Learning plan
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'''The learning plan process''' | '''The learning plan process''' | ||
| − | The learning plan process is divided into two | + | The learning plan process as described by Rice et al. <ref name="Learning_Plan"> Rice et al., Implementing a Learning Plan to Counter Project Uncertainty, MIT Sloan Management Review, 49, 2008. </ref> is divided into two main parts. First, a learning loop is conducted and second, the learning from this loops gets evaluated. Following the steps of the learning plan template, each learning loop or iteration through the learning plan starts with the identification of explicit uncertainties in all four uncertainty categories. The following figure provides a non-comprehensive list of uncertainties that potentially arise in projects that can serve as a starting point for creative thinking. It can also be beneficial to write down what is already known at this step of the process. |
[[File:Uncertainty_Management_Checklist.png|450px|thumb|right|Figure 1: Uncertainty Management Checklist <ref name="Learning_Plan"> Rice et al., Implementing a Learning Plan to Counter Project Uncertainty, MIT Sloan Management Review, 49, 2008. </ref> <ref name="Radical_Innovation"> Leifer et al., Radical Innovation: How Mature Companies Can Outsmart Upstarts, Harvard Business School Press, 2000. </ref>.]] | [[File:Uncertainty_Management_Checklist.png|450px|thumb|right|Figure 1: Uncertainty Management Checklist <ref name="Learning_Plan"> Rice et al., Implementing a Learning Plan to Counter Project Uncertainty, MIT Sloan Management Review, 49, 2008. </ref> <ref name="Radical_Innovation"> Leifer et al., Radical Innovation: How Mature Companies Can Outsmart Upstarts, Harvard Business School Press, 2000. </ref>.]] | ||
| + | The definition of knowns and un-knowns is followed by an assessment of their criticality to identify potential showstoppers and make a decision on where to learn first. Mostly this is done with the levels high, medium and low. In the next step, the project team needs to develop assumptions while potentially focusing on the most critical uncertainties depending on time and resource constraints. Assumptions are accepted as true as long as they are not disproved. While a project can potentially progress based on these assumptions it is key to the learning plan that these assumptions get further tested to either turn them into facts or find better suitable assumptions. This is done through the remainder of the steps of a learning loop starting with the identification, exploration and assessment of alternative testing approaches to each assumption. Then, the most efficient testing approaches in terms of “learning per dollar spent per time” are selected. This can be understood as the value of the cumulative learning outcome that can be expected from the test compared to the costs it causes. If no testing approach is found to deliver sufficient value, the project can either continue based on the assumption or managers might even decide on terminating the project. After that, the measurement criteria for either proving or disproving an assumption through the test gets defined. In the following step, the timetable for the tests is defined and resources get assigned to the tests which are then finally conducted. The test outcomes get also noted down in the learning plan. The tests do not necessarily have to be taken out by the project team but can as well be outsourced to other parts of the company or even external providers. | ||
| − | This is | + | In the second part of the learning plan the evaluation of the learning loop takes place. This part is not necessarily to be taken out by the core project team itself but can also be taken out by an oversight board or project evaluation board that continuously monitors the learning outcome. It starts with an analysis and assessment of the test results and whether they prove or disprove the assumptions based on the measurement criteria. In case an assumptions is disproved it needs to be evaluated which other assumption might then be more appropriate to the respective uncertainty. Then, as uncertainties in the four categories interact with one another, it has to be further assessed if the learning from testing one assumptions has potentially affected assumptions about uncertainties in other categories. Finally, the learning gets evaluated in terms of its effect on the overall project progress before the steps required for following learning loops are defined. In practice, teams are found to have taken three to four learning loops until they reached an appropriate level of certainty to apply another approach to project planning. |
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| + | == Conclusion == | ||
== Limitations == | == Limitations == | ||
Revision as of 17:09, 16 February 2021
Contents |
Abstract
[tbd] This article is about the ‘Learning plan’ - a tool to overcome the challenge of making sound decisions while facing uncertainties. It provides a systematic framework to facilitate a learning process that turns un-knowns into knowns. In principle, a learning plan is a document that can be used by a project team to resolve uncertainties in four different categories: market, technical, resource and organizational uncertainty. For the most critical ones the team develops assumptions for their solution. These are then tested and, if disproved, turn into a new assumption or, if proved, into a fact. A learning plan is essential to successful project management in the light of uncertainty. This is especially the case in new product development where the degree of uncertainty is typically high. In detail, learning from experience is one of the principles that reflect successful programmes and projects [1] [2]. An example learning process consists of several learning loops or passes through the learning plan. In each, a set of assumptions get tested until a sufficient level of certainty is reached. Typically, a project team needs about 3-4 learning loops to progress on the project. Each iteration consists of two phases: the testing of critical assumptions and the evaluation. The latter consists of a review of the results where new assumptions and further tests are identified.
Big idea
A learning plan is a tool to overcome the challenge of making sound decisions while facing uncertainties. It provides a systematic framework to facilitate a learning process that systematically turns un-knowns into knowns. It is particularly useful in the project planning stage when a project team needs to manage multidimensional uncertainties. This is especially the case in new product development where the degree of uncertainty is typically high. Therefore, learning from experience is one of the principles that reflect successful projects as they involve a temporary organization that may not already have the necessary experience. Through the learning plan, a project team can systematically gain this experience through experimentation during the life cycle of a project [1] [2].
In short, a learning plan has the following characteristics: [3] - It catalogues uncertainties - It connects uncertainties with assumptions - It prioritizes uncertainties based on their criticality - It presents testing approaches to resolve critical uncertainties - It documents a project’s progress in terms of learning outcomes and consequences thereof
While a learning plan has no universal format, a basic learning plan should consist of at least two sections. In the first section, the participants of the learning process catalogue uncertainties in four categories: market, technical, resource and organizational uncertainty. For the most critical ones the team then develops assumptions that get tested and, if disproved, turn into a new assumption or, if proved, into a fact. In the second section, this is then followed by an evaluation of the learning where results are reviewed and, if necessary, new assumptions and tests are developed to initiate another iteration of the learning plan. The learning plan is therefore continuously revised to adopt learning outcomes.
Background
A common characteristic of projects is that they all face uncertainty in the planning process. As projects mature the project team will gain experience which increases the availability of decision-relevant knowledge while never fully eliminating all un-knowns. Uncertainty can be seen as the cause of individual project risk which is defined as "an uncertain event or condition that, if it occurs, has a positive or negative effect on one or more project objectives". [4]. Reducing uncertainty to make decisions based on knowledge is therefore a common goal in project management. The process of acquiring new, or modifying existing, knowledge, behaviors, skills, values, or preferences based on experience is called learning [3]. Uncertainty as a lack of knowledge or information can therefore be reduced with an appropriate learning process and is also an essential part of risk and uncertainty management procedures [5].
The learning plan as a tool for systematic learning which ideally results in uncertainty reduction. It is widely used for innovation projects, particularly for radical innovations, where the degree of uncertainty is typically higher. In order for project teams to proceed, assumptions have to be made. Over time, learning reduces the number of these assumptions and turns them into new knowledge. This in turn leads to a higher certainty in management decisions while projects mature. [3]
There are different established approaches to cope with project uncertainty. The following figure provides an overview of different project planning approaches each associated with a certain degree of uncertainty where it proved most useful. The learning plan is therefore seen as the project planning framework that can be used in situations of particularly high uncertainty. While the degree of uncertainty ideally gets reduced throughout the lifecycle of a project and several iterations of the learning plan, other project planning approaches may take over. [3]
Application
The following figure shows a template for a basic learning plan. It incorporates both the steps of the learning plan process and the categories of uncertainties that are found to occur in projects. These refer to the multidimensionality of uncertainty. For a successful application of the learning plan it is crucial to understand these categories, which are therefore presented further before digging into the actual learning plan process.
Dimensions of uncertainty
The following figure shows the three dimensions of uncertainty in the context of project management described by O'Connor and Rice [5]: category, latency and criticality.
The first dimension, the uncertainty category, is dividing uncertainties into the four content areas technical, market, organizational and resource uncertainty. In relation to the learning plan, the following learning objectives can be defined for each: [6]
- Market uncertainty: Learning about market drivers, value creation and business viability - Technical uncertainty: Understanding technology drivers, value and economic feasibility - Resource uncertainty: Accessing money, people and organizational competencies - Organization uncertainty: Gaining and maintaining organizational legitimacy
Projects can differ largely in the level of uncertainty in each dimension. Moreover, the uncertainties in different categories can interact with one another so that resolving an uncertainty in one category can also have an effect on other categories. Splitting up the uncertainties into these categories helps a project team analyzing the entire spectrum of uncertainties and avoiding the pitfall of focusing only on such categories that the project team is comfortable with. For successful projects it is particularly important to reduce uncertainty and accumulate learning over all categories. [3]
The second dimension of uncertainty, latency, refers to the degree to which an uncertainty can be anticipated. The higher the latency, the more difficult is it to perceive the uncertainty and find appropriate assumptions for it. As a result, high latency uncertainties may not be resolved with assumption testing before they actually occur. The concept of latency is not explicitly noted in the learning plan. Nevertheless, project teams need to try their best in cataloguing also those uncertainties that are difficult to anticipate but might have a large influence on the project's progress. Moreover, they need to be flexible in their learning approach as they might need to adapt to new circumstances as the project matures.
The third dimension of uncertainty refers to the criticality of the uncertainties identified within the four categories. An uncertainty is found to be critical if it is a potential showstopper for the project. In order to ensure a project's success these therefore need to be resolved immediately. On the other hand, an uncertainty which is routine does not threaten a project's survival. The assessment of criticality takes place in the second step of the learning plan process. The most critical uncertainties should be targeted by assumptions and tests as soon as possible.
The dimensions latency and criticality are found to interact with one another as shown in the following figure. The uncertainties which are anticipated and routine are fairly easy to handle as they are known from project start and can be targeted with an appropriate set of assumption testing approaches. Unanticipated but routine uncertainties occur without prior perception but due to their routine property can be treated quickly through the next iteration of the learning plan. Anticipated showstoppers need to be targeted with a more comprehensive set of actions while unanticipated showstoppers need to be addressed aggressively upon occurrence which may require a substantial amount of resources. The occurrence of uncertain events during a project´s lifecycle is not necessarily negative but can as well be an opportunity for further progress that hasn't been there before.
The learning plan process
The learning plan process as described by Rice et al. [6] is divided into two main parts. First, a learning loop is conducted and second, the learning from this loops gets evaluated. Following the steps of the learning plan template, each learning loop or iteration through the learning plan starts with the identification of explicit uncertainties in all four uncertainty categories. The following figure provides a non-comprehensive list of uncertainties that potentially arise in projects that can serve as a starting point for creative thinking. It can also be beneficial to write down what is already known at this step of the process.
The definition of knowns and un-knowns is followed by an assessment of their criticality to identify potential showstoppers and make a decision on where to learn first. Mostly this is done with the levels high, medium and low. In the next step, the project team needs to develop assumptions while potentially focusing on the most critical uncertainties depending on time and resource constraints. Assumptions are accepted as true as long as they are not disproved. While a project can potentially progress based on these assumptions it is key to the learning plan that these assumptions get further tested to either turn them into facts or find better suitable assumptions. This is done through the remainder of the steps of a learning loop starting with the identification, exploration and assessment of alternative testing approaches to each assumption. Then, the most efficient testing approaches in terms of “learning per dollar spent per time” are selected. This can be understood as the value of the cumulative learning outcome that can be expected from the test compared to the costs it causes. If no testing approach is found to deliver sufficient value, the project can either continue based on the assumption or managers might even decide on terminating the project. After that, the measurement criteria for either proving or disproving an assumption through the test gets defined. In the following step, the timetable for the tests is defined and resources get assigned to the tests which are then finally conducted. The test outcomes get also noted down in the learning plan. The tests do not necessarily have to be taken out by the project team but can as well be outsourced to other parts of the company or even external providers.
In the second part of the learning plan the evaluation of the learning loop takes place. This part is not necessarily to be taken out by the core project team itself but can also be taken out by an oversight board or project evaluation board that continuously monitors the learning outcome. It starts with an analysis and assessment of the test results and whether they prove or disprove the assumptions based on the measurement criteria. In case an assumptions is disproved it needs to be evaluated which other assumption might then be more appropriate to the respective uncertainty. Then, as uncertainties in the four categories interact with one another, it has to be further assessed if the learning from testing one assumptions has potentially affected assumptions about uncertainties in other categories. Finally, the learning gets evaluated in terms of its effect on the overall project progress before the steps required for following learning loops are defined. In practice, teams are found to have taken three to four learning loops until they reached an appropriate level of certainty to apply another approach to project planning.
Conclusion
Limitations
Text
Annotated bibliography
Text
References
- ↑ 1.0 1.1 AXELOS, The Stationery Office Ltd, Managing Successful Programmes, 2011 Edition.
- ↑ 2.0 2.1 AXELOS, The Stationery Office Ltd, Managing Successful Projects with PRINCE2, 2017 Edition.
- ↑ 3.0 3.1 3.2 3.3 3.4 3.5 Leifer et al., Radical Innovation: How Mature Companies Can Outsmart Upstarts, Harvard Business School Press, 2000.
- ↑ Guide to the Project Management Body of Knowledge, PMBOK Guide, 6th Edition, 2017.
- ↑ 5.0 5.1 5.2 5.3 Perminova et al., Defining Uncertainty in Projects - A New Perspective, International Journal of Project Management, 26, 2008.
- ↑ 6.0 6.1 6.2 6.3 6.4 Rice et al., Implementing a Learning Plan to Counter Project Uncertainty, MIT Sloan Management Review, 49, 2008.
