Question

Chapter 3 – Program Management Case Study

Minnesota State University (MSU), a large state college in Mankato, Minnesota, 30 miles southwest of the Dallas/Fort Worth metroplex, enrolls close to 15,000 students. In a typical town–gown relationship, the school is a dominant force in the small city, with more students during fall and spring than permanent residents.

A longtime Division II football powerhouse, MSU is a member of the Northern Sun Intercollegiate conference and is usually in the top 20 in Division II college football rankings. To bolster its chances of reaching the elusive and long-desired number-one ranking, in 2014, MSU “re”-hired Todd Hoffner as its head coach.

One of Hoffner’s demands on rejoining MSU had been a new stadium. With attendance increasing, MSU administrators began to face the issue head-on. After 6 months of study, much political arm wrestling, and some serious financial analysis, Richard Davenport, president of Minnesota State University, had reached a decision to expand the capacity at its on-campus stadium.

Adding thousands of seats, including dozens of luxury skyboxes, would not please everyone. The influential Hoffner had argued the need for a first-class stadium, one with built-in dormitory rooms for his players and a palatial office appropriate for the coach of a future NCAA Division II champion team. But the decision was made, and everyone, including the coach, would learn to live with it.

The job now was to get construction going immediately after the 2015 season ended. This would allow exactly 270 days until the 2016 season opening game. The contractor, Towns Construction (Randy Towns being an alumnus, of course), signed his contract. Randy Towns looked at the tasks his engineers had outlined and looked President Davenport in the eye. “I guarantee the team will be able to take the field on schedule next year,” he said with a sense of confidence. “I sure hope so,” replied Davenport. “The contract penalty of $10,000 per day for running late is nothing compared to what Coach Hoffner will do to you if our opening game with crosstown rival Southwest Minnesota State is delayed or canceled.” Towns, sweating slightly, did not need to respond. In football-crazy Minnesota, Towns Construction would be mud if the 270-day target was missed.

Back in his office, Towns again reviewed the data (see table below) and noted that optimistic time estimates can be used as crash times. He then gathered his foremen. “Folks, if we’re not 75% sure we’ll finish this stadium in less than 270 days, I want this project crashed! Give me the cost figures for a target date of 250 days—also for 240 days. I want to be early, not just on time!”

Minnesota State University Project

Activity	Description	Predecessor (s)	Optimistic	Likely	Pessimistic	Cost/Day
A	Bonding, insurance, tax structuring	—	21	27	45	$1,500
B	Foundation, concrete footings for boxes	A	20	60	70	3,500
C	Upgrading skybox stadium seating	A	50	60	100	4,000
D	Upgrading walkways, stairwells, elevators	C	30	50	100	1,900
E	Interior wiring, lathes	B	25	30	35	9,500
F	Inspection approvals	E	1	1.5	2	0
G	Plumbing	D, F	25	30	35	2,500
H	Painting	G	10	20	30	2,000
I	Hardware/AC/metal workings	H	20	25	60	2,000
J	Tile/carpet/windows	H	8	10	12	6,000
K	Inspection	J	0.5	1	1.5	0
L	Final detail work/cleanup	I, K	20	25	60	4,500

Discussion Question

If it is necessary to crash to 250 or 240 days, how would Towns do so, and at what costs? As noted in the case, assume that optimistic time estimates can be used as crash times.

Please show all steps

Answer 1

Pgnost Answeri Now Here, we get, Activity Predecesogo optimistic Likely Pesimestic cost/Day Dugation Variance 16.00 А 21 27 45 15oo 29 B А 20 60 70 3500 55 69.44 с C A A 50 100 4000 65 69.44 D С C 30 50 100 1900 55 136-11 B 25 30 35 9500 30 278 E F 1.5 2 105 0.03 G D,F 25 30 3.5 2 500 30 278 H G 10 20 30 2000 20 ll.ll I H 20 25 60 2000 30 44.44 J J H 8 10 12 6000 0.44 10 1 K K 0.5 l 1.5 0 0.03. प J IK L ㄴ 20 25 60 4 500 30 44.44 variance variance 397.06 → Now Here, we do that below. The Reduction to 250 days [cost = $15000] 270 - 250 Probability =1.0036 v0.8418 = 84.13 0397.06 % Reduction to to 240 days [cost = $15000 + $19000 = $34. 270 - 240 prob 1.57 50.934.5 93.45 %