1. Metricon 1.0 Model Concepts for Consideration and Discussion
Risk Optimized Solutions
Metricon 1.0 Model Concepts for Consideration and Discussion
Presented by:
Bryan S. Ware

2. Digital Sandbox Risk Optimized Investment Matrix™1 6
Risk Measure
Allocation within Quadrants
High
Discount for low effectiveness
Best investments II I
Risk 5 IV
III
Allocation to Quadrants 2
Low
Apply minimum funding
Risk Threshold
Incentivize high effectivenss
In constructing the matrix, we considered over 1000 options to include:
3 different measures of risk (actual data, curve fit data, modified curve fit data)
2) 2 concepts for a risk threshold (avg, break in the curve)
3) 5 Different Effectiveness utilities (two averages, three utility functions)
4) 2 concepts for Effectiveness threshold (Mean, Median)
5) 2 concept for allocation within bins (straight, 2/3-1/3)
6) 3 Bin allocation concepts
Low
High 4 3
Effectiveness
Effectiveness Threshold
Effectiveness Measure

3. 2x2 Matrix Approach Risk Effectiveness Risk Data Effectiveness Data
Higher risk,
lower
effectiveness
Higher risk,
higher
effectiveness
Risk
Lower risk,
lower
effectiveness
Lower risk,
higher
effectiveness
Risk Data
Effectiveness
Each grantee is plotted in the matrix by their combination of Risk Score and Effectiveness Score. Those scores determine which quadrant of the matrix they end up in.
We performed extensive analysis of options for assembling the matrix. Our analysis led us to constructing the matrix with the following characteristics.
1) Risk is based on a curve fit to the actual RMD Data
Risk threshold determined by natural inflection point in curve
Effectiveness was based on the peer review scores for the Investment Justification Portfolios of the Grantees
The effectiveness threshold was determined statistically by taking the Median of the effectiveness scores. This guarantees that half the grantees are on the high side and half on the low side of effectiveness
Competition within each bin was based on a 65/36 split of Risk vs. Effectiveness
Allocation within the bins is the most important Management Decision as it drives final allocations for grantees. We have looked at many options for this.
Frequency
Score
Effectiveness Data

4. Combining Risk and Effectiveness
Selected approach for combining risk and effectiveness to determine final allocations is 2x2 matrix
Creates set of plausible options by considering high and low cases of two competing needs
Benefits
Optimizes ability to allocate resources based on relative risk and proposed solutions to address identified need
Supports management objectives
Creates incentives to building well-planned, solid proposals
Risk
Effectiveness 1 2 3 4
Best investments
Incentivize high effectiveness
Discount for low effectiveness
Apply minimal funding
Low
High
VALUE OF 2x2 MATRIX
A complex situation is modeled as a set of dueling interests (e.g. Balancing Risk and Effectiveness)
Instead of  a single “right answer”, a set of plausible options is created by considering high and low cases of two competing needs
When the two axes are well defined, the options in each quadrant will be rich in explanatory power and provide a graphical representation of the decisions that must be made.
Well known 2x2 Matrices include Steven Covey’s classic time management matrix, Gartner Group’s technology leadership matrix, and Boston Consulting Group’s Product Portfolio matrix.
Similar matrices are frequently developed for balancing investment priorities among dissimilar objectives
Evaluated approximately 1,100 combinations to determine the best approach