Using Learning Plans to Counter Project Uncertainty

Revision as of 10:29, 16 February 2021

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 what a Learning Plan is, how it is implemented and highlights the benefits and limitation of the tool.

Introduction

The philosophy behind the Learning Plan is 'learning per dollar spent'. The Learning Plan arose from a seven year research study from MIT tracking the progress of 12 breakthrough innovation projects in 10 large, technology intensive firms. The philosophy acknowledges that working with projects of high uncertainties often force project teams to make decisions based on assumptions rather than known facts because they are simply not available. Since it is unclear if It measures the progress of such projects on the 'learning per dollar spent instead' of

Depending on the different degrees of uncertainties associated with a project, management may use different planning approaches as illustrated on figure 1. 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 facts may not be not available. Using an inappropriate planning approach for a project of high uncertainty may be a costly and time-wasting affair.

This is because the goals and direction of such projects tend to change with a much higher frequency compared to projects of low uncertainty when unknowns become knowns.

- ‘Learning per dollar spent’ philosophy - From unknowns to knowns (unknown, hypothesis, known) - Figure

Prioritizing unknowns using the Uncertainty Matrix

- Purpose: - Technical, Market, Organizational and Resource uncertainties - Tells which unknowns to work on (upper right corner) - Figure

Implementing the Learning Plan

- 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]

References

Annotated bibliography

Depending on the different degrees of uncertainties associated with a project, management may use different planning approaches as illustrated on figure 1. 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 and the path forward is difficult to visualize. 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. This iterative learning loop approach allows managers to decide on an ongoing basis whether the cumulative learning is of sufficient value to warrant continuing the project. The progress is measured by 'learning per dollar spent'.