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| − | == Abstract ==
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| − | The successive principle is a method for managing uncertainty and can be applied to budgeting and scheduling, as well as other disciplines of Project Management, Systems Engineering, Risk Analysis and Cost Engineering.<ref name="LIC2006" /> It was developed by Steen Lichtenberg, a former professor at the Technical University of Denmark (DTU).
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| − | Uncertainty is part of every project and marks the base for risks. Managing risks in a project proactively is of high importance, which can not only be a threat, but also be an opportunity with positive influence on the project success. <ref name="PMI2019"/> Especially infrastructure and construction projects suffer from underestimation of costs. Depending on the geographical area, the costs for infrastructure projects overrun in 9 of 10 cases and the real costs drift far off the cost estimations. The projects might fail and therefore seriously hazard the involved companies. Too optimistic and subjective estimations can arise from technical, economic, psychological and political pitfalls. <ref name="FLY2002"/>
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| − | The successive principle tries to minimize the subjective influence by successively eliminating uncertainties with a top-down approach and can be contextualized next to other classical risk analysis techniques. It differs from them through focusing on a cooperation of experts from estimating, scheduling, technical specifications, etc. and therefore creates a precise whole picture without disregarding a single aspect. Moreover, it synergizes subjective estimations with statistical theory and faces uncertainty also as an opportunity. <ref name="LIC2000" /> A diverse analysis team follows a given procedure successively defining new uncertainties and eliminating these through the combination of subjective (psychological) and objective (statistical) techniques. It is implemented into organizations mainly in the Nordic countries and has lead to success even in project with very high uncertainty. Although already being implemented successfully, criticism arises from the extensive preparations, a non balanced composition of the analysis group and human error in calculations. <ref name="LIC2016" />
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| − | The basic idea and procedure of the Successive Principle is described in detail and a simplified calculation example is given. Furthermore, example applications, as well as limitations and a critical reflection of the method in relation to project management standards are given.
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| − | == Theory and Principles==
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| − | The main goal for the development of the Successive Principle was to avoid the many pitfalls when applying classical risk management methods, which lead to cost overruns. It combines psychology, statistics and cost engineering and is based on the following key elements: <ref name="LIC2016" />
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| − | # Uncertainty exists and cannot be avoided and therefore needs to be considered and tackled
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| − | # Multidisciplinary, evened groups can evaluate smart and unbiased
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| − | # Eliminating uncertainty by successively detailing and building a quantitative model
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| − | # Getting a holistic view by adding overall influences and everything influencing the project <ref name="ARC2016" />
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| − | It also differs from traditional project management methods in three further points. <ref name="ARC2016" /> While typically the areas of large uncertainty are not tackled because of subjectivity, the Successive Principle picks exactly these for detailing and is able to be more precise than a traditional approach, considering more, but less subjective items. Furthermore, the new principle prioritizes the items with highest uncertainty and thus seeks diving into the most difficult items to estimate, which again differs from the traditional approach. Another change is made in the treatment of interrelated areas. The management of schedules, cost, resources and technical issues is now combined, specialists from each area are working together and thus interrelated areas are treated together, in order to not deflect the holistic view on the project. <ref name="ARC2016" />
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| − | == Procedure of the Method ==
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| − | The procedure of applying the successive principle can be split into a qualitative and a quantitative phase with several subtasks. Successive detailing takes place in the quantitative phase after setting the preconditions up in the qualitative phase. The general process is illustrated in figure… <ref name="LIC2000" />
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| − | ===Qualitative Phase===
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| − | '''Identification of subject and purpose:'''
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| − | The first step of each analysis consists of setting the scope and concrete goal, which should include more than just a cost minimization goal. It should contain preconditions, e.g. how profitability is measured and which currency is used. Furthermore, it defines the system of involved companies, which types of problems should be addressed and what limits the analysis. <ref name="LIC2000" /> Subject to the analysis can be a projects in all stages of its life cycle or also setting general strategic plans. <ref name="ARC2016" />
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| − | '''Establishing a group:'''
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| − | The analysis is conducted by a team of 7 to 15 experts, while the group size should not exceed 25 participants. It is very important, experts from all major key areas are included. To avoid bias and make the analysis precise, the group should also consist of generalists, specialists, optimists and pessimists and should include all genders and relevant age groups. The group will work in sessions of 2-3 days, which should be attended by most of the participants. <ref name="LIC2000" />
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| − | '''Ensure perfect conditions:'''
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| − | It is important to ensure, that a neutral environment is selected for the workshops, where all participants feel comfortable and can focus totally on the analysis. A perfect environment communication has to be established. <ref name="LIC2000" />
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| − | '''Consensus:'''
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| − | In the first group session, the participants get introduced to each other and a discussion about the goals, preconditions and scope defined in the first step is carried out. It is important, that all participants understand all key concepts and therefore an open discussion is key to success. The results of the discussion should be documented afterwards. <ref name="LIC2000" />
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| − | '''Identifiy and order most imporant issues:'''
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| − | '''Identifying issues:'''
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| − | The last step in the qualitative phase is to identify the main issues regarding the project. This starts with a group brainstorming to find 50-100 key words describing the issues. These can be further developed using matrices for pre-grouping, which also promote creativity. It is important to include positive issues in order to collect opportunities. The issues are then grouped into statistically independent groups, called overall influences, with an aim of obtaining 8-15 groups. For each of the overall influences, two cases are created, a base as a reference, and a future situation to include opportunities, double sided manners and risks. It will be also necessary to build a group with not groupable issues, as well as one with issues related to the analysis itself (e.g. pessimism and optimism). <ref name="LIC2000" />
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| − | ===Quantitative Phase===
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| − | '''Quantification and successive specification:'''
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| − | The quantitative phase begins with running through successive cycles, to reduce uncertainty. In each circle, beginning with the overall influences, now called items are detailed using the “Hierarchical work breakdown structure.” Therefore, each item gets split into sub items in each circle. The calculation of the uncertainty is based on the “subjective probability theory.” <ref name="LIC2000" /> For each item, triple estimates are made, which consist of the estimated extreme minimum and maximum values and a most likely value. A mean value of these is build, while the most likely value is multiplied with the factor 3. The standard deviation and variance are calculated as well. Taking the square route of the sum of the single variances leads to the overall global standard deviation.
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| − | Through successively detailing the uncertainties, the global standard deviation will decrease. The process should be continued, until the global value does no longer improve. The priority for further detailing is given by the variance of each item. This process description only gives an overview of the real process. Here correction factors are applied and each time the analysis breaks down, and an additional uncertainty for the breakdown must be added. <ref name="LIC2000" />
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| − | '''Action plan:'''
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| − | With the specified costs and uncertainties, an action plan is developed by the team as a final step of the analysis. It should mainly focus on the results of the successive specification and can be initiated with a brainstorming. The goal is to establish actions to exploit opportunities, protect against risks and reduce the general uncertainty. <ref name="LIC2000" />
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| − | == Example Calculation ==
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| − | To illustrate the top-down approach, a simplified example calculation is given. The calculation shows, how the overall uncertainty can be decreased by successively breaking down the largest uncertainties. In the example (see figure…), three items (A, B, C) and an additional item for the overall influences (X) are used. Fictional numbers for mean values and standard deviation of each item are set, which in would be calculated from the triple estimates. These add up to an overall mean value and standard deviation. The variance for each item can be calculator by squaring the standard deviation and the item with the highest standard deviation is defined as the largest uncertainty. In a second step, the item B with the highest standard deviation is broken down into sub items, which are again filled with the results from the triple estimates and the table updated. With the breakdown, the variance of item B can be lowered and thus the total variance and overall standard deviation decrease. This also means, that the uncertainty decreased. If this successive procedure is carries out for all items and into, always starting with the highest uncertainty, the overall uncertainty can be lowered significantly. This is done by successively creating new “top ten lists” starting with the item, that has the highest uncertainty. <ref name="LIC2016" /> The example also shows, that while mean values might increase through specification, the overall uncertainty decreases. This happens, because the standard deviation of each subitem is expected to decrease, which is connected to a smaller range of the triple estimate values.
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| − | == Comparison to Risk Management Standards ==
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| − | == Limitations and Critical Reflection ==
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| − | == Annotated Bibliography ==
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| − | * Lichtenberg, S. (2000). Proactive management of uncertainty using the Successive Principle - a practical way to manage opportunities and risks. Polyteknisk Press
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| − | ::The main publication explaining the methodology
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| − | * Lichtenberg S., Klakegg, O.J. Successful Control of Major Project Budgets. Administrative Sciences. 2016; 6(3):8.
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| − | ::Peer reviewed paper, Latest publication
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| − | * Project Management Institute, Inc. (PMI). (2019). Standard for Risk Management in Portfolios, Programs, and Projects. Project Management Institute, Inc. (PMI)
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| − | == References ==
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| − | <references>
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| − | <ref name="LIC2000">Lichtenberg, S. (2000). Proactive management of uncertainty using the Successive Principle - a practical way to manage opportunities and risks. Polyteknisk Press</ref>
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| − | <ref name="LIC2016">Lichtenberg, S., Klakegg, O.J. Successful Control of Major Project Budgets. Administrative Sciences. 2016; 6(3):8.</ref>
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| − | <ref name="LIC2006">Lichtenberg, S., (2006) The Successive Principle – a scientific crystal ball for management. Conference Paper. The international Cost Engineering Council </ref>
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| − | <ref name="PMI2019">Project Management Institute, Inc. (PMI). (2019). Standard for Risk Management in Portfolios, Programs, and Projects. Project Management Institute, Inc. (PMI) </ref>
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| − | <ref name="FLY2002">Flyvbjerg, B., Skamris Holm, M., Buhl, S. (2002). Underestimating Costs in Public Works Projects: Error or Lie? , Journal of the American Planning Association, 68:3, 279-295 </ref>
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| − | <ref name="ARC2016">Archibald, R., Lichtenberg, S. (2016). Experiences Using Next Generation Management Practices The Future Has ALready Begun, PM World Journal, 5:8 </ref>
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| − | </references>
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