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A Simple Evolutionary Project Management Method Tag: Quantified Simple Evo Project. Version: July 8, 2003. Owner: Tom@Gilb.com. Status: Draft. Project Process Description 1. Gather from all the key stakeholders the top few (5 to 20) most critical performance goals (including qualities and savings) that the project needs to deliver. Give each goal a reference name (a tag). 2. For each goal, define a scale of measure and a ‘final target’ goal level. For example, Reliability: Scale: Mean Time Between Failure, Goal: >1 month. 3. Define approximately 4 budgets for your most limited resources (for example, time, people, money, and equipment). 4. Write up these plans for the goals and budgets (Try to ensure this is kept to only one page). 5. Negotiate with the key stakeholders to formally agree these goals and budgets. 6. Plan to deliver some benefit (that is, progress towards the goals) in weekly (or shorter) cycles (Evo steps). 7. Implement the project in Evo steps. Report to project sponsors after each Evo step (weekly, or shorter) with your best available estimates or measures, for each performance goal and each resource budget. - On a single page, summarize the progress to date towards achieving the goals and the costs incurred. - Based on numeric feedback, and stakeholder feedback; change whatever needs to be changed to reach the goals within the budgets. 8. When all goals are reached: “Claim success and move on” (Gerstner 2002). Free the remaining resources for more profitable ventures Project Policy 1. The project manager, and the project, will be judged exclusively on the relationship of progress towards achieving the goals versus the amounts of the budgets used. The project team will do anything legal and ethical to deliver the goal levels within the budgets. 2. The team will be paid and rewarded for ‘benefits delivered’ in relation to cost. 3. The team will find their own work process, and their own design. 4. As experience dictates, the team will be free to suggest to the project sponsors (stakeholders) adjustments to the goals and budgets to ‘more realistic levels.’ EVOLUTIONARY PROJECT MANAGEMENT 25 This simple project process and policy capture all the key features: you need read no more! However, in case any reader would like more detail, I will comment on the process and policy definition, statement by statement, in the reminder of this paper! 3 PROJECT PROCESS DESCRIPTION 1. Gather from all the key stakeholders the top few (5 to 20) most critical goals that the project needs to deliver. Projects need to learn to focus on all the stakeholders that arguably can affect the success or failure. The needs of all these stakeholders must be determined – by any useful methods – and converted into project requirements. By contrast, the typical agile model focuses on a user/customer ‘in the next room’. Good enough if they were the only stakeholder, but disastrous for most real projects, where the critical stakeholders are more varied in type and number. Agile processes, due to this dangerously narrow requirements focus, risk outright failure, even if the ‘customer’ gets all their needs fulfilled. 2. For each goal, define a scale of measure and a ‘final target’ goal level. For example, Reliability: Scale: Mean Time Before Failure, Goal: >1 month. Using Evo, a project is initially defined in terms of clearly stated, quantified, critical objectives. Agile methods do not have any such quantification concept. The problem is that vague targets with no quantification and lacking in deadlines do not count as true goals: they are not measurable, and not testable ideas. Note in Evo, the requirements are not cast in concrete, even though they are extremely specific. During a project, the requirements can be changed, and tuned, based on practical experience, insights gained, external pressures, and feedback from each Evo step (See also point 4 under ‘Project Policy’). 3. Define approximately 4 budgets for your most limited resources (for example, time, people, money, and equipment). Conventional methods do set financial and staffing budgets, but usually at too macro a level. They do not seem to directly, and in detail, manage the array of limited resources we have. Admittedly there are some such mechanisms in place in agile methods, such as the incremental weekly (or so) development cycle (which handles time). However,
26 ENTERPRISE INFORMATION SYSTEMS VI Back Room Front Room 2 QuickTime and a Graphics decompressor are needed to see this picture. Back-room Design Developme 123456789n Front-room Evo \the Evo method sets an explicit numeric budget for any useful set of limited resources. WHICH IS WHAT? 4. Write up these plans for the goals and budgets (Ensure this is kept to only one page). All the key quantified performance targets and resource budgets, should be presented simultaneously on a single overview page. Additional detail about them can, of course, be captured in additional notes, but not on this one ‘focus’ page. 5. Negotiate with the key stakeholders to formally agree these goals and budgets. Once the requirements, derived from the project’s understanding of the stakeholder needs, are clearly articulated – we need to go back to the real stakeholders and check that they agree with our ‘clear’ (but potentially incorrect or outdated) Costs / Effects Past Benchmark Budget Past Goal Satisf Goal Heal 123456789n Figure 1: Evolutionary result delivery takes system components readied for integration in the ‘backroom’ using arbitrary acquisition duration (as in kitchens), and presents them to stakeholders in frequent short Evolutionary result delivery cycles (as in the dining room). (Illustration courtesy of Kai Gilb) interpretation. It is also certainly a wise precaution to check back later, during the project evolution, with the stakeholders, especially the specific stakeholders who will be impacted by the next Evo step: �� as to how they feel about a particular choice of step content (that is, how they see the proposed design impacting performance and cost, and whether the original impact estimates are realistic in the real current implementation environment, and �� to check for any new insights regarding the long term requirements. 6. Plan to deliver some benefit (that is, ‘progress towards the goals’) in weekly (or shorter) cycles (Evo steps). A weekly delivery cycle is adopted by agile methods; this is good. However, the notion of
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Page 5 and 6: vi TABLE OF CONTENTS PART 1 - DATAB
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Page 9 and 10: CONFERENCE COMMITTEE Honorary Presi
Page 11 and 12: Hung, P. (AUSTRALIA) Jahankhani, H.
Page 13 and 14: Invited Papers
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Hit Rate (%) ACME-DB: AN ADAPTIVE C
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5.3.6 Effect on all Policies by Int
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ACKNOWLEDGEMENTS We would like to t
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This paper describes the data sampl
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The major limit A of the operation
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RELATIONAL SAMPLING FOR DATA QUALIT
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TOWARDS DESIGN RATIONALES OF SOFTWA
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((Brown et al., 1998), pp. 159-190,
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sive data filtering, presentation (
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• implementation changes in servi
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MEMORY MANAGEMENT FOR LARGE SCALE D
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Data Rate [bytes/sec] 1600000 14000
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E.g., DV Camcorder Camera Packets (
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Procedure CheckOptimal (n rs 1 ...n
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MEMORY MANAGEMENT FOR LARGE SCALE D
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PART 2 Artificial Intelligence and
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110 ENTERPRISE INFORMATION SYSTEMS
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DYNAMIC MULTI-AGENT BASED VARIETY F
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AN EXPERIENCE IN MANAGEMENT OF IMPR
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ANALYSIS AND RE-ENGINEERING OF WEB
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Module p0 Customer Itinerary Send I
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departments: the marketing dept. se
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• An acyclic module M is usable,
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BALANCING STAKEHOLDER’S PREFERENC
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The scenarios will provide an abstr
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BALANCING STAKEHOLDER'S PREFERENCES
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BALANCING STAKEHOLDER'S PREFERENCES
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A POLYMORPHIC CONTEXT FRAME TO SUPP
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A POLYMORPHIC CONTE XT FRAME TO SUP
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FEATURE MATCHING IN MODEL-BASED SOF
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combination of solution domains - a
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• features for all the concepts:
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Existence In both steps it is possi
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matching strategies are maximal, mi
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TOWARDS A META MODEL FOR DESCRIBING
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elementary message (ae-message) can
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problems on a pragmatic level, whic
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TOWARDS A META MODEL FOR DESCRIBING
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INTRUSION DETECTION SYSTEMS USING A
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INTRUSION DETECTION SYSTEMS USING A
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(k� 1) (k) (k�1) (k) p � w
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Table 5: Performance Comparison of
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A USER-CENTERED METHODOLOGY TO GENE
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carries out the second phase of the
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1 1 1 1 2 PROCESS STORE ENTITY EDGE
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constraints rules. KOGGE (Ebert et
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PART 4 Software Agents and Internet
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CABA 2 L A BLISS PREDICTIVE COMPOSI
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y disables evidencing severe mental
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Figure 4: Symbols emission in DAR-H
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they evidence a generalization erro
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A METHODOLOGY FOR INTERFACE DESIGN
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and mobility loss coupled with redu
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Tradeoff: The default input is poss
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Sessions on the VABS which are held
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A CONTACT RECOMMENDER SYSTEM FOR A
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A CONTACT RECOMMENDER SYSTEM FOR A
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- "Going to the sources". The user
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Here are the matrix W and P for our
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EMOTION SYNTHESIS IN VIRTUAL ENVIRO
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theme turns out to be surprisingly
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6 FROM FEATURES TO SYMBOLS 6.1 Face
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sions are described by different em
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Electronic Imaging 2000 Conference
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to the accessibility problem for th
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Figure 3: Hierarchical View of the
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4 CONCLUSIONS AND FUTURE WORK On th
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PERSONALISED RESOURCE DISCOVERY SEA
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profile, the user defines his curre
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Abdelkafi, N. .....................
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