In project work we're looking to create or change something, in some defined period of time, for a defined cost. This means we're going to spend money now for some future outcome. The elements that go into this effort to produce some change in the future include (but are not limited to) scope of our efforts (requirements for the outcomes), technical performance (including quality and other ...ilities of the outcomes), the schedule for the work (so we don't have to do everything at once), the budget so we know the cost of the value produced), resources that do the work in exchange for money defined in the budget, risk to cost, schedule, and technical performance goals, and other attributes. A specific project will have specific constraints from each of these attributes.
The relationships between these attributes is usually non-linear, random in some way (stochastic), and affects future outcomes. Because of the random nature of the attributes and the random nature of their relationship, simple linear, non-statistical projections of past performance used for future performance is most likely to be a disappointment.
To answer the question what does the future look like when the past is a non-linear stochastic process, we need to be able to manage in the presence of uncertainty. With this ability, the future simply emerges and many times this futute is not what was expected.
This is the role of planning. The best description of planning is
planning constantly peers into the future for indications as to where a solution may emerge. A Plan is a complex situation, adapting to an emerging solution.
- Mike Dwyer, Big Visible
To be successful at planning we need to do many things. Since it is the future we're planning for each of these things requires an
ESTIMATE
Yes, we're never going to see it coming if we don't Plan. And to Plan, we need to estimate. And to estimate we need to learn how to estimate. So if we want to manage in the presence of uncertainty, here's a starting point...
- Statistical Decision Theory: Concepts, Methods, and Applications
- Improved Software Project Risk Assessments using Bayesian Networks
- Software Project and Quality Modelling using Bayesian Networks