443155 Discovery Driven Planning - A Tool to Quantify and Report on Uncertainty

Wednesday, April 13, 2016: 2:00 PM
339A (Hilton Americas - Houston)
A. R. (Tony) Cartolano, SPEC Process Engineering & Construction Inc., Burlington, MA and R. Pierantozzi, Cameron & Associates, LLC, Blue Bell, PA

As a new process is developed there are many decision points along the way, any of which could de-rail the program if the wrong decision is made.  These decisions can be technical decisions about process options and/or business decisions about products and markets.  Early in the project, there is usually uncertainty about elements of these aspects, so the project team will make assumptions, make decisions, and move forward based on those assumptions.  Here’s the catch – all of these assumptions are wrong to some extent.  So what is the team to do?  Management is pressuring the team for results, so the team presses on, sometimes to disappointing results. 

There are techniques for evaluating the uncertainties associated with the assumptions made and for driving decisions based on the sensitivity of the desired outcome to key assumptions.  One of these tools is known as Discovery Driven Planning, developed at Wharton.   Although the tool was developed primarily to address uncertainty about a business plan, it can be used to analyze the technical side of a project where uncertainty exists and assumptions need to be made, which is probably over 99% of all technical programs.  This can be uncertainty about a product cost strip, or a capital investment, or any technical aspect of a development program.

We present the basic tenets of a Discovery Driven Plan, and outline the steps needed for any project team to perform.  This results in the development of a model that produces objective functions dependent on the assumptions made by the team.  We also present a Monte Carlo simulation tool that allows the team to test any objective function against the assumptions made, resulting in predictions of the objective function(s), and sensitivity of the function to the assumptions made.  Finally, a new-product cost strip is presented as an example, and the management decisions that resulted from this analysis are discussed.

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See more of this Session: Technology Transfer: The Process and Applications I
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