but not necessary in the same format, instead the format should be optimised to support the type of queries that the Business Intelligence product will be making. This means producing, and managing, another database using full time administration as well as supporting the initial database, thus the operational cost, and possibly the implementation time and cost, may start to become closer to those of a ‘Data Warehouse’ or ‘Data Mart’ that the approach was chosen to avoid in the first place, though it will still gain access to current data. 6.4 Summary


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The three basic approaches have different benefits and limitations, to solve different needs at different costs, not only that but there are some products offering ‘Hybrid Approaches’ such as using an ‘Accelerator Engine’ for queries to speed up a production database implementation. What is clear is that these techniques are built soundly on historical data analysis more than on current events, though again some new Business Intelligence products are able to address ‘Services’ too.


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7. Enterprise Business Intelligence – Using Client Services and SOA

Currently Business Intelligence spans several different techniques offering a range of options that cover different requirements, most are of proven value, but new thinking is required. The business requirement is broadening, requiring more than a narrow specialised view on a single topic, and the overall change in IT technology from ‘Client Server’ to ‘Client Services’, based on ‘Service Orientated Architecture’, or SOA, provides the means to provide more. The purpose of this White Paper is not to examine in detail Client Services and Service Orientated Architecture, though something of a recap may help for this white paper. The purpose of Client Services is to define business processes in a granular manner, preferably breaking down complex multi step processes into single steps that can be combined, in any permutation to provide the required complex process. In order to achieve this Service Orientated Architecture ensures a common environment by supporting common interface specifications to allow this to happen. The model is that of the World Wide Web. Simple interface specifications allow any browser to work with any web server with the complexities hidden from the interface, unlike traditional ‘Enterprise Application Interfaces’, or EAI, were a semantic interpretation of the entire application is required. The combining of Service elements into Business Processes is currently a ‘manual’ operation following a requirement for a defined business requirement, using the ability to assemble and dissemble, in creating the right process readily, as defined by ‘Adaptive’ capabilities. The ability to change readily in response to market, and business demands, is crucial in periods of high market volatility. Client Services provides the technology for this, and as with the World Wide Web, the aim is for the standards for Services to become universally adopted. The goal is to allow a Business Process to be a transactional chain of the required ‘Services’ assembled in response to the business requirement that joins buyers and sellers together within a market ecosystem. This is currently achievable under controlled, pre agreed and determined conditions, but the capability to achieve this dynamically in response to events will be driven by the business gains in areas such as Supply Chain Management. The technology direction is to automate this so that an ‘event’ will result in the right process being ‘orchestrated’ from the available services in such a manner that the optimal response will be delivered even if the buyer and seller are previously unknown to each other. Appendix A explains this in more detail using an abstract from the Capgemini white paper on ‘Real Time’ IT. The extended value chain of buyers and sellers may change for each successive transaction as the optimum combination of aspects such as price, delivery, specification; etc will vary in response to each ‘event’ query. Obviously this requires a different relationship to the current ‘adversarial’ relationship between a buyer and seller negotiating for a one off deal that may then cover a period, or a quantity, to be called off. Whilst this may be beneficial for the management of the time and cost of the negotiation process it actually results in a loss of flexibility during the period of the contract to be able to respond freely to the market conditions. Collaborative working is the ability to allow all potential partners to automate their response on a continuously changing basis to each, and every enquiry, based on their current circumstances. Therefore factory capacity available may change the pricing, little spare capacity can be sold at a higher price, and too much capacity may justify a lower marginal pricing offer. Collaboration occurs when potential partners agree to work in this manner on the basis that there is, or will be, mutual gain for all. The emerging capability to ‘read and react’ to individual events in this manner has a potentially profound impact on the role, and concept, of Business Intelligence. In fact it is arguable that for the first time it will need to become truly ‘intelligent’ in terms of a real time response to current circumstances. Starting with an ‘event’ provoking the initial response, the feedback from the resulting chain of interactions with the market will in turn modify, or even drive the next action. This is very different from using data and management information today that is based on past transactions. This is using history to determine a response to a current and possibly new situation; the difference between driving forward by looking out of the back window to see where you have been, versus driving forwards looking out of the front window and making steering


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corrections in response to where you are currently positioned on the road, and where you need to be positioned on the road that is visible in front. At this point the need for Business Intelligence becomes self evident, but it cannot be the same form of Business Intelligence as in the past, based more on historical transactions than current opportunities, also making it a narrow focus on a part of the business rather than as overall focus on the impact to the overall enterprise. The subject of this section is the changes that will allow ‘Right Time’ actions, in response to current events happening within a ‘Threshold of Opportunity’ by providing ‘Business Intelligence’ through using the capabilities provided by the technologies of ‘Client Services’ within a ‘Service Orientated Architecture’. The following diagram explains a new way of thinking about combining these forces to achieve this;

ExceptionEvents

CurrentOptions

Rules

Mobility

HistoricData

FutureOptions

processprocessprocess

applicationapplicationapplication

ThresholdOf

Opportunity

No. of OptionsBecoming less

With passing time

In the past a singleOption was recorded

Data Mining show this

ServiceOrientated

Architecture

BusinessIntelligence

Event drivenresponse to

non predetermineddata on the basis

of the optimalopportunity at thecorrect moment

linked to the abilityto Orchestrate people

and process in aServices Architecture

Decreasing Value Decreasing Opportunity

ExceptionEvents

CurrentOptions

Rules

Mobility

HistoricData

FutureOptions

processprocessprocess

applicationapplicationapplication

ThresholdOf

Opportunity

No. of OptionsBecoming less

With passing time

In the past a singleOption was recorded

Data Mining show this

ServiceOrientated

Architecture

BusinessIntelligence

Event drivenresponse to

non predetermineddata on the basis

of the optimalopportunity at thecorrect moment

linked to the abilityto Orchestrate people

and process in aServices Architecture

Decreasing Value Decreasing Opportunity

Historic data has diminishing value as time goes by, and has to be mined with increasing exactitude to determine its value in a pre determined situation. The results of this can be of value to provide ‘rules’ for certain situations. These rules are inflexible, and this is an advantage when dealing with certain areas an example might be; ‘no shipment with out a purchase order and pre payment for this customer on the basis of a historical bad credit record’. This kind of data has been derived from ‘applications’ and is held in a traditional database. Business ‘events’ are trapped by ‘mobility’ the term denoting sensing and forwarding of data from a wide variety of places, then passed to the ‘rules’ engine, where if the rules permit the data is forwarded to ‘processes’ for action. The processes may be pre determined to cover the necessary tasks, or created ‘on demand’ by orchestration techniques to cover the requirements of the particular transaction. This mechanism is the basis for ‘event’ handling within a Service Orientated Architecture by using ‘services’ to define ‘processes’ in the front office. After the transaction has occurred it is recorded in a data base in the back office. The number of options available will reduce as time goes by, for a variety of reasons such as the expiry of offers from other players in the market. Therefore the ideal moment is when there is the largest number of options available, coupled with an understanding of the value of these option, because as time passes all the options bar one are likely to have disappeared. This is an important factor to understand as it introduces very firmly the reason why event driven real time responses are of such great commercial importance. The moment when there is the maximum amount of opportunity and options, is called in this diagram the ‘threshold of opportunity’.


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If the ‘rules’ are set correctly the ‘event(s)’ entering the ‘threshold’ are exceptions that need to be ‘interpreted’ by Business Intelligence to determine the optimal response, for the enterprise, taking all factors into account. This is the concept of ‘Enterprise Intelligence’, the ability to use all data across the different parts of an integrated business model in a coordinated manner with the different capabilities, in order to arrive at an overall optimum decision. Current activities lack the scale to achieve this; therefore the enterprise can only be seen in functionally separate departments, each individually optimising decision in respect of their own data and positions. These exceptional events captured within the threshold can be processed using ‘Agent’ based decision techniques. This is based on finding an optimal solution by comparing combinations of the granular elements as opposed to completing a pre determined processes. The use of ‘Agents’ to automate the orchestration of ‘Services’ is becoming a commonly accepted method, arising from their increasing use to handle the kind of complex operational situations that ‘services’ and ‘processes’ are effective in dealing with. While this paper is not about the complexities of Agent based software, once again it might be worth a short recap on their capabilities in the context of Business Intelligence and this is given in Appendix 2. Agents work by ‘optimisation’ to determine the best option from available choices through testing various combinations of possibilities but unlike rules the combinations need not be predetermined. The predetermination lies in the creation of the ‘role’ of each agent not in the subsequent behaviour. Each agent represents a single ‘point of view’ in a ‘socialisation’ interaction, much in the manner of the way that people work with in a meeting. In the same way that a meeting to solve an issue will adjust its decision making process to reflect the knowledge of the individual people present, agents will adjust in the same manner. Unlike rules there is no interdependence between agents, therefore new ones can be added, old ones removed, or modified at will. This allows different departments to ‘own’ their own agents that they can maintain there by adding their own experience to the ‘Business Intelligence’ process. This provides a scalable non dependant environment that allows all departments to work together resulting in ‘Enterprise Intelligence’, as opposed to the narrow focus of current Business Intelligence. A further possibility is to invoke a data search for more information on the topics that the ‘event’ provides data upon, thereby making it a search within the current context as opposed to a search on a historic question. The ‘Enterprise Intelligence’ that these actions provide can be used to invoke, or orchestrate, the selected ‘services’ to provide the optimum ‘process’ to complete the response. This may initially be a semi automatic process asking a selected user, with knowledge of the topic identified, to confirm actions, or, in time, become a fully automatic response. The use of feedback mechanisms means that the numbers of a specific exception will diminish until it can be handled by ‘rules’ as a known event/process chain, and this then frees capacity to deal with further new exceptions. The overall issue to be considered, and the need for rethinking the approach to Business Intelligence is the application of ‘real time’ computing, coupled with the resulting ‘real time’ markets being better monitored by ‘mobility’ devices. Taken together these changes will require a significant shift in the way Business Intelligence is both provided and the role it plays in use. Designing and implementing a Business Intelligence solution today needs to be done in a manner that can be ‘grown’, by developing it to work with Service Orientated Architecture as much, or may be even more, than with the data architecture that the current Business Intelligence products are designed around.


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7.1 A Use Case Example

A use case may illustrate the approach better. This is based on the current interest that national governments around the world have with identifying undesirable travellers seeking to gain entry to their countries. Currently, using the results of collating data in various databases a profile of people to be identified and rules for an immigration official to use are drawn up. This is a historically accurate description of an individual, or a group of people that have been identified in the past as ‘undesirable’. On arrival at an immigration desk the passport check will indicate them as in need of a more detailed interrogation, or may result in immediate refusal. Either is intensive on time for those concerned, as well as those queuing behind the person being questioned. From an event and threshold view there are multiple stages at which the check could be made; booking to travel; checking in with the transporting company; arriving after travel; holding for more questioning; finally, having to find someone after they have ‘disappeared’ into the country. As each stage passes the numbers of options to ‘manage’ the event reduces with the time, and cost of the event increasing. The key to the problem is to locate the ‘threshold’ time when the maximum amount of information, together with potential options, is available to make a decision and act. At the same time the threshold moment must provide a wider range of inputs than purely the immigration officer, or their department, alone can provide so it will need to use ‘enterprise intelligence’, or even be an ‘ecosystem intelligence’ based solution involving airlines etc. The ‘threshold’ would be when the passenger was actually on the aircraft in transit in the case of air travel, and the ecosystem to provide intelligence would include the airline, credit card companies and others holding some aspect of the identity in connection with the event of the passenger travelling. Checking in requires the passenger to present a passport for the airline to inspect, online checking of machine readable passports will show that this is a valid passport that has been correctly issued, and is not currently ‘wanted’, but it cannot confirm that the holder is the person to whom the passport has been issued. The widespread adoption of Biometric passports is still some way off, and in any case the facilities at check in expensive. However, other data is available to be used in concert to increase the accuracy of the identification process. There are a number of transactions usually associated with the purchase of an airline ticket that can be used in conjunction to verify identity; these include a credit card, a phone number, increasingly an e mail address, as well as a physical address. The presence or absence of these represents a first level of authentication, tickets bought for cash are immediately suspected, as an example. The names, and addresses, should all tie together in a recognisable manner, but the searches will require a Business Intelligence ecosystem working in collaboration to establish bona fide travellers. The benefits to the entire travel industry are sufficient to encourage the mutual win-win to all from this collaboration, and would also permit much of, if not all of, this data to be pre-searched before the passenger ‘check in’ at the airport with a passport for final authentication. Indeed it is also possible if this was an unsatisfactory result to ask for extra identification to be provided prior to travel as an option. All of these can be checked through ‘rules’ with automatic escalations to the next level. The period of the journey from check in to landing represents the threshold to handle the exceptions which could not be handled by, or fell outside the scope of, the rules. This is when true ‘intelligence’ is required as to how to handle the situation by making further searches in different databases to find existing references, or correlations, that could relate to the passenger and information provided, or even to establish the questions to ask on arrival. It is possible to handle some aspects of this through a rules structure, mostly to do with the procedures. In main it does require the use of ‘agent’ based software with its abilities to ‘optimise’ situations that have not been predetermined, allowing different departments to own their own agents in the threshold. On arrival the intelligence relating to the current event of the particular person, and their current journey, will have been processed with comparison to historical data to determine the action to be taken on disembarking, together with updating of any records involved to improve further accuracy of intelligence.


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If the requirement was to prevent a potential terrorist flying, the same processes and data sources would be largely used, augmented by some specific intelligence information, and the “Threshold of opportunity” would be before the flight took of.


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8. Tactical, Strategic and Enterprise BI – How to deliver as ‘Services’

Business Intelligence allows organisations to access, analyze, and share information in order to drive more informed business decisions. It is increasingly recognised as key for Business success.

Gartner Group published view on Business Intelligence

Unfortunately, like most advice on the topic of Business Intelligence it stresses the potential value without offering any practical advice how to gain the value, or implement. The key questions for most CxO level management are; where and how to go about applying Business Intelligence tactically to get the most effective returns; together with how to insure that this meshes with longer term strategic goals to continue to extend the capabilities thus providing increasing value, rather then becoming a costly long term liability. This white paper has examined Business Intelligence today in terms of; current approaches built around historical data analysis; the legislation that is forcing enterprises to compile more data with increased reporting requirements often in very short time frames; and the increasing need for ‘event driven information to be handled in ‘right time’ to provide optimised business decisions. In addition it should be remembered that these changes are themselves being brought about by a technology shift to ‘processes’ and ‘web services’ with MIPS ‘on demand’ and that therefore Business Intelligence implementations must take account of this. So Capgemini would summarise the approach as; The challenge is to initially gain from the immediate tactical benefits of ‘making more of the data you have’ then to move to the strategic positioning of ‘making more of the opportunities your enterprise has’ by embracing the technology change from fixed functional applications to adaptive service processes.

Capgemini view on implementation of Business Intelligence

This requires moving from islands of informed operations based on data analysis, where the implementation decision has been largely based on choosing a product that is compatible with the existing MIS database, to Enterprise wide Business Intelligence driven by the overall business objectives of the Enterprise. To do this the Business Intelligence product has to be selected on broader grounds, both business and technology. On the business side this means a wider, and more careful, assessment of the role that Enterprise will require Business Intelligence to play, coupled with a detailed understanding of the nature of events that will be encountered, and the form of optimisation that will provide the necessary answer. On the technology side this means alignment with the overall shift in MIS investment towards delivering ‘more for less’ by using ‘Client Services’ technology delivered by ‘Service Orientated Architecture’ and Web ‘Services’. The case for being able to improve the quality, and role, of Business Intelligence through using Web Services is compelling with some of the leading Business Intelligence products are already exploiting this today by operating as a ‘Service’ in their own right able to call, or be called by any other service. As these ‘Services’ are for the most part in the ‘Front Office’ covering the most ‘interactive’ operations where events are most likely to occur this is obviously a prime area for ‘Event’ driven ‘Right Time’ Business Intelligence to focus. There is the potential to improve business efficiency measurably and redefine the role that Business Intelligence can play for the Enterprise by so doing. The second benefit comes in implementation and on going deployment based on the nature of ‘Web Services’ using a standardised interface to integrate with any, and all, other ‘Web Services’ or more simply ‘Services’. This approach can work internally to parts of the enterprise, and externally, to include customers and suppliers, or across a large multi national Enterprises operating divisions to ‘join up’ operations. The benefits in the cost of development, and integration, across the entire MIS operation are great, and the use for new developments is increasing rapidly driven by all major Software suppliers endorsing the approach with new products and tools to incorporate their existing applications built in ‘Client Server’ formats.


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‘Web Services’, or ‘Services’, have the potential to lower Business Intelligence implementation costs because, quite simply, a large part of the work is around integration, and therefore the more data sources that are required to be part of a Business Integration solution the higher the cost. This is counter productive as the role, and often the accuracy, of a Business Intelligence solution is limited by the cost of increasing the number of data sources that can be used to provide the answers. A similar problem exists in the cost of delivery of Business Intelligence to individual users, again restricting the numbers that are included within the solution and who therefore can benefit from the information. This difficulty and cost has been the key reason for taking a technology focus on selecting a Business Intelligence product by looking to see which has the best fit to existing MIS systems, as opposed to being the best fit for the business. This short termism creates a further problem by often not providing the best long term solution that will be capable of extending the numbers of sources incorporated, and the number of people empowered. Higher level standards are being to emerge and make an impact in the support of ‘open’ integration; such as the ‘Common Warehouse Metamodel’, or CWM, or queries such as the ‘eXtensible Reporting Business language’, or XRBL, even ‘Ontology Web Language’, OWL, providing semantic meaning for ordinary words. Taken together the impact for the provision of ‘Enterprise Business Intelligence’ will be profound. The functionality of defining dimensions, hierarchies, calculations, business rules and reporting formats and sharing them across Business Intelligence processes through the use of ‘Services’ will open up the role and quality of Business Intelligence as well as making it more accessible to more users. The import and export of data from existing applications is becoming simplified by the use of ‘eXtensible Mark up Language’, XML, in a similar manner. The ‘open’ approach also offers benefits in programming costs as a variety of languages can be used; such as Visual Basic, C++, Java etc, and the results can be held as reusable components in .Net or J2EE libraries to support quick assembly and delivery of new requirements. Some of the components may be reused from other work, not necessary Business Intelligence, and some may even be brought in through using ‘Open Source’. Business Intelligence delivered in this manner will also benefit from the advantages of improvements in the reliability, and security, of messaging thus allowing broader geographic usage by people over the Internet, or other low security communication services. The adoption by the IT industry of a ‘Services Orientated Architectural’ approach based around ‘Services’ with standardised interfaces has a profound impact on the choice of Business Intelligence product, and on the role that Business Intelligence can, and will play. This new approach will play a powerful role in moving Business Intelligence from a limited area of operations to a generic Enterprise wide capability. Implementation should however still be planned around tactical phases that deliver maximum value for minimum cost, and the following may offer useful guidance;

• Phase 1 – Operational Efficiency in Selected Areas Implementing Business Intelligence to reduce the cost, and improve the efficiency, of selected business processes such as Customer, or Supplier Relationship Management, CRM and SCM. It may possibly add some form of directed workflow to actually improve the actions in response to understanding the process better.

• Phase 2 – Predictive Analysis for Planning Purposes

Taking and developing the input from Phase 1 to build data models that can offer ‘what if’ analysis to aid the business planning, and decision making, for still further operational improvements with some degree of strategic influence becoming apparent. This represents a significant improvement over current forecasting techniques.

• Phase 3 – Event Driven Optimisation

The extension of the planning models, together with historical analysis, for guidance in determining actions as a response to non pre determined, or complex event combinations. These should aim to


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introduce the capability to provide an optimised set of activities in the right time will significantly improve business performance.


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9. People, Collaboration, and BI – the missing link in BI projects

The current structure of work is based on the principle of defining and containing responsibilities to limit the risks of poor decision making by individuals. The decision to do something is followed by the accumulation of data on all aspects that might affect the decision to be made using traditional historically based Business Intelligence. In fact this type of decision making is rarely time critical as it occurs after the event, or events, have happened, being used to determine the redefinition of responsibilities for the future. As such the existing organisational structure and methods of working are unchanged. Event driven optimisation is by its nature time critical, and does not permit the accumulation of data in the same way, neither will the decision that needs to be taken be pre defined, and contained in the old way. In short to handle events in right time is not only a technology issue it is a people, and organisational issue. The decision makers will need immediate access to exceptional events, irregularities, the things that do not fit the rules and structure of the business, together with the necessary decision support advice. Then the decision maker will need the authority to actually make the decision with a commitment from the Business right then and there. The form of the commitment may be an immediate action, but on many occasions it will contain an element of ‘negotiation’ to make a counter offer to the one that started the event. The ability to interact and negotiate a mutually agreed optimum situation for both parties is the art of collaboration, as opposed to the existing art of making full and final offers that are only open to being accepted as is. The changes in the roles and responsibilities that decision makers will need to be able to adopt are new, and profoundly different. As the online electronic commerce ecosystems between trading partners expands, the role of Business Intelligence will expand, making the question of a change to the organisational structure more acute. The following are some observations on how these changes may manifest themselves;

• A smaller number of people with broader, more empowered, areas of responsibility must be created to handle the use of ‘right time’ enterprise business intelligence decision making.

• People must have clearer areas of expertise catalogued with directory services to allow Business

Intelligence workflow to determine who should see what information under what circumstances.

• Organisational structures will need to move from being hierarchal to being based on capability and expertise with a corresponding flattening of management structures.

• Work units will move from being functionally based, (around applications), to being process based,

(around services), in loose coupled teams coordinated by the event, and the solution.

• Responsibilities on individuals will be increased moving from the current following of procedures to become more on the results, cut across many existing activity boundaries, around individual accountability.

• More people will become part of ‘management’ through taking advanced decisions, but this form of

management will be based on individual working, or deployed expertise, on a specialised topic rather than general management skills leading to a decrease in the numbers of administrative managers.

• Organisations will need to alter their thinking on compliance, moving away from narrowing choice

and options available to individuals in an attempt to gain control by empowering them in a overall compliant environment..


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APPENDICES


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Appendix 1 – Real Time IT from Client Services using SOA

Since the advent of the World Wide Web with its architecture based on using the Internet to provide ‘any to any’ connectivity between a handful of standardized technology elements, notably the Browser, the Web Server, with the Lockup and Search Engine to orchestrate, there has been a steady development of new technology products inspired by this new technology milestone. The existence of these new technology elements, each an answer to some aspects of the demand for improved IT capabilities, and mostly capable of individual implementation, has some what obscured the overall development of a changed architectural model. It is only recently that it has even been possible to talk about Service Orientated Architectures, or the Client Services model, with some broad recognition of what is meant. Client Services is the product of integrating a handful of new technologies, including Mobility, Grid Computing, Web Services and the ability to orchestrate the pieces into functional processes in response to ‘events’. The fact that each technology area can be implemented individually for gain is both a benefit, as it will create the overall ‘Real-Time’ computing capability within Enterprises, as well as across the market ecosystems; and a threat as individual implementations may not align to complete the Real-Time computing capability. The so called ‘PC Network problem’ when the individual implementation pf PCs and Networks had immense benefits to individual requirements, then when the overall architecture became clear, the non alignment of these implementations became a major issue, costing time and money to put right. The importance of understanding the architecture for event driven Real-Time computing is that it is made up of the hot technologies that enterprises are investing in today; Grid Computing, Web Services and Mobility devices such as Radio Frequency Identification tags. There is opportunity to get it right in delivering individual projects, and rather more opportunity to get it wrong! The use of eXtensible Markup Language, XML, in vertical sectors such as Financial Services Industry illustrates the point. Using XML in projects is growing, but few FSI enterprises have yet appointed a decision maker with the power to manage an overall governance model for the use of XML with full understanding of not only its internal need for alignment, but also its external industry standards development. Beyond schema management lays the almost untouched need for contract management in order to invoke the necessary responses to data changes. In this example lie both the benefit, and the problem, of moving to Service Orientated Architectures as well. Delivering individual projects and requirements using Service Orientated Architectures does not automatically provide a holistic environment in which, over a period of time, the parts will come together to form the whole. If this does not happen, the benefit to the enterprise will be lost and a further layer of technology will have been formed, making change more difficult and expensive. There must be an overall conceptual architecture that will provide direction, and governance, to the individual project teams resulting in the building of a low cost, transaction orientated environment where a Business Service and an IT Service is recognizably the same thing. When this stage is reached then the long sought goal for IT alignment to business needs will have been reached through the clear mapping between the Business and the IT service. The fact that the business is now represented as a series of ‘services’ that can readily be brought together, both internally and externally, in response to real world events, through a new set of technologies broadly grouped under the heading of ‘Orchestration’ and ‘Optimization’ is the change point from historic abstracted procedures integrated via data. Event driven IT responding to the Real World in Real-Time enables interactive, iterative Business Collaboration, and, Services Orientated Architecture is the building block. Though Business Services is clearly the obvious target for the IT organisation, there are in fact six categories of IT System Services that need to be identified, and managed, to deliver systems that can support services, or service calls of all types;

1) Business Services should provide value to business users. Their function and behaviour supports business execution. Business services can be provided by combining IT System Services and the activity of service providers, such as business people. Examples are payments processing, order fulfilment and logistics administration.


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2) Information Systems Services provide value to Business Services. Their function is the automated processing of business tasks. They implement business logic for processes such as incoming payments administration, order entry and route planning.

3) Web Services are special technical infrastructure services that use web technology to expose other services to the outside world. They can be implemented internally within an organisation, within their intranet, or externally to other service providers, using the Internet. Web services use Internet specifications and standards; HTTP, XML, SOAP, WSDL and UDDI to define and expose themselves. Some web services may expose business services such as ordering but typically web services are still used just to expose functionality within a system.

4) Technology Infrastructure Services provide value to Information Systems Services (and of course) Web Services. They enable Information Systems Services using shared common technology. Strictly speaking they should not contain business logic. Examples are web access service, data storage service, white and yellow page services, broker services and wide area network service.

5) Mobility Services to input the information on events and / or accept commands to respond to events. This can be any form of device from a handheld device for mobile workers such as service engineers, through to sensors and sensing covering Radio Frequency Identification Tags, Information Flows from market transactions etc.

6) Support Services manage the delivery of all IT System Services in a live operational environment.

Services need to be clearly understandable as to their purpose using a common manner that allows them to be found and used. This description along with the definition of the level of service should be managed through the service contracts located in the services directory. Furthermore, the service providing mechanism must have measures for handling exceptions in the provision of a service. Integrity of the service is vital, and therefore the management of data used by, or in, the service must be resilient and enable multiple services to be supported if necessary. The level of componentisation of services is the key to maximise re-use of services generally, but the principle of service distribution is fundamental to operational realisation of effective re-use, this calls for great care in the definitions of service interfaces. A service may have more than one interface to accommodate different requests such as a user versus a machine, but each interface must be safe, secure and consistent during the transaction and be able to manage the situation of multiple interfaces being accessed, this includes a graceful failure capability to send back invalid, or unavailable messages if need be. The technology parts at a more physical level can be grouped and arranged in a conceptual manner to each

other as in the diagram; A quick check on this architecture, and its roots on the Internet and the World Wide Web, describes how the architectural model works. Using the Web as an example of a ‘client service’, the Browser is the Mobility ‘client’, and the Web Server is the Grid ‘resource’. The Web Server accessed could be geographically any place, belonging to

anyone, but it does provide the computational delivery as a Service to any Browser via the open network that supports any to any connectivity. The two are connected on demand by a URI, or ‘universal resource indicator’ that orchestrates the requested or required ‘service’.

Services ArchitectureLinking everything

together? ? ?

MOBILITY – the Internet of Access

GRID – the Internet of Resources

Agent Optimisation

Semantic StdsOWL 1.0

WS-Eventing

Ws-RF


together


together? ? ?


? ? ?? ? ?


GRID – the Internet of ResourcesGRID – the Internet of Resources

Agent OptimisationAgent Optimisation

Semantic StdsOWL 1.0

WS-Eventing

Ws-RF


26



An important aspect in this is how to discover the service that is required; in the case of the Web itself it is represented by search engine technology. The ability to find what is wanted from the masses of content available without knowing more than a few key word parameters have produced a whole new technology that works in a very different way to previous ways of indexing and finding data. However, it has a its limitations, and the results in the sheer number of options that result speak for themselves, the need is to find the right answer for the context in which the question is being posed. The contextual question requires the use of Semantics, the ability to describe within context, bringing back the topic of self describing data, or alternatively the use of standardised agreed vocabulary of terms. The Semantic Web is about moving beyond searching for a collection of key words and using an agreed language to describe items within their context, the first release of this language has just occurred. The OWL, Ontology Web Language is designed for use by applications that need to process the content of information instead of just presenting information to humans. UDDI, Universal Description, Discovery and Integration was supposed to provide similar functionality for Web Services, unfortunately after a promising start it has not kept pace with the needs for being able to also deploy and run services when located. Real-Time computing is based on supplementing this with the introduction of a whole new world around Mobility clients able to sense, and provides responses, to Real-Time events with out the aid of human intervention. Using the orchestration of events to find the optimal services and responses through both new ways of using network based services, and the steady introduction of Agent based software allows the ability to handle the ‘any to any’ complexity without predetermined rules. The event driven Real-Time responses, as opposed to the predictive nature of abstracted procedures, results in a chaotic and non predictive requirement for computing cycles hence the need for 'on demand' supply of MIPS using Grid computing. The arrangement of the Mobility and the Grid services, even the construction of Web Services offer recognisable methods to many practitioners of IT Architecture, but the concept of Orchestration and Optimisation is the real key to Business success. The consequences of the Real-time connected ecosystem are that there are so many variables that the ability to optimise a situation better, and faster, than competitors becomes the key differentiating factor. In financial markets the ability to respond to trading markets faster and more predictably led to the introduction of ‘program trading’, with some terrible consequences. This was because they were quite simply programs that worked by rules and would relentless follow one course of action unable to comprehend any other aspects of a situation. Agent based software is increasingly being deployed as an element within well known complex software products. Whereas rules struggle with more than 15 to 20 definitions agents are capable of infinite judgements in the context that they have been programmed to understand. Agent based software will increasingly be based upon capturing the experience of a skilled person in a manner that permits this to be used to make hundreds of thousands of decisions a day to improve the overall capability of an enterprise to reach the level of its highest performing employees on a routine transactional basis. However, this is not a substitute for human talent, more a support to allow the expertise to be employed at work levels that a human cannot sustain, and most importantly of all allowing the expert to devote time to continuous improvement. Real-Time Business Collaboration calls for sustained levels of interactive decision making that are beyond the current capacity of humans to provide, Real-Time computing therefore must be able to provide the intelligent orchestration and optimisation that is currently provide by users on a transactional basis, leaving Humans to further refine and define the services to market and the decision making criteria to increase their Enterprises competitive edge. Real time computing requires Business Intelligence to provide in near real time accurate

information within the context needed to support complex decision making

This appendix is an abstract from the Capgemini white paper on ‘real time optimisation’ entitled ‘Making IT Real; – moving to use Adaptive IT for Business Collaboration’.


27



Appendix 2 – An overview on Agent technology

A software agent is an intelligent software object that can be programmed to operate proactively to achieve multiple predefined goals. The agent has senses to gather information, reasoning to evaluate it and the authority and autonomy to act independently. Thus, it can monitor networks for events, consider new information, identify unexpected events, learn from previous results, and trigger actions that will bring it closer to achieving its objectives. Deploying these agents throughout an entire market ‘ecosystem’, (within and across companies), provides the means of real-time communication, optimization and execution. The key capabilities can be considered to be; Sense – monitoring of the business network to identify the visible solution space and real-time detect exceptions or unplanned events Analyze – development of the correct economic model necessary to resolve the exception. These models are based on local decision-making strategies, which are capable of aligning-balancing local goals with overall goals of the business network Act – providing distributed computational capabilities across the trading network and a behavioural framework for intelligently managing peer-to-peer interaction. In behaviour Agents exhibit the characteristics first described by Wooldridge in 1995, and have subsequently been accepted and reused as the basic description of Agent behaviour;

• Autonomy: an agent operates without direct intervention of other agents or humans and has control over its actions and its internal state.

• Responsiveness: an agent perceives its environment (the transportation network being monitored, for the research described) and responds in a timely fashion to changes that occur in it.

• Pro-activeness: an agent doesn’t simply react to changes in the environment, but exhibits goal-directed behaviour and takes the initiative when it considers it appropriate.

• Social ability: an agent interacts with other agents (if it is needed) to complete its tasks and help others to achieve their goals.

• The above characteristics form the concept known as the ‘weak notion of agency’. The ‘strong notion of agency’ is described by properties that are more usually applied to humans who act as agents to other humans:

• Mobility: The agents can move around an electronic network. This means that not only robots are characterized as mobile, but also an agent that is ‘moving’ through the Internet can be classed as mobile.

• Veracity: An agent will not knowingly communicate false information. • Benevolence: The agents do not have conflicting goals, and therefore they will try to do what they

are asked to in an aligned fashion. • Rationality: The agents will not act in such a way as to prevent their goals being achieved. • Cooperation: The users specify what they want to be performed on their behalf by the agent, and

the agent specifies what it can do and provides results. Different Types of Agents – the concept of ‘levels of Agents’ As the range of events that might need to be found are very large there are different types of agents constructed in different ways to handle these differences, and the following are some examples of both the types and the supplier. In time it may become possible that many of these types will merge into agents able to support a range of activities, and as part of this one of the key concepts for the future is that of the ‘Semantic Agent’. The term ‘semantic’ merely confers the ability to understand in context to actions and events a wide range of data types. Tim Berners-Lee, inventor of the World Wide Web, believes that the next stage of its development will be as the ‘Semantic Web’ where agents will be deployed to make sense of this increasingly large and chaotic example of a Market ecosystem.


28



Level 1 Agents; Simple Monitoring Agents • Agents either passively monitor, or actively search, the market ecosystem and on finding what they

were assigned provide ‘flagging’ when the specific events happen. • Increasingly this type of Agent is being built into functional software at a variety of levels from

monitoring the performance of IT systems to specific monitoring of functions in areas such as Supply Chain Management software.

Level 2 Agents: Simple Deterministic Agents These agents are able to solve problems based on a form of given rules where each agent works on one event defined by one rule set and the relations between agents are not used for finding non rule covered optimizations. Therefore the agents act deterministically, and their solutions are predictable, but the situations covered are more complex than a single rules engine could cover. An example in an Adaptive Capacity Management Software providing;

• Incoming events are detected from various sources with every event represented as data change. • The event bus detects the semantic value of each event and invokes the corresponding agents. • The intelligent agents (event handlers) react to events, check the current status of the model in the

persistence layer, and invoke, if necessary, the appropriate optimization engines. • Each agent acts on the sub-model that is defined by the value of the events, uses the engine to define

optimal solution on the sub-model, stores the solution for other agents, and creates, if necessary, new events to feedback into the system.

Level 3 Agents: Complex Deterministic Agents These agents are able to solve more complex problems than those above, and rather than working on a single event, they are designed to provide services on request to multiple clients, possibly concurrently, and to respond to many distinct events that may occur in their environments. The relations between agents are more important, as level 3 agents typically make use of the services provided by other agents. They still act deterministically, but the complexity of their individual behaviours, and the possibility of concurrency, means that global system behaviour is more difficult to predict. While such agents have until recently been built using conventional programming languages, commercial products are now available which employ high-level Agent Programming Languages to largely automate their construction. The following is an example of a commercially available product solution detailing what it provides;

• A service-oriented agent framework based on goal-directed agent technology for deployment in standard J2EE application server environments.

• A graphical agent modelling and development environment that allows agent types and their goals, behaviour and data to be specified in a high-level agent modelling language.

• The intelligent agents react to events and service requests that may be communicated via synchronous or asynchronous communication mechanisms, including web services.

• Each agent incorporates a powerful execution engine that produces runtime behaviour by dynamically assembling appropriate plans on the fly according to its goals and circumstances.

Level 4 Agents: Non-deterministic Agents There are two types of non-deterministic agents and these are often used as a combination of both types when building a solution. Currently, these are not commercially available needing to be built individually to implement a particular solution. The two types are; a) Self-modifying rules – where the actions of the agents are not predictable as they are self-learning, and therefore ‘adaptive’ to the environment; b) Dynamic relations – whereby the agents optimize their environments collaboratively. Each of them possesses some intelligence, but the main intelligence emerges from the network of agents and their collaboration. An example of a level 4 agents solution (in this case built by Capgemini), provides;

• Events are found by a monitoring agent located locally to the event and reported. • Next the ‘option finding’ agents bargain with each other to see who should handle this event or how

to share the problem solving with other agents.


29



• This creates a sequentially declining optimization wave beginning at the location of the initial event moving through the whole net re optimizing the network globally, (water drop theory)

• Waves of different events meet create interferences and the network is continuously re optimized. Simplification through the use of Multi-Agent-Systems, MAS. The increasing use of agent based software is simple to explain, it simples the dependence on using very complex mathematical models, and or equally complex rules engines, both of which may well work to solve the requirement, but are very expensive to build and maintain. As complex situations in commercial environments can be expected to be subject to continuous volatility this has made the applicability of building and maintaining such approaches as uneconomic. In an agent-based model, the system is represented as a collection of autonomous, interacting entities referred to individually as Agents. The Agents behaviour is determined by their current circumstances according to a set of internal rules. These internal rules may be relatively few in number due to the basic concept of simplicity in each agent with the complicated interaction being handled between the Agents. Alternatively, a smaller number of more complex agents that employ more sophisticated reasoning mechanisms and representations of behaviour may be adopted. The rules may be simple if-then clauses, hierarchical plans, or graphical processes, and execution can employ more sophisticated machine learning algorithms. Large numbers of repetitive actions between many agents are required to allow for the emergence of unexpected behaviours. To achieve realistic simulation of a system, computers are needed to explore the possible dynamics; these dynamics are based on the new concepts of optimization, and, are effectively out of the reach of pure mathematical methods. However as the actual amount of computing power required for each agent and the collective optimisation is low due to the use of simple edge driven rules this is an inexpensive technique. It is this change in approach that enables commercial implementation of requirements that would formally have meant using ‘super computers’ in research establishments. Parameters of the model are set to represent a situation of interest, and the model is run for a given number of iterations. Every software component within a multi agent system has to carry out problem solving actions in order to achieve its goals. When acting on their own, their functionality determines the right actions to perform in certain situations, however in many applications this determination must often be made with limited information and computational resources, under hard or soft deadlines. This leads to a need for notions of bounded rationality that specify how optimal or good decisions may be made with imperfect information limited resources. Within a multi-agent system agents must also consider the actions of the other software components as well, based on some more general principle of social rationality. The rules and conventions of a "society of agents" may also be represented explicitly by means of norms and interaction protocols. This concept of bounded rationality has been a further factor in the successful commercial use of agent based software solution as it allows for a progressive implementation with functionality being added as and when required, as well as supporting the ability to work with existing software. Perhaps most importantly it allows control of unforeseen circumstances with out massive testing programmes. Additional Information The European Union has been an active supporter of Agent based Technology through its programme for supporting European based technology innovation, possibly through this support coupled with the high capabilities for Mathematics found in several European universities Europe seems to be leading in this technology area at present. The work includes publishing a roadmap, www.agentlink.org/roadmap predicting how agent based software will be adopted around the following principle time frames; • 2002-2005 – Closed Agent Ecosystems, ad-hoc designs using pre defined protocols, simulation scalability • 2005-2008 - Cross Boundary Systems, structured agent designs, semi structured languages, large number

scalability • 2008-2010 – Open Agent Systems, standardised agent designs, advertised standards on Grid Computing • 2010 onward – Ubiquitous usage and scale, learned protocols and the emergence of new languages


30

http://www.agentlink.org/roadmap



Appendix 3 – A Glossary of Mainstream Major Standards

The following is not an exhaustive list and the including, or omitting, of any particular standard should not be taken as any particular comment upon its individual status. The list is merely an attempt to provide a glossary of some of the more common standards

802.11 Wireless LAN standard for WiFi access points determining number of channels and

radio spectrum, 802.11a, 802.11b and 802.11g available now and 802.11i expected with advanced security in 2004

ADpr Active Digital Profile specification, submitted to the OASIS Provisioning Services Technical Committee for advancement as part of PSML

AES Advanced Encryption Standard, Wireless LAN standard expected with 802.11i in 2004 ASC X12 The Accredited Standards Committee (ASC) X12, accredited by the American

National Standards Institute and comprised of cross-industry representation, develops robust e-business exchange specifications and electronic data interchange standards.

AuthXML Security specification submitted to the OASIS Security Services Technical Committee for advancement as part of SAML

BPML An effort by the BPMI consortium to do much the same as WSBPEL. BPSS bXML Business Process Specification Schema provides a standard framework by which

business systems may be configured to support execution of business collaborations consisting of business transactions.

BTP Business Transactions Protocol, an XML-based protocol for managing complex B2B transactions over the Internet

CALS Continuous Acquisition and Life-Cycle Support, a US Department of Defense initiative to improve weapon system acquisition and life-cycle support processes through accelerated creation and application of digital product data and technical information

CBEFF Common Biometric Exchange File Format CIQ Customer Information Quality, a family of XML specifications for customer

profile/information management CRML Customer Relationship Markup Language, an XML vocabulary specification that

defines customer relationships, submitted by MSI Business Solutions to the OASIS CIQ Technical Committee

DSML Directory Services Markup Language, an XML specification for marking up directory services information

DTD Document Type Definition, the building blocks of an XML document ebXML Electronic Business Extensible Markup Language, sponsored by UN/CEFACT and

OASIS, a modular suite of specifications that enable enterprises of any size and in any geographical location to conduct business over the Internet

ebXML CPA ebXML Collaboration Protocol Agreements ebXML CPP ebXML Collaboration Protocol Profiles ebXML CPPA ebXML Collaboration Protocol Profile and Agreement specifications that

define CPPs and CPAs ebXML IIC OASIS ebXML Implementation, Interoperability, and Conformance Technical

Committee working to facilitate the creation of interoperable ebXML infrastructures and applications

ebXML MSG ebXML Messaging Services Specification, which provides a secure method for exchanging electronic business transactions using the Internet

ebXML RegRep ebXML Registry Repository Services Specifications, which define interoperable registries and repositories with an interface that enables submission, query and retrieval on the contents of the registry and repository


31

http://www.oasis-open.org/committees/tc_home.php?wg_abbrev=provision

http://www.x12.org/

http://www.oasis-open.org/committees/tc_home.php?wg_abbrev=security

http://www.oasis-open.org/committees/tc_home.php?wg_abbrev=business-transaction

http://oasis-open.org/specs/tablemodels.shtml

http://www.oasis-open.org/committees/tc_home.php?wg_abbrev=xcbf

http://www.oasis-open.org/committees/tc_home.php?wg_abbrev=ciq


http://www.oasis-open.org/committees/tc_home.php?wg_abbrev=dsml

http://www.oasis-open.org/committees/tc_home.php?wg_abbrev=docbook

http://www.ebxml.org/

http://www.oasis-open.org/committees/tc_home.php?wg_abbrev=ebxml-cppa



http://www.oasis-open.org/committees/tc_home.php?wg_abbrev=ebxml-iic

http://www.oasis-open.org/committees/tc_home.php?wg_abbrev=ebxml-msg

http://www.oasis-open.org/committees/tc_home.php?wg_abbrev=regrep



ebXML RIM ebXML Registry Information Model, which provides information on the types of metadata stored in an ebXML Registry as well as the relationships among the various metadata classes

ebXML RS ebXML Registry Services Specification, which defines the interface to ebXML Registry Services and identifies message definitions and XML schema

ebXML TRP Transport, Routing and Packaging Specification, see ebXML Messaging EDI Electronic data interchange, electronic exchange of business information between

organizations in a structured format (X12). EML Election Markup Language, a specification for exchanging election and voter services

information using XML EPC Electronic Product Code, the data structure for serialisation enabling the identification of

individual products (RFID tags contain enough memory to carry EPC identifiers) Fragment Interchange An OASIS (SGML Open) resolution that defines a method of

exchanging portions of an SGML document HumanML Human Markup Language, a specification designed to represent human

characteristics through XML IETF Internet Engineering Task Force ITML Information Technology Markup Language, submitted to the OASIS Provisioning

Services Technical Committee for advancement as part of PSML J2EE-CA Java Connector Architecture, a standard architecture for integrating with diverse

enterprise systems, typically legacy. JMS Java Message Service, an API for accessing enterprise messaging systems from Java

programs. JSP Java Server Pages, a server-side executing page-based scripting language for outputting

browser-based presentation content. ONS Object Naming Service PML Physical Markup Language RELAX Regular Language description for XML, a language for validating XML documents

that was merged with TREX to create RELAX NG RELAX NG Regular Language Expression, a lightweight XML language validation

specification based on TREX and RELAX RMI Remote Method Invocation, a way for Java programs to invoke a remote procedure call. RosettaNet Defines a standard set of protocols and message formats for supply chain

integration, called Partner Interface Processes (PIPs). S2ML Security specification submitted to the OASIS Security Services Technical Committee

for advancement as part of SAML SAML Security Assertion Markup Language, an XML-based security specification for

exchanging authentication and authorization information SIMPLE SIP for Instant Messaging and Presence Leveraging Extensions, IETF standard

allowing any IP connected device to become registered SIP Session Initiation Protocol, IETF standard for establishing a live VoIP connection SOAP The Simple Object Access Protocol for invoking synchronous or asynchronous Web

Services. SPML Service Provisioning Markup Language, an XML-based framework specification for

exchanging user, resource, and service provisioning information TREX Tree Regular Expressions for XML, a language for validating XML documents that

was merged with RELAX to create RELAX NG UBL Universal Business Language, a standard library of XML business documents UDDI Universal Description, Discovery and Integration for discovering Web Services. VoIP Voice over IP WebCGM An application of the ISO-standard Computer Graphics Metafile for electronic

documents


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http://www.oasis-open.org/committees/tc_home.php?wg_abbrev=ebxml-msg

http://www.oasis-open.org/committees/tc_home.php?wg_abbrev=election

http://oasis-open.org/specs/fragmentinterchange.shtml

http://www.oasis-open.org/committees/tc_home.php?wg_abbrev=humanmarkup


http://www.oasis-open.org/committees/tc_home.php?wg_abbrev=relax-ng






http://www.oasis-open.org/committees/tc_home.php?wg_abbrev=ubl

http://www.cgmopen.org/



WML Wireless Markup Language, a language for indicating small-device content; WML2.0 is based on XHTML.

WSBPEL Web Services Business Process Execution Language, a submission by IBM, Microsoft and others to OASIS to standardize a notation for specifying business process behaviour based on Web Services.

WSCM Web Services Component Model for Interactive Applications, see WSIA WSDL The Web Services Description Language describes what a Web Service is capable of

and how a client invokes that service. WSIA Web Services for Interactive Applications, a coordinated set of XML vocabularies and

Web services interfaces that allow companies to deliver Web applications to end users through a variety of channels

WS-RM Web Services for Reliable Messaging, describes a protocol for reliable message delivery.

WS-RF a linking standard for Grid under Globus and Web Services bring software and hardware aspects together, includes sub standard WS-Eventing, to support real-time event driven activities

WSRP Web Services Standard for Remote Portals, an XML and Web services specification that will allow for the "plug-n-play" of visual, user-facing Web services with portals or other intermediary Web applications

WSUI Web Services User Interface, a specification for defining standard user interfaces for Web services, submitted to the OASIS WSIA Technical Committee

WSXL Web Services Experience Language, a Web services-centric component model, submitted by IBM to the OASIS WSIA Technical Committee for advancement as WSIA

XACML eXtensible Access Control Markup Language, an XML specification for expressing policies for information access over the Internet

xAL Extensible Address Language specification XCBF XML Common Biometric Format, an XML schema for describing information that

verifies identity based on human characteristics such as DNA, fingerprints, iris scans, and hand geometry.

xCBL XML component and business document library submitted to the OASIS UBL Technical Committee by Commerce One

xCIL Extensible Customer Information Language specification xCRL Extensible Customer Relationships Language Xforms are an XML-based language that represents the next generation of forms for the Web. XHTML is the reformulation of HTML 4 as an application of XML. XLIFF XML Localization Interchange File Format, an XML specification for multi-lingual

data exchange xNAL Extensible Name and Address Language specification xNL Extensible Name Language specification XML Extensible Markup Language, a metalanguage for creating other text-based markup

languages. XMLvoc Vocabulary for XML Standards and Technologies, a set of topic maps published

subjects defining the vocabulary of interchangeable ontologies for the XML domain XPath test XML Path Language test, an OASIS conformance suite for XSLT/XPath

processors Xquery XML Query Language. XRPM Extensible Resource Provisioning Management specification, submitted to the OASIS

Provisioning Services Technical Committee for advancement as part of PSML XML Stylesheet Language Transformation test, an OASIS conformance suite for XSLT/XPath

processors ZEROCONF IETF platform independent networking standard that allows the configuring of

IP addresses, router numbers and domain name addresses without user intervention


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http://www.oasis-open.org/committees/tc_home.php?wg_abbrev=wsia


http://www.oasis-open.org/committees/tc_home.php?wg_abbrev=wsrp



http://www.oasis-open.org/committees/tc_home.php?wg_abbrev=xacml


http://www.oasis-open.org/committees/tc_home.php?wg_abbrev=xcbf

http://www.oasis-open.org/committees/tc_home.php?wg_abbrev=ubl



http://www.oasis-open.org/committees/tc_home.php?wg_abbrev=xliff



http://www.oasis-open.org/committees/tc_home.php?wg_abbrev=xmlvoc

http://www.oasis-open.org/committees/tc_home.php?wg_abbrev=xslt


A POINT OF VIEW ON BUSINESS INTELLIGENCE & SERVICE ARCHITECTURES A White Paper on real time event driven Business Intelligence


34

Document Control

Version History

Version Date Comments

0.1 July 2004 Draft produced by Andy Mulholland

0.3 Aug 2004 Updates by Jon Gibbs

V1.0 Aug 2004 First release Document Distribution

Name

Location Responsibility Action / Information

Jon Gibbs

Derek Crates

Aston UK

Woking UK

Global Product Manager BI

Life Sciences SPOC to TS

review

review

Rob van de Star Utrecht NL TC head of sales inform Source File Location PC asset - directory - Word 6.0

Documents

A POINT OF VIEW ON BUSINESS INTELLIGENCE AND SERVICE ... · A POINT OF VIEW ON BUSINESS INTELLIGENCE & SERVICE ARCHITECTURES A White Paper on real time event driven Business Intelligence