Using Learning Plans to Counter Project Uncertainty
Innovation projects are fraught with uncertainty in their nature. However, oftentimes management approaches presume a high degree of knowns and plan clear pathways through development stages. Doing so can be a costly and time-wasting affair and is caused by not recognizing that project teams are proceeding based on assumptions instead of known facts. [1] When recognizing this fact, the Learning plan offers a systematic way of dealing with the high uncertainties to reduce maturation time or the time needed to reach a decision to kill the project by as much as 50%. Using the Learning Plan allows a team to manage the ongoing evaluation and redirection in innovation projects, where specific objectives most likely are unclear or where the final goal is clear, but the pathway is uncertain. This article describes the Learning Plan, how it is implemented and highlights the benefits and limitation of the tool.
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Introduction
The Learning Plan is a planning tool suitable for projects of high uncertainty. It allows a project team to evaluate and redirect the project in a proactive way when objectives may be unclear or when the goal is clear but the path is uncertain. When the uncertainties are high, project teams often need to proceed based on assumptions rather than known facts. This is for instance the case when dealing with innovation projects where the final market is unclear, which products will gain market acceptance most quickly and fully are unknown. The significance and number of uncertainties make it difficult to define milestones and the pathways to achieving them. In such projects, it is more reasonable and useful to identify and prioritize uncertainties that must be resolved, to define alternative approaches to exploring them and to continually assess the value of cumulative learning compared to the costs incurred. The prioritized uncertainties are input to the Learning Plan, which offers an iterative learning loop approach that allows managers to decide on an ongoing basis whether the cumulative learning is of sufficient value to warrant continuing the project. The progress of a project is measured by 'learning per dollar spent'. Learning in this context can be translated into the extend to which an unknown has become a known. This is an effective way of measuring progress in high uncertainty projects because it acknowledges that the direction or goal of high uncertainty projects tend to change much more frequent compared to projects of low uncertainty. When such a change happens, it does not always make sense to measure the progress based on how close you get to your initial goal. Instead you measure how much you learned from each dollar spent.
Prioritized unknowns are input to the Learning Plan
The Learning Plan makes use of four categories of uncertainty: technical, market, organizational and resource.
Technical uncertainties comprise those related to the completeness of scientific knowledge regarding the problem, whether the technical specifications may be applied and so forth.
Market uncertainties are related to customers' needs, customer segments and competitors [4]. The difficulty in understanding the customers’ needs and translating them into functional and symbolic characteristics of the product generates market uncertainty [5].
Organizational uncertainties are associated with the dynamics of the organization and include, organizational resistance, lack of persistence, inconsistencies in expections and metrics, changes in strategies, or changes in internal and external partners. [6]
Resource uncertainties include financial ressources but also competencies. Project teams often lack one or more competencies critical to the success of pursuing opportunities. This may lead to project teams spending large amounts of time on acquiring the competencies needed.
- Purpose: - Technical, Market, Organizational and Resource uncertainties - Tells which unknowns to work on (upper right corner) - Figure
Implementing the Learning Plan
- From unknowns to knowns (unknown, hypothesis, known) / Figure - Encourages project teams to systematically examine each of the categories in the Uncertainty Matrix
- One learning loop: o Assumption, test assumption (select approaches to test and test success criteria that meet the needs of managers) o Agreement between team and evaluaters on objectives for each test and how success is measured for each test. o Teams conduct tests and assess how much uncertainty reduction there is for each unknown. Update uncertainty matrix. o Evaluation with team’s oversight board (critical step)
- Iterative, remember to update uncertainty matrix as you identify more unknowns - Figure
Key benefits
Limitations and pit falls
- there is a natural tendency to confront the uncertainties with which the team is more comfortable and to ignore others. This is a dangerous problem for teams composed mostly or solely of technical personnel, who generally prefer to focus on technical challenges. Failing to also recognize and confront market, organizational and resource uncertainties increases the likelihood that one of these uncertainties will turn out to be a project killer. To counteract such tendencies, it is important for oversight boards to be staffed with veterans of high-uncertainty projects.
References
1. See R.G. Cooper, “Stage-Gate Systems: A New Tool for Managing New Products,” Business Horizons 33, no. 3 (May-June 1990): 44-54. 2. See Z. Block and I. MacMillan, “Milestones for Successful Venture Planning,” Harvard Business Review 63 (September-October 1985): 184-196. 3. See R.G. McGrath and I. MacMillan, “Discovery-Driven Planning,” Harvard Business Review 73 (July-August 1995): 44-54. [1] 4. Rice, M. P., O’Connor, G. C., Pierantozzi, R., 2008. Counter Project Uncertainty. MIT Sloan Management Review, Winter, 54-62. 5. Biazzo, S., 2009. Flexibility, structuration, and simultaneity in new product development. Journal of Product Innovation Management, 26, 336-353. 6. Lechler, T. G., Edington, B. H., Gao, T., 2012. Challenging Classic Project Management: Turning Project Uncertainties Into Business Opportunities. Project Management Journal, 43, 59-69.
References
Annotated bibliography
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