Algorithms

Algorithms

   10:27 PM       Rizkooblogsite

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Algorithms are step-by-step processes that generate a solution to an AI problem.We will look at algorithms that generate routes through a game level to reach a goal, algorithms that work out which direction to move in to intercept a fleeing enemy, algorithms that learn what the player will do next, and many others.
  Data structures are the other side of the coin to algorithms. They hold data in such a way that an algorithm can rapidly manipulate it to reach a solution. Often, data structures need to be particularly tuned for one particular algorithm, and their execution speeds are intrinsically linked.
  You will need to know a set of elements to implement and tune an algorithm, and these are treated step by step in the text:

• The problem that the algorithm tries to solve
• A general description of how the solution works, including diagrams where they are needed
• A pseudo-code presentation of the algorithm
• An indication of the data structures required to support the algorithm, including pseudocode, where required
• Particular implementation nodes
• Analysis of the algorithm’s performance: its execution speed, memory footprint, and scalability
• Weaknesses in the approach

  Often, a set of algorithms is presented that gets increasingly more efficient. The simpler algorithms are presented to help you get a feeling for why the complex algorithms have their structure. The stepping-stones are described a little more sketchily than the full system.
  Some of the key algorithms in game AI have literally hundreds of variations. This article can’t hope to catalog and describe them all. When a key algorithm is described, we will often give a quick survey of the major variations in briefer terms.

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THE ARTIFICIAL INTELLIGENCE PERIODS

THE ARTIFICIAL INTELLIGENCE PERIODS

   9:52 PM       Rizkooblogsite

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The Early Days

The early days include the time before computers, where philosophy of mind occasionally made forays into AI with such questions as: “What produces thought?” “Could you give life to an inanimate object?” “What is the difference between a cadaver and the human it previously was?” Tangential to this was the popular taste in mechanical robots, particularly in Victorian Europe. By the turn of the century, mechanical models were created that displayed the kind of animated, animal-like behaviors that we now employ game artists to create in a modeling package.

  In the war effort of the 1940s, the need to break enemy codes and to perform the calculations required for atomic warfare motivated the development of the first programmable computers. Given that these machines were being used to perform calculations that would otherwise be done by a person, it was natural for programmers to be interested in AI. Several computing pioneers (such as Turing, vonNeumann, and Shannon) were also pioneers in early AI. Turing, in particular, has become an adopted father to the field, as a result of a philosophical paper he published in 1950 [Turing, 1950].

The Symbolic Era

From the late 1950s through to the early 1980s the main thrust of AI research was “symbolic” systems. A symbolic system is one in which the algorithm is divided into two components: a set of knowledge (represented as symbols such as words, numbers, sentences, or pictures) and a reasoning algorithm that manipulates those symbols to create new combinations of symbols that hopefully represent problem solutions or new knowledge.

  An expert system, one of the purest expressions of this approach, is the most famous AI technique. It has a large database of knowledge and applies rules to the knowledge to discover new things. Other symbolic approaches applicable to games include blackboard architectures, pathfinding, decision trees, state machines, and steering algorithms. All of these and many more are described in this article.

  A common feature of symbolic systems is a trade-off: when solving a problem the more knowledge you have, the less work you need to do in reasoning. Often, reasoning algorithms consist of searching: trying different possibilities to get the best result. This leads us to the golden rule of AI: search and knowledge are intrinsically linked. The more knowledge you have, the less searching for an answer you need; the more search you can do (i.e., the faster you can search), the less knowledge you need.

  It was suggested by researchers Newell and Simon in 1976 that this is the way all intelligent behavior arises. Unfortunately, despite its having several solid and important features, this theoryhas been largely discredited. Many people with a recent education in AI are not aware that, as an engineering trade-off, knowledge versus search is unavoidable. Recent work on the mathematics of problem solving has proved this theoretically [Wolpert andMacready, 1997], and AI engineers have always known it.

TheModern Era

Gradually through the 1980s and into the early 1990s, there was an increasing frustration with symbolic approaches. The frustration came from various directions. From an engineering point of view, the early successes on simple problems didn’t seem to scale to more difficult problems or handle the uncertainty and complexity of the real world. It seemed easy to develop AI that understood (or appeared to understand) simple sentences, but developing an understanding of a full human language seemed no nearer.

  There was also an influential philosophical argument made that symbolic approaches weren’t biologically plausible. The proponents argued that you can’t understand how a human being plans a route by using a symbolic route planning algorithm any more than you can understand how human muscles work by studying a forklift truck. The effect was a move toward natural computing: techniques inspired by biology or other natural systems. These techniques include neural networks, genetic algorithms, and simulated annealing. It is worth noting, however, that some of the techniques that became fashionable in the 1980s and 1990s were invented much earlier. Neural networks, for example, predate the symbolic era; they were first suggested in 1943 [McCulloch and Pitts, 1943]. Unfortunately, the objective performance of some of these techniques never matched the evangelising rhetoric of their most ardent proponents.

  Gradually, mainstream AI researchers realized that the key ingredient of this new approach was not so much the connection to the natural world, but the ability to handle uncertainity and the importance it placed on solving real-world problems. They understood that techniques such as neural networks could be explained mathematically in terms of a rigorous probablistic and statistical framework. Free from the necessity for any natural interpretation, the probablistic framework could be extended to found the core of modern statistical AI that includes Bayes nets, support-vector machines (SVMs), and Gaussian processes.

Engineering

The sea change in academic AI is more than a fashion preference. It has made AI a key technology that is relevant to solving real-world problems. Google’s search technology, for example, is underpinned by this new approach to AI. It is no coincidence that Peter Norvig is both Google’s Director of Research and the co-author (along with his former graduate advisor, professor Stuart Russell) of the canonical reference for modern academic AI [Russell and Norvig, 2002].

  Unfortunately, there was a tendency for a while to throw the baby out with the bath water and many people bought the hype that symbolic approaches were dead. The reality for the practical application of AI is that there is no free lunch, and subsequent work has shown that no singleapproach is better than any other. The only way any algorithm can outperformanother is to focus on a specific set of problems. The narrower the problem domain you focus on, the easier it will be for the algorithm to shine—which, in a roundabout way, brings us back to the golden rule of AI: search (trying possible solutions) is the other side of the coin to knowledge (knowledge about the problem is equivalent to narrowing the number of problems your approach is applicable to).

  There is now a concerted effort among some of the top statistical AI researchers to create a unified framework for symbolic and probabilistic computation. It is also important to realize that engineering applications of statistical computing always use symbolic technology. A voice recognition program, for example, converts the input signals using known formulae into a format where the neural network can decode it. The results are then fed through a series of symbolic algorithms that look at words froma dictionary and the way words are combined in the language.

  A stochastic algorithm optimizing the order of a production line will have the rules about production encoded into its structure, so it can’t possibly suggest an illegal timetable: the knowledge is used to reduce the amount of search required.

  We’ll look at several statistical computing techniques in this book, useful for specific problems. We have enough experience to know that for games they are often unnecessary: the same effect can often be achieved better, faster, and with more control using a simpler approach. Although it’s changing, overwhelmingly the AI used in games is still symbolic technology.

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What Is AI?

What Is AI?

   9:40 PM       Rizkooblogsite

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Artificial intelligence is about making computers able to perform the thinking tasks that humans and animals are capable of.

  We can already program computers to have superhuman abilities in solving many problems: arithmetic, sorting, searching, and so on. We can even get computers to play some board games better than any human being (Reversi or Connect 4, for example). Many of these problems were originally considered AI problems, but as they have been solved inmore and more comprehensive ways, they have slipped out of the domain of AI developers.

  But there are many things that computers aren’t good at which we find trivial: recognizing familiar faces, speaking our own language, deciding what to do next, and being creative. These are the domain of AI: trying to work out what kinds of algorithms are needed to display these properties.

In academia, some AI researchers are motivated by philosophy: understanding the nature of thought and the nature of intelligence and building software to model how thinking might work. Some are motivated by psychology: understanding the mechanics of the human brain and mental processes. Others are motivated by engineering: building algorithms to perform humanlike tasks. This threefold distinction is at the heart of academic AI, and the different mind-sets are responsible for different subfields of the subject.

  As games developers, we are primarily interested in only the engineering side: building algorithms that make game characters appear human or animal-like. Developers have always drawn from academic research, where that research helps them get the job done.

  It is worth taking a quick overview of the AI work done in academia to get a sense of what exists in the subject and what might be worth plagiarizing.We don’t have the room (or the interest and patience) to give a complete walk-through of academic AI, but it will be helpful to look at what kinds of techniques end up in games.

  You can, by and large, divide academic AI into three periods: the early days, the symbolic era, and
the modern era. This is a gross oversimplification, of course, and the three overlap to some extent,
but we find it a useful distinction.

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WHAT IS INTELLIGENCE?

WHAT IS INTELLIGENCE?

   9:28 PM       Rizkooblogsite

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The word intelligence is fairly nebulous. The dictionary will tell you it is the capacity to acquire and apply knowledge, but this is far too general. This definition, interpreted literally, could mean that your thermostat is intelligent. It acquires the knowledge that the room is too cold and applies what it learned by turning on the

heater. The dictionary goes on to suggest that intelligence demonstrates the faculty of thought and reason. Although this is a little better (and more limiting; the thermostat has been left behind), it really just expands our definition problem by introducing two even more unclear terms, thought and reason. In fact, the feat of providing a true definition of intelligence is an old and harried debate that is far beyond the scope of this text. Thankfully, making good games does not require this definition.

   Actually, this text will agree with our first dictionary definition, as it fits nicely with what we expect game systems to exhibit to be considered intelligent. For our purposes, an intelligent game agent is one that acquires knowledge about the world, and then acts on that knowledge. This is not to say that our notion of intelligence is completely reactive, since the “action” we might take is to build a complex plan for solving the game scenario. The quality and effectiveness of these actions then become a question of game balance and design.

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PROCESS IMPROVEMENT TOOLS AND METHODOLOGIES

PROCESS IMPROVEMENT TOOLS AND METHODOLOGIES

   2:03 PM       Rizkooblogsite

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Process modeling tools can range from simple flowcharting tools to very sophisticated modeling tools with repositories of process models or simulation capability. At the very basic end of the spectrum, sticky notes and flip charts are great tools to use while documenting or designing processes.

  Simple flowcharting or drawing tools, such as Visio by Shapeware Corporation, Micrografx’s ABC Snapgraphics and ABC Flowcharter, and Process Charter by Scitor Corporation are examples of products that can help. Process mapping software provides more assistance in reengineering, with tools such as BPWin by Logic Works and Plexus by The Jonathon Corporation. There are also process mapping products that support the IDEF Integrated computer-aided Definition) process mapping methodology, such as AI0 and AI4 by Knowledge Based Systems, Meta Software’s Design/IDEF, Texas Instruments’ BDF, Wizdom Systems’ IDEFine, and AutoSADT by Triune Software. Process simulation software tools, such as Optima by AdvanEdge Technologies, ITHINK by Performance Systems, ProTEM by Software Consultants International, Application Development Consultants ProcessSimulator, and AT&T ISTEL Witness, allow one to analyze the impact of process improvements before implementation. Some of the tools available are shown in Figure 1.7 (although software products and companies change on a continual basis).

  Process modeling tools have improved over the past few years in both functionality and ease of use. Most process modeling tools generate

workable models, identify tasks within a process, show who performs the tasks, guide task performance, prioritize processes, and outline back-up plans for the process. The tools are typically Internet enabled, allowing browser users to easily view the next steps as well as entire processes. Some tools also provide reference business models of the leading Enterprise Requirements Planning software packages for specific industries, provide a gap analysis between a specific process and the industry process, and do multidimensional analysis. Although it may be helpful, it is not required to have sophisticated and expensive tools before embarking on a process improvement effort. Sometimes it can be helpful to tackle the first few process improvement efforts using more simple tools (such as Visio) to concentrate on the process improvement steps and determine the true requirements of an automated tool.

  In addition to charting tools, there are many different methodologies. Methodologies can be intimidating. Some are clear and specific; many are vague and complex. At its core, a methodology guides you down the path of practical improvement with a step-by-step approach. It provides a framework to make decisions, take action, and move forward. Figure 1.8 identifies some of the methodologies associated with information systems processes. This figure shows a variety of methodologies, some are for improving a few specific process areas, while some are general standards or guidelines.

  This article is written to present a practical step-by-step methodology, not to explore each of the published methodologies listed. Being aware of these options simply informs one of other existing methodologies that may work in an organization. Many companies spend years developing internal experts and changing their practices

to align with an improvement methodology. In today’s fast paced information systems world, years are not available to implement these changes. The methodology to use is a personal choice. The reason for choosing a methodology is to provide the framework to make decisions, take action, and improve. The methodology is only the means to an end, not the end itself. Do not spend an enormous effort laboring over a particular methodology, rather apply that energy toward the improvements. Whatever is done must be done quickly. Develop an approach, deploy it within the organization, and demonstrate results.

  One way to evaluate methodologies is to think about the methodology in terms of approach, deployment, and results, as shown in Figure 1.9.

This model was created through The Malcolm Baldrige Criteria for Performance Excellence and is used to guage the effectiveness of an organization.

  Thinking about an improvement methodology in this manner will provide the framework to make decisions, take action, and improve.

• Approach. Every methodology represents an approach to improving the operation. In essence it is what you decide to do. For example, using a web-based ticketing system to manage computer support activities is one approach. How effective an approach it may be depends on many factors, such as:
•   Is it unique and innovative?
•   Is it systematic?
•   Is it integrated?
•   Is it prevention based?
•   Does it involve improvement cycles?

Is it based on quantitative information that is objective and reliable? The more complete the answers to these questions, the more solid the approach and methodology for selecting processes for improvements. An example of approach is shown in Figure 1.10.

• Deployment. No matter how solid the approach is, without effective deployment it is worthless. Deployment refers to the extent to which the approach is applied to all relevant areas of the organization. In essence it deals with how much is done, in both organizational depth and breadth. For example, if “all computer users feed ticket requests for all software through the web directly to each computer support technician,” how good the deployment is depends on four encompassing questions:
•   Does the implementation apply to all work units?
•   Does the implementation touch all relevant people in each work unit?
•   Does the implementation impact all transactions, occurrences, or interactions?
•   Does the implementation happen to the full extent?

Again, the more complete the answers are to these questions, the more solid the deployment of the methodology. An example of deployment is shown in Figure 1.11.

• Results. Once an approach is deployed, the next step is to review the results. Results demonstrate the outcome from an approach that was effectively deployed. In essence it deals with how well you did what you set out to do. For example, 73 percent of ticket requests are communicated and resolved within 12 hours. How good the results are depends upon three encompassing questions:
•  What is the quality and performance level that is being achieved?
•   Are there sustained improvement trends?
•   Are there comparisons with similar providers and world leaders?

An example of results is shown in Figure 1.12.

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BARRIERS TO CHANGE

BARRIERS TO CHANGE

   1:31 PM       Rizkooblogsite

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So, why has it taken so long for Information Systems to embrace process improvement methodologies when they have been practiced for many years within other areas of the business? Why aren't more companies in the world-class category of evolution? Why may some individuals within Information Systems not initially support the improvement efforts? What are the barriers to change from the old way of doing things? In many areas of the business, processes are repetitive and produce a tangible or deliverable product. Information Systems is about technology and information. It is more of a job-shop environment, as no two projects or problems are really alike. Processes are more difficult to identify, document, and automate in a variable environment. However, when complex problems are broken down into simple steps, commonality can be found.

   Information Systems is also a relatively newer discipline than manufacturing and other service areas. There is less structure and organization, and fewer standards have been developed in the information systems industry as a whole compared with other industries. However, there are a growing number of resources available that were not available several years ago. This article is one of those resources.

  Typically, Information Systems organizations have a tremendous backlog of requests. In an environment that feels as if one is continually behind, chaotic or firefighting, and continuously pushed to provide more, it is often difficult to take a step back and take the time to improve the tools and processes. Although the job of Information Systems is to improve the tools and processes for others, we are often the last ones to improve our own processes and tools. To get past this barrier, it is critical to step out of the firefighting circular chaos and improve the tools and processes to become more efficient and effective. It is always amazing to see how many Information Systems organizations do not have the time to do a task right, but always have the time to do it over again. If time is spent today preventing tomorrow’s problems, less time will need to be spent tomorrow fixing the errors of today!

  Some individuals in Information Systems may resist a structured process environment because they claim it will limit their creativity and confine them to a rigid process. Actually, the structured process allows them to more effectively use their creativity in developing solutions for the customer rather than continually fighting the same fires over and over again.

  Although it has changed significantly in recent years, in the past, Information Systems was viewed by many organizations as simply an overhead function rather than one adding true value to the business. As an overhead function, budgets were often constrained to the bare minimum. With tight resources, it was difficult to invest resources in improving processes. However, more companies are viewing information systems as a strategic part of the business. Information Systems’ budgets continue to climb. Once the initial investment has been made, improved processes will save money.

  Many individuals in Information Systems work very hard, but fail to take the viewpoint of their customer. When information systems individuals are asked during an assessment to rate their performance, efficiency,  and support, they typically rate themselves relatively high. When the users are also asked to rate the performance of the Information Systems organization, many times their ratings are significantly lower. It is important to realize, when asking a customer or user about the support provided by Information Systems, perception is reality. The Information Systems organization must realize that, although they may be working very hard, the level of service they provide the customer may be totally unacceptable. By focusing on process improvement, IS can establish a common understanding of quality with the customer, measure quality, and celebrate success while moving toward the targets.

  Change is always difficult and can be resisted by some individuals. The old ways of doing things become entrenched in the organization, and it may be difficult to see new ways. Chapter 10 outlines in more detail barriers to change and how to help the organization accept change.

  How is it possible to get over the barriers to change and move the Information Systems organization through the evolution to become a world-class operation? This book will outline a step-by-step methodology to guide the process improvement effort.

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PROCESSES EVOLUTION

PROCESSES EVOLUTION

   11:11 AM       Rizkooblogsite

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How do information systems processes evolve? Developing an Information Systems organization to become a world-class organization is an evolution. A culture of continuous improvement must be instilled in the organization. This change, or evolution, does not happen overnight; it takes work, education, and commitment to excellence. For a change to occur, the reward must be greater than the sum of the current pain plus the pain of the change. That is, the organization must truly want to change to begin the process evolution.

There are five basic stages an organization goes through to evolve into a world-class organization. The stages described in Figure 1.6 are similar to the five levels of maturity that were developed in 1991 with the U.S. Department of Defense by the Software Engineering Institute at Carnegie Mellon University. That model, the Capability Maturity Model for improving the software development process, as well as the model discussed here, maps an evolutionary path from ad hoc, chaotic processes to mature, disciplined, and efficient processes. Looking at process improvement as a continuum allows companies to take steps toward an improved environment rather than attempt to get there in one move. This breaks the complexity of the process improvement into manageable stages, maps the opportunities for improvement, and recognizes the value of evolution. The stages of process evolution are described in more detail below. Firefighting An organization in this stage may be in the firefighting, reactive, or chaotic mode. Each crisis or issue is handled independently, depending upon the skill set of the individual handling the crisis. Success depends on heroes. For example, when one user calls the Help Desk person with an issue, it may get handled totally differently than when another user calls another Help Desk individual with the exact same issue. There are no processes or procedures documented and formalized. There is no commonality across information systems. Projects and support are handled inconsistently. There are few metrics measured and reported. Schedules and cost targets are rarely met, or are met with very unpredictable results. Commitments are made without any process or detail to ensure they can be met. Furthermore, projects are not managed to meet the commitments. In this environment, some individuals may even feel that defined processes stifle creativity and, therefore, process definition is resisted. Another common comment by staff is that they do not have time to implement a more structured approach. Most often this is true, because they are continually in crisis mode. In 1998, the META Group estimated 50 percent of organizations to be in this mode of operation.

Desire 

An organization in this stage wants to implement procedures and processes to obtain a more structured approach. Although they are still skills-based, some metrics and procedures may begin to be developed. Some of the individual and heroic efforts may be organized so that they can be repeated. Initial process training may have been conducted, but the concepts are not used extensively. Individuals have heard process concepts and engineering techniques enough to say, “Sure, we do that.” Although some project management concepts may be followed, in a crisis, the individuals revert to the firefighting mode of operation. A systems development methodology may have been selected but not fully or consistently implemented. Processes that may receive focus in this stage are those that establish basic information systems controls, such as: 

• Schedule Management
• Security Management
• Financial Management
• Vendor Management
• Facilities Management

An estimated 35 percent of Information Systems organizations are in this stage of evolution (META, 1998).

Beginning

In this phase, standard processes are defined, documented, and followed. The organization understands the process, how it works, and what its individual role is in the process. A process management group is established to manage improvements. Process training and communication occurs regularly. This organization may be both process- and skills-based in different areas of the Information Systems organization. Although some areas of the Information Systems organization may have fully implemented process methodology and have documented procedures that are consistently followed, not all areas of the organization may be integrated into the processes. There may be pockets or islands of automation for various steps of a process. There may be many metrics that are measured and reported on a regular basis. Successful processes are repeatable. Reasonable commitments are planned. Schedules, cost, and functionality targets are met on a regular basis. Processes that may receive attention in this phase are those that address both system and organization issues as the organization establishes an infrastructure. These are processes that institutionalize effective practices and management of processes across the function, such as:

• Backup and Disaster Recovery Management
• Problem Management
• Understand Requirements
• Design Solutions
• Construct and Integrate Solutions
• Test Solutions
• Customer Acceptance

An estimated 10 percent of Information Systems organizations is in this stage (META, 1998).

Proactive:

In this stage, processes are the natural way. Metrics are collected and used to identify and handle process variation in all areas of the Information Systems organization. Quality targets are established. Targets for cost and time are predictable and reliable. Procedures and processes are well documented and followed with rigor, even in a crunch, in all areas of the Information Systems organization. All individuals in the Information Systems organization have an understanding of all the processes. Processes are integrated across various Information Systems organizations (such as technical support and desktop and business applications). Issues are handled consistently and predictably each time they occur. Automation has been implemented and integrated across all the processes and areas of the organization. Process improvement is a regular part of everyone’s job and is reflected as part of job descriptions and performance appraisals. Processes that may receive attention during this phase are those that focus on establishing a quantitative understanding of both the systems and the activities being performed, such as:

• Performance and Availability Management
• Capacity and Storage Management
• Change Management
• Installation and Configuration Management
• Inventory and Asset Management
• Software Distribution Management

Fewer than 5 percent of Information Systems organizations are estimated to be in this stage of development (META, 1998).

World Class:

All customer needs are met with quality systems and solutions on a consistent basis. Benchmarking is done regularly to continually improve processes and metrics. The organization is fully process-based, with all procedures and processes well documented and understood. Processes are designed for maximum efficiency and effectiveness. A balanced scorecard may have been developed, with metrics posted regularly and all members striving for improvement. Processes are fully integrated and fully automated. Users understand and participate eagerly in the processes. Causes of poor performance are eliminated. New technology and process improvements are prototyped, piloted, and added to the process on a regular basis. Processes that may receive attention in this phase are those that cover the issues related to continual, measurable process improvement, such as:

• Service Level Management
• Information Systems Strategic Planning
• Market Information Systems Offerings
• Customer Satisfaction Management
• Human Resource Management

Fewer than 1 percent of Information Systems organizations are estimated to be in this stage (META, 1998).

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MARKET DRIVERS

MARKET DRIVERS

   10:04 AM       Rizkooblogsite

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Why is information systems process management important now? What are the market drivers? The META Group (a research company) identified process improvement as a key trend in its 1999 trends for IT Performance Engineering and Measurement Strategies. Specifically, META predicted that in 1999 and 2000, software process improvement and quality programs would continue to stagnate, enabling only micro-level progress on It productivity and quality. However, by 2001 and 2002, they predicted that It will focus on performance engineering as the preferred approach for achieving performance improvements, and by 2002 and 2003, performance engineering approaches will improve productivity and quality to new levels. There are many forces creating this need for process improvement within Information Systems.

• Electronic commerce, e-business, and the Internet. As companies leverage the use of Intranets and Extranets, there will be an additional need for Information Systems to understand and link
  
  with the processes of other departments within the company. With the advent of e-business and technology our information systems processes are moving closer to and impacting the end customer. In the past, business processes could mask the inadequacies of our information systems processes. For example, if the system was down when a customer called to place an order, the customer service representative could take the information down on paper and call the customer back with a delivery date. Likewise, if the system was not developed properly to fit the business needs, the customer service agent could translate as information was input into the system. With customers placing orders directly into corporate systems, as is done with e-business, any outage in the system or inaccurate design can directly affect the customer. Technology is becoming an integral part of day-to-day business and impacting the success of the business.

• Performance demands. Today, executives are sensitive to total cost of ownership, poor and lengthy application development, and performance issues with systems. Executives are demanding that Information Systems improve their methods and increase overall efficiency and effectiveness of the organization by implementing best practices. There is pressure to do more with less, reduce operating costs, and increase end customer satisfaction. As technology progresses in an organization, users of the technology are becoming more engaged, informed, and demanding. Processes such as Problem Management, Inventory and Asset Management, Change Management, and Understand Requirements are just a few of the processes that may not be well understood or documented within an Information Systems organization.
• Changing technology. The identification and implementation of new information technologies can be an outcome of successful process management. Today, there is an abundance of tools and technologies available on the market to assist in automating information systems processes, such as Help Desk call management software, change management software, and systems management software. These tools can be costly and take time to implement. Many companies have tried to implement the tools and have failed because they applied the technology without understanding and reengineering the process using the technology.
• Reliability demands: Companies today are using technology to provide them with a competitive advantage and market dominance. Growing numbers of companies are implementing technology tightly linked with core business processes. These critical systems must provide guaranteed round-the-clock reliability and scalability (ability to grow with the company to support the business operations). As the core applications become the very livelihood of the business, there is no tolerance for application down time. Internet companies are a prime example of this. Just a few hours of system down time can cause millions of dollars of lost revenue and influence the price of the stock and earnings per share. Fundamental information systems processes such as Availability Management, Capacity Management, Change Control, and Problem Management must be functioning properly to ensure consistent, reliable service and deliver high levels of application availability.
• Interdependence. Business solutions today are dependent on many different pieces that must function together. In the early years, with a mainframe and terminal, troubleshooting was less complex. Today, with client/server solutions, the problem may be on the PC, network, server, main server, database, router, or any number of other areas. As a user, there is nothing more frustrating than being in an organization that reports 99.9 percent availability of their system and yet constantly experiences system down time. To a user, the system is unavailable, whether it is a desktop application or a network issue. Information systems processes and metrics must operate end to end and across organizational boundaries to be effective.
• Enterprise Requirements Planning (ERP). Many companies recently invested significantly in new ERP systems to solve their year 2000 issues. Companies that have experienced the pain and expense of these implementations will be looking at process improvements as a means of finding additional value for their investment.
• Outsourcing. Although the outsourcing movement has made many Information Systems organizations nervous, it is, in fact, an admission by company personnel (usually out of frustration) that they cannot internally produce quality information systems services efficiently and effectively. They turn to outsourcing as a possible answer and catalyst for change to improve the efficiency (or cost, typically) and effectiveness. The outsourcing pronouncements by many organizations are wake-up calls to Information Systems organizations that they must start improving their services or their very survival can be threatened. It is sad to see organizations resort to outsourcing as their only alternative, as information systems can be a competitive advantage if functioning properly. Even if an organization must turn to outsourcing, it is much easier (and less expensive) to outsource a process-based organization.
• Globalization. In order to be competitive, companies are finding they must stretch their business across the globe. E-business is also forcing this worldwide movement, because there are no boundaries in cyberspace. Processes must cross over continents and be transparent to the customer, no matter where they are physically in the world.
• Regulatory requirements. ISO 9000 audits that focus on defined procedures and processes now include the scope of Information Systems. For many Information Systems organizations, processes and procedures are a new concept, because they may be in a firefighting survival mode. When the internal ISO auditors turn to Information Systems, they often find a tremendous lack of documentation and defined processes.
• Labor issues. The short supply of information systems professionals has raised labor costs and requires companies to be more effective in using these costly resources. In the study by Jones, chairman of Software Productivity Research., Inc., in Burlington, Massachusetts, 60 percent of the U.S. software workforce is engaged in fixing errors that would be avoidable if total quality management practices were implemented. If that number is accurate, quality software development processes could lead to a surplus of more than one million personnel, rather than the huge shortage of personnel claimed throughout the industry. In other words, valuable resources are being mismanaged. A process methodology and proper documentation are also methods for companies to sustain through many cycles of information systems staff turnover. Process documentation can also ensure that resources are used efficiently so an expensive technical resource is not doing a function that could be performed by someone else (for example, a database administrator standing in line at the copy machine).
  
• End of Year 2000: With the year 2000 issue resolved, companies will have to begin defining new initiatives that require improved processes. Many companies will also be reducing information systems costs and will need to focus internally to improve their overall efficiency and effectiveness. As shown in Figure 1.5, there are numerous market drivers encouraging or even dictating improved information systems processes. As global competition increases and technology becomes more critical in business, efficient and effective information systems processes are no longer a competitive advantage, but a fundamental necessity to sustain business and promote growth.

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BENEFITS OF PROCESS MANAGEMENT

BENEFITS OF PROCESS MANAGEMENT

   9:51 AM       Rizkooblogsite

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Why is information systems process management important? What are the benefits? There are many benefits of implementing process improvement, such as:

• Processes strengthen business partnership and improve customer service. Improving information systems processes can result in a significant improvement of customer (or user) satisfaction, which in turn improves the relationship between the business and Information Systems. In this environment, Information Systems will be aligned with what is important to the business, and the priorities will be reflected in the day-to-day operations. The implementation of a quality initiative, or TQM, in the Information Systems organization can increase the value-added contribution to the organization. The Information Systems leader who speaks and embraces quality concepts can build bridges to other areas of the organization that have been using these techniques for years. Top management confidence in Information Systems will improve as the organization measures and improves the value it adds to the company.
• Processes improve efficiency and communication. Documented processes will clearly define roles and responsibilities of project team members. Knowing their job responsibilities and expectations will allow them to be more effective. Communication will be improved as responsibilities and expectations are clear and understood by everyone involved.
• Processes improve productivity of the Information Systems organization. For years, many businesses claimed that their Information Systems organizations were not responsive enough to changing business needs as they watched their backlog continue to grow. There are many examples of failed projects in the industry. Many executives allege they spend too much money and time on projects that never meet business expectations. Information Systems is continually asked to do more with less. We all have limited budgets, limited headcount, and limited hours in a day. Rather than working harder, we need to find ways to work more productively. Process improvement can significantly improve and sustain new levels of performance and productivity.
• Processes improve effectiveness of project management. Improved processes will assist Information Systems in consistently meeting commitments through better planning, estimating, costing, tracking, and reporting of project progress. Statistics from the Standish Group that studied 23,000 projects in companies of all sizes showed that in 1998 only 26 percent of projects were successful. They defined successful as completed on time, on budget, with the promised functionality. 46 percent of the remaining projects were challenged and 28 percent cancelled. As an industry, Information Systems professionals must improve the success rate of project development and project management. Becoming a process-based organization is one condition for consistently delivering successful projects.
• Processes reduce defects and improve quality. Having a consistent and reliable process with metrics will provide the vehicle to improve and to increase the quality of service provided. Typically, the root cause of failure or defects is due to process and organizational failure, not failure of people.
• Processes help avoid bad publicity. Today, system failures and system quality issues are highly publicized events that can impact the financial performance of a company. A 1996 survey of 240 Fortune 1,000 companies in North America and Europe was commissioned by CenterLine Software, Inc., a company in Cambridge, Massachusetts that developed a software testing tool. The survey found that 12 percent of the companies contacted had faced liability or litigation issues with regard to direct or consequential damages from lack of software quality. With the movement toward ebusiness and putting software even closer to the customer, we can expect this number to increase in the future. Although process improvement cannot guarantee the elimination of events that could cause bad publicity, improved quality of products and services would reduce the likelihood of such issues.
• Processes improve consistency. Although the heroes of the Information Systems organization may produce high-quality results quickly, the entire organization may have difficulty producing heroic results consistently. Improving processes ensures a consistent level of quality and timeliness of service and support throughout the organization.
• Processes increase return on investment. Jim Stikeleather in Insane Expectations (Computerworld Client/Server Journal, November 1995) claims a $5 return for every dollar invested in process improvement. Companies are continually looking into all areas to increase the return on investment. Since many companies still view Information Systems as an expense rather than a competitive asset, they often look at Information Systems to cut expenses and obtain more for each dollar invested. They focus on how to reduce the unit cost of Information Systems. Companies may be willing to spend more money on Information Systems if they are getting a larger return on their investments.
• Processes provide the company with a competitive advantage. Faced with increased competition, companies are asking how they can utilize technology to provide their company with a competitive advantage in the marketplace. Particularly as companies are migrating to e-business, information systems processes must change significantly to handle the increased demands. Increased speed, flexibility, and quality in all processes are becoming an expectation as technology evolves toward e-business.
• Processes leverage best practices and solutions. By establishing and managing proven, repeatable processes, knowledge can be leveraged so that every project gains from previous project experience.
• Processes reduce the impact of turnover. Turnover is high in Information Systems organizations. Employees gain a specific set of knowledge and skills, but that knowledge is in only one person rather than a companywide asset. As employees leave the company, they take their knowledge, skills, and training with them. Best practices and process management turns that expertise into repeatable processes or knowledge that can be used continually within an organization.
• Processes improve business productivity and revenue. As businesses have tightly integrated technology into their business processes, the business can be significantly impacted by the performance of the Information Systems group. If the system is down or a user is waiting for the Help Desk to fix a problem, that user’s productivity is impacted. The end customer may also be impacted, as the employee may not be able to properly assist the customer without the system and tools. As a customer, there is nothing more frustrating than calling a company with an order and having the service agent reply that they are unable to assist at that time because the computer is down. In addition to affecting customer satisfaction, it could also impact customer loyalty and market share. Customers unable to wait for technical issues to be resolved will gravitate to another supplier to fill their needs more rapidly.
• Processes improve business quality. Since information is often tightly integrated with how the organization does business with its customers, it is difficult for a company to implement a total quality methodology without including the Information Systems organization. For example, a company may have successfully implemented quality concepts in parts of the organization, but not on a companywide basis. If a customer calls to find the status of an order, the process to provide that information to the customer may be very efficient and effective. However, the customer service representative may provide the customer with inaccurate information because of errors in the systems development process used by Information Systems. In fact, there is often a direct relationship between the quality of systems and the quality of goods and services that a company provides.
• Processes prepare for future growth and flexibility. Without processes in place, as an organization grows there will be a need to increase the number of employees to provide the same level of support. With established processes, productivity is significantly improved and the functions will be organized to handle growth with a minimal increase in employees. Although money may still need to be spent to handle growth, the spending would not be linear.
• Processes create a culture of empowered and satisfied employees. No one enjoys being part of an organization that has a bad reputation or is not meeting expectations. Clear processes and responsibilities enable employees to meet expectations, resulting in increased job satisfaction. The employees will also feel empowered to make changes and resolve issues. With metrics and measures that they can impact, employees aspire for excellence. Information Systems personnel feel valued, understand the expectations, and feel competent to perform their job.

As can be seen in Figure 1.3, the benefits of information systems process improvement outlined above can be realized for the business itself as well as the Information Systems organization. In fact, many of these benefits are cited as goals when companies begin their process improvement efforts. A research study was done by Gartner Group in 1997 of more than 200 Information Systems departments

on the benefits of process improvement projects. Figure 1.4 identifies the primary goal reported by these companies beginning process improvement projects.

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PROCESS MANAGEMENT

PROCESS MANAGEMENT

   9:35 AM       Rizkooblogsite

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What is process management? Process management is the method used to implement and continuously improve how products or services are delivered. The function is performed at a predictable level of service, support, time, and cost. Process management organizes a group of functional activities into steps that are measurable, repeatable, and reliable. A process management mentality is a fundamental change or transcendence from the firefighting mode found in many Information Systems organizations.

  The principles of process management and Total Quality Management (TQM) are shown in Figure 1.1 and include:

• Continuous improvement. Continuously improve the goods and services produced by the Information Systems organization; continuously expand and grow to create a new future. This is a continuous process as new technologies and approaches become available.
• Management commitment. Top management must be committed to the improvement of processes. According to Dr. W. Edwards Deming, 85 percent of quality problems lie within management control. Management must change the culture of the organization and create an environment where continuous improvement can 
  
  flourish. Management must also continually communicate theircommitment, support, and interest. 
• Customer focus. Keep a customer focus at all times. Information Systems customers could be the internal customer or even the external customer. See the process through the eyes of the customer, not from the vantagepoint of Information Systems. The Internet and movement toward e-business are bringing information systems closer to the external customer. The objective is to establish a common definition of quality with the customer (either internal or external). Many different aspects and interfaces that the customer may have with Information Systems influence value and satisfaction. Some of the aspects a customer may consider when judging the quality of Information Systems include:

1. Time to get a request completed
2. Time to resolve a Help Desk call
3. System availability and up-time
4. System response time
5. Friendliness of personnel
6. Knowledge of personnel
7. Quality of the new system developed
8. Accuracy of the information the systems produce
9. Ability to utilize technology for a competitive advantage

• Right work, right first time. The goal for all activities is to do the right work and to do the work right the first time. Doing the right things includes obtaining the customers’ true requirements. Doing the work right the first time includes both efficiency (little waste) and effectiveness (producing the desired results which include meeting or exceeding customer expectations).
• Error prevention. Errors can actually be prevented. Error-free work is always organized and planned with every activity, as it is always cheaper to do it right the first time. Rather than rewarding the heroic firefighter, reward those who actually prevent the fires from beginning in the first place. Ensure that processes have the necessary checks and balances to prevent errors. Anticipate that errors are going to happen before they actually happen. Analyze how you might be contributing to your own problems.
• Metrics. Processes and performance results are measured with specific metrics and targets. Positive trends exist for all measures.
• Corrective action. Problem solving is begun and corrective action is taken. The root cause of problems is determined, rather than just fixing the symptoms. When errors occur, rather than determining who made the error, the focus is on the problem correction and how the issue can be prevented in the future.
• Teamwork. Full teamwork is required to achieve improvements. Employee involvement, group brainstorming, and team efforts are common practices.

Process improvement includes technical aspects such as the tools, techniques, methodologies, and training. However, the behavioral aspects of process improvement must also be considered. These aspects include organizational issues, job responsibility changes, performance rewards, and culture as shown in Figure 1.2. Implementing a process mentality is a culture change for most Information Systems organizations. When working on processes, focus on both behavioral aspects and technical aspects.

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