PM 570 Week 4 Selecting and Balancing a Portfolio Example

Mandatory, Strategic or Optional: Selecting and Balancing a Manufacturer's Project Portfolio Under a Refrigerant Deadline

[Student Name]

University of Phoenix

PM/570: Projects, Programs, and Portfolios

Week 4 Assignment

[Instructor Name]

[Date]

Red River Air Systems, its candidate projects, scores and figures are composites written for a model paper.

Red River Air Systems, the invented Wichita Falls maker of light commercial rooftop units followed through PM 570, sets its capital and engineering plan each autumn. For the coming year, eleven candidate investments compete for about $24 million in capital and project spending and for a pool of 62 engineers. The refrigerant conversion program designed in Week 3 is one of them. This paper selects and balances the portfolio.

Portfolio Management Versus Program Management

Program management coordinates related projects to gain shared benefits; portfolio management chooses which projects and programs, related or not, the organization should invest in to meet its strategy. Archer and Ghasemzadeh (1999) proposed an integrated framework for portfolio selection that moves from strategy and resource limits through screening and individual project analysis to optimal portfolio selection and adjustment, emphasizing that selection should consider interactions among projects and resource constraints rather than evaluating each in isolation. Martinsuo (2013) reviewed portfolio management research and argued that real portfolio decisions are shaped by organizational context, negotiation and politics, not only by rational models. Red River's process uses a structured method while acknowledging that judgment and negotiation will shape the result.

Step 1: Mandatory Work First

The conversion program is required by regulation; without it, Red River cannot sell its main products for new installations. It needs about $8.6 million and 26 engineers in the coming year. A second mandatory item, replacing a paint line's air permit controls to meet a state air permit renewal, needs $1.2 million and 2 engineers. Mandatory work therefore takes $9.8 million and 28 engineers, leaving about $14.2 million and 34 engineers for discretionary choices.

Step 2: Screening

Nine discretionary candidates remain. Two fail minimum criteria: a residential split-system line, which conflicts with the strategy of focusing on light commercial customers, and an acquisition of a small duct manufacturer, which the board deferred for financing reasons. Seven candidates move to scoring:

A: variable-speed compressor option for the rooftop line ($3.4 million; 9 engineers).

B: enterprise resource planning upgrade ($4.1 million; 3 engineers plus outside consultants).

C: second coil production cell to raise capacity ($3.8 million; 4 engineers).

D: remote diagnostics module for dealers ($2.2 million; 8 engineers).

E: automated sheet metal line ($5.6 million; 6 engineers).

F: dedicated outdoor air unit for schools ($2.9 million; 11 engineers).

G: dealer portal and parts e-commerce ($1.6 million; 4 engineers).

Step 3: Scoring

Before scoring, the executive team set weights: strategic fit 35 percent, net present value 25 percent, risk 20 percent, scored so that lower risk scores higher, and time to benefit 20 percent. Scores from 1 to 5 were assigned by a panel of the finance, engineering and sales leaders with written reasons. Weighted results, highest first: C 4.15 (capacity for the compliant line, strong value, low risk); A 3.95 (efficiency rules and dealer demand); D 3.80 (service differentiation, recurring revenue); G 3.55; E 3.40; B 3.10; F 2.95 (strategic but long time to benefit and high risk).

A scoring model ranks the candidates; the constraint decides how many of them can actually run.

Step 4: Applying the Binding Constraint

Money is not the binding constraint: the top five candidates cost $16.6 million, only modestly above the $14.2 million available, and the ERP upgrade could be phased. Engineers are. The top four by score, C, A, D and G, need 25 engineers; adding E brings the total to 31, within the 34 available; adding B needs only 3 more, reaching 34; F, at 11 engineers, cannot fit. But C, A, D, G and E together cost $16.6 million, above the $14.2 million limit. Dropping E, the most expensive, gives C, A, D, G and B at $15.1 million, still above the limit unless B is phased; phasing B to $2.6 million this year brings the total to $13.6 million and 28 engineers.

Step 5: Checking Balance

Red River's strategy sets target shares for discretionary spending: about 40 percent growth, 40 percent efficiency and 20 percent capability. The candidate set C, A, D, G and phased B splits roughly 53 percent growth (A, D, G), 28 percent efficiency (C) and 19 percent capability (B). Growth runs over its target and efficiency under it, because E, the largest efficiency project, was dropped. Risk is concentrated in A and D, both depending on the controls engineering team already stretched by the conversion program. Kester et al. (2011) studied portfolio decision processes in firms and found that effective portfolio decisions combined evidence-based analysis with intuition and political processes, and that firms differed in how well they integrated these. The executive team discussed the controls risk explicitly and agreed that D's start would follow the conversion program's sensor platform milestone.

Recommendation

Fund the mandatory conversion program and paint line permit work. Fund C, A and G in full, start D after the sensor platform milestone in month 5 and phase B, with its first phase covering finance and purchasing. Defer E to next year, when the conversion program releases engineers, and defer F, which needs a new market study. Total discretionary spending is about $13.6 million with 28 engineers, leaving six engineers as a buffer for the conversion program, whose regulatory deadline cannot move. The value given up by deferring E, an estimated $1.4 million in net present value from a year's delay, is accepted to protect the mandatory program's schedule.

Limits of the Method

The scoring model has weaknesses the team acknowledged. Scores for strategic fit depend on judgment, and the sales leader on the panel had an interest in the remote diagnostics module. To limit that, each score required a written reason and a second panelist's agreement. Net present value estimates for the variable-speed option and the remote diagnostics module rest on uncertain adoption rates, so the panel scored them with ranges and used the midpoint. Finally, scoring treats projects as independent, while some are not: the dealer portal will be more valuable if remote diagnostics also proceeds, since dealers could order parts from diagnostic alerts. The recommendation keeps both, partly for that reason.

Communicating the Decision

The sponsors of deferred projects needed more than a list. The chief operating officer met the automation team, whose sheet metal line was deferred, to explain that the decision turned on engineers, not on the merits of the project, and to commit to a start in the second half of the year if the conversion program releases people on schedule. The schools product team received a smaller budget for a market study, so its case can be rebuilt with evidence. Explaining deferrals in person reduced the risk that good teams would read the decision as a judgment on their work.

Review

The portfolio will be reviewed quarterly. If the conversion program finishes Wave 1 early, E can start in the second half of the year.

Conclusion

Red River's portfolio decision began with the mandatory regulatory work, screened and scored the discretionary candidates, applied the true constraint of engineering capacity and checked balance and risk. The result funds five discretionary projects, sequences one behind the conversion program's key milestone and defers two, with the trade-offs stated. The process is structured, but as research suggests, it also relied on discussion and judgment, which is where the final sequence was decided.

References

Archer, N. P., & Ghasemzadeh, F. (1999). An integrated framework for project portfolio selection. International Journal of Project Management, 17(4), 207-216. https://doi.org/10.1016/S0263-7863(98)00032-5

Kester, L., Griffin, A., Hultink, E. J., & Lauche, K. (2011). Exploring portfolio decision-making processes. Journal of Product Innovation Management, 28(5), 641-661. https://doi.org/10.1111/j.1540-5885.2011.00832.x

Martinsuo, M. (2013). Project portfolio management in practice and in context. International Journal of Project Management, 31(6), 794-803. https://doi.org/10.1016/j.ijproman.2012.10.013