ADMS 1000 Lecture Notes - Lecture 43: Dj Controller

Case : Multi Projects Inc (Page 452 -454) Successful Project Management 6th Edition (Clements & Gido)

Case Study 1 Multi Projects

Multi Projects, Inc., is a well established consulting firm with 400 employees. It has many projects going on at the same time for various clients. Multi Projects has a good reputation , and nearly 30 percent of its business is from previous clients. It targets growing companies for future business and has been successful in this, too. Because of the growth, things have been quite hectic, with employees trying to keep up with the work, keep old clients satisfied, and bend over backward to accommodate new clients. Multi Projects has been hiring new employees-in fact, it has grown from 300 to 400 employees over the past two years.

Multi Projects has a matrix organizational structure. As new projects come in, a project manager is assigned. One project manager may be assigned to several projects at a time, depending on the sizes of the projects. Projects range in value from $20,000 to $1 million and can be from one month to two years in duration. Most projects are about six months in duration and worth about $60,000 to $80,000. The firm performs a range of consulting services, including market research, manufacturing system design, and executive recruiting. Its clients are medium to large corporations and include banks, manufacturers, and government agencies.

Multi Projects just got a call from Growin Corporation, which wants to go forward with a project that Multi Projects proposed nearly six months ago. Partners at Multi Projects are surprised by the good news. They had thought the project was dead. They are also very interested in carrying out a first project for Growin Corporation because it is a rapidly growing company. Multi Projects sees an opportunity to do several projects with Growin Corporation in the future.

Jeff Armstrong has been assigned as project manager for the Growin Corporation project. He has been with Multi projects far about a year and has been anxious to get a challenging project to manage. He worked on the proposal for the Growin project.

Tyler Bonilla is a senior systems engineer. He has been with Multi Projects eight years. He has an excellent reputation, and previous clients with whom he has worked usually request that he be assigned to their projects. He enjoys his work, even though he is extremely busy. He is currently working full time on a project for Goodold Company, a previous client. Goodold said that one of the reasons it does business with Multi Projects, rather than with another consulting firm, is the great work Tyler does on their projects.

Jennifer Fernandez is the manager of systems engineering. She has been with Multi Projects about 15 years. Tylet reports to Jennifer, but because of his heavy workload and associated travel, he does not get to see Jennifer very often, other than at her monthly staff meetings.

Julie Capriolo is the project manager for the Goodold Company project. She has been with Multi Projects for about two years. Tyler is assigned to her project full time. The project has a tight schedule, and everyone is putting in extra hours . Julie feels a lot of pressure, but she has a good project team--she relies heavily on Tyler. She had heard from a friend who used to work with Jeff that Jeff is very ambitious and will do whatever it takes to make himself look good. This had not been of concern to Julie because she and Jeff have separate projects and do not run into each other very often.

The day Jeff is assigned to be project manager on the Growin Corporation project, he runs into Tyler in the hallway. "We got the Growin project," he tells Tyler.

"Great," responds Tyler.

Jeff continues, "You know, one of the big reasons they gave the project to us rather than another consulting firm is because we promised you'd be the lead systems engineer on the project, Tyler. They were impressed with you when we met with them to present our proposal. When do you think you can start work on the project:"

"Unfortunately, I can't. I'm tied up on the Goodold project, and things are really hectic. I'll be on the project for another four months," says Tyler.

"No way!" exclaims Jeff. "This Growin project is too important to me--I mean, to us. I'll take care of it."

"You'd better talk to Jennifer," Tyler tells him.

Jeff stops by Jennifer's office. She's busy, but he interrupts her. "I gotta have Tyler Bonilla on my Growin project. He wants to work on it, but he said I should talk to you."

"Thats impossible," says Jennifer. "He's assigned to Julie Capriolo's Goodold project for the next four months."

"Julie? Who's she? Never mind. I'll find her and work it out. You probably have somebody else you can assign to her project." replies Jeff, as he quickly bolts out of her office in search of Julie.

"Thats my decision , not yours or Julie's!" shouts Jennifer. But by that time Jeff is gone and does not hear what she says.

Julie is meeting with her project team in the conference room. Jeff knocks on the door and opens it. "Is there a Julie in here?" he asks.

"I am Julie," she responds.

"I need to talk to you ASAP. It's important. Oh, by the way, sorry for interrupting." Looking forward Tyler, who's in the meeting, Jeff says, "Hey, Tyler, catch you later, buddy, after I talk with Julie." Jeff then shuts the door and goes back to his office. Julie is noticeably disturbed at the interruption.

After her meetin, Julie calls Jeff. "This is Julie. What did you want to talk to me about that was so urgent?'

"About reassigning Tyler to my project. He's interested, and I've already talked to Jennifer about it," answers Jeff.

"Thats impossible," declares Julie. "He's critical to the Goodold project."

"Sorry," says Jeff, "but if the Growin project is successful, we'll get more business from them than we ever got form the Goodold Company."

"It's already after 6 o'clock and I have to be out of town for a week, but I'll discuss this with Jennifer as soon as I get back," snaps Julie

"Yeah, sure, whatever," responds Jeff.

The next day Jeff calls a meeting with Jennifer and Tyler. He starts by telling them, "I called this meeting to figure how soon Tyler can begin working on the Growin project and how you [looking at Jennifer] can get somebody to take his palce on what's-her-name's project."

"I think Julie should be here for this discussion," says Jennifer.

"She couldn't make it. Apparently she's out of town for a week, and we need to get going on the Growin project." Jeff tells her. "We need to prepare for a meeting with them next week. Besides, Tyler is the one we're talking about, and he'd rather work on the Growin project. Right, Tyler?'

"Ah, well, now that you have asked, I am getting tired of working on the Goodold projects," replies Tyler. "I'm not learning anything new. I mean, it's okay, but I'd like a change.

Jennifer is astonished. "You never mentioned that to me, Tyler."

Jeff breaks in, "Well, I guess it's settled. Jennifer, you assign somebody else to the Goodold project who'll feel a little more challenged and tell Julie when she gets back. In the meantime, me and my buddy Tyler have got a lot of work to do to look good for our meeting with the Growin people next week."

Evaluate the case and propose a solution. Prioritise the steps to be taken in your approach, be systematic and motivate your assertions.

Total: [100]

What do you believe is the ultimate impact of technology on job creation? Should there be curbs to the pace of modernization?

(Answer in a paragraph(around 200 words))

What Econ 101 Can Teach Us About Artificial Intelligence

Here's why advancing technology often leads to more jobs for humans, not fewer

A Tesla Model X 75D semi-autonomous electric vehicle is parked at the Governor's Mansion in Olympia, Wash., this year. Goldman Sachs predicts that 25 years from now, driver employment will be growing by 300,000 less per year because of autonomous vehicles.

By Greg Ip

Aug 9, 2017

The first chart you draw in Economics 101 is the downward-sloping demand curve. It shows that when the price of something drops, people consume more of it.

This elementary rule of economics is remarkably helpful in discussing the effects of technological change. As I wrote last week, when technology makes something cheaper, we consume more of it, often by finding new uses. This lesson repeats through history: When coal-fueled steam power became more efficient in the 1800s, demand for steam power and coal spread. When automated teller machines made it cheaper to operate bank branches in the 1980s, banks opened more branches.

My column cites spreadsheet programs like Lotus 1-2-3, whose arrival in the early 1980s made repetitive recalculation vastly simpler and faster. This reduced demand for bookkeepers but created more demand for people who could run numbers in new and interesting ways, such as accountants and management consultants.

In a recent article for the Harvard Business Review, Ajay Agrawal, Joshua Gans and Avi Goldfarb, economists at the University of Toronto who study artificial intelligence, say that in the 1990s, economists didn’t buy into the hype that the internet and the World Wide Web would upend everything:

“It wasn’t that we didn’t recognize that something changed. It was that we recognized that the old economics lens remained useful for looking at the changes taking place. The economics of the ‘New Economy’ could be described at a high level: Digital technology would cause a reduction in the cost of search and communication. This would lead to more search, more communication, and more activities that go together with search and communication. That’s essentially what happened.”

They apply that lesson to artificial intelligence and more specifically to machine learning, the use of powerful algorithms to make predictions from patterns in large quantities of data. Machine learning, they say, means many problems will be reframed as prediction problems. Autonomous driving no longer involves programming the car to respond in a certain way to a variety of controlled scenarios, but instead, to watch what humans actually do and then respond the same way.

How does this affect jobs? The authors says it depends on whether the technology competes with or complements what you do. Spreadsheets competed with what bookkeepers do (record keeping and calculation) and thus made them less valuable, but complemented what accountants and consultants do (analysis), and made them more valuable.

Mssrs. Agrawal, Gans and Goldfarb say that AI reduces the value of those who predict things for a living, such as whether a mark on an X-ray is a tumor, but it raises the value of those who use predictions to make judgments:

“When prediction is cheap, diagnosis will be more frequent and convenient, and thus we’ll detect many more early-stage, treatable conditions. This will mean more decisions will be made about

medical treatment, which means greater demand for the application of ethics, and for emotional support, which are provided by humans.”

So AI will create winners and losers within and among industries and occupations. But what will the net effect be? More jobs or less, and for whom? This isn’t knowable, but history suggests that while a specific occupation or industry may suffer losses, the aggregate effects will be positive. The growth in accounting and analytical jobs since the early 1980s is much larger than the loss of bookkeeping jobs.

Nor did all those bookkeepers necessarily lose jobs; many probably became accountants or analysts. As Mr. Gans told me, bookkeepers may have been best placed to exploit the capabilities of spreadsheets: “If you were doing calculations all day as a bookkeeper, chances are you thought a bit about why you are doing that. When you got a spreadsheet, rather than doing one calculation per day you could do 10 to 50, so you had a better sense of what the [calculations] might say.”

Some readers said AI is a much bigger threat than spreadsheets because it has so many more potential applications—and they displace uniquely human abilities. I agree with the first part, less so with the second. I suspect workers in previous eras, whether they drove a horse and plow, handled a stock trade or connected a phone call, thought there was something about their job that a machine could never replace.

Will the disruptions this time around be greater? Maybe, but not necessarily. Goldman Sachs predicts that 25 years from now, driver employment will be growing by 300,000 less per year because of autonomous vehicles. That’s 25,000 jobs per month to make up, compared with the 5,000 per month that the decline in bookkeeping since 1985 represents. But it’s hardly insurmountable in a labor market where five million jobs are created and destroyed each month.

Others said I was ignoring the potential for rogue algorithms and robots to turn on us or strip us of our freedom.

The experts, of which I am not one, tell me AI is nowhere near that capability. (Before the robots can kill us they must first stop killing themselves.) And don’t assume spreadsheets have been all benign. Excel may not have slain anyone Terminator-style, but it did help wound J.P. Morgan through its role in the “London Whale” trading disaster.

Which brings me to the final point. We should not confuse what technology enables us to do with how much better off it makes us. Spreadsheets enabled analysts to construct much more intricate forecasts of stock prices and the economy, but didn’t make those forecasts any more accurate. AI may enable companies to better manage the risks of their products and actions, but those products and actions may not be more profitable. Many a CEO has wondered whether the money they spend on spreadsheet-wielding consultants yields any real value. Some day they may wonder the same thing about their AI-wielding consultants.

Grade inflation Gone Wild - sTUarTrojsTaCzer

A bout six years ago, I was sitting in the student union of a small liberal arts college when I saw a graph on the cover of the student newspaper that showed the history of grades given at that institution in the past 30 years.

Grades were up. Way up.

I am a scientist by training and I love numbers. So when I looked at that graph, I wondered, How many colleges and universities have
data like this that I can find? The answer is that a lot of schools have data like this hidden somewhere. Back then, I found more than 80 colleges and universities with data on grades, mostly by poking around the Web. Then I created a website (gradeinflation.com) so that others could find this data. I learned that grades started to shoot up nationwide in the 1960s, levelled off in the 1970s, and then started rising again in the 1980s. Private schools had much higher grades than public schools, but virtually everyone was experiencing grade inflation.

What about today?

Grades continue to go up regardless of the quality of education. At a time when many are raising questions about the quality of U.S. higher education, the average GPA at public schools is 3.0, with many flagship state schools having average GPAs higher than 3.2. At a private college, the average is now 3.3. At some schools, it tops 3.5 and even 3.6. A is average at those schools! At elite Brown University, two-thirds of all letter grades given are now A's.

These changes in grading have had a profound influence on college life and learning. When students walk into a classroom knowing that they can go through the motions and get a B+ or better, that's what they tend to do, give minimal effort. Our college classrooms are filled with students who do not prepare for class. Many studies less than 10 hours a week that's less than half the hours they spent studying 40 years ago. Paradoxically, students are spending more and more money on an education that seems to deliver less and less content.
With so few hours filled with learning, boredom sets in and students have to find something to pass the time. Instead of learning, they drink. A recent survey of more than 30,000 first-year students across the country showed that nearly half were spending more hours drinking than they were studying. If we continue along this path, well end up with a generation of poorly educated college graduates who have used their four years principally to develop an addiction to alcohol.

Many say that grade inflation is a complicated issue with no easy fix. But there are solutions. At about the same time that I started to collect data on rising grades, Princeton University began to do something about its grade-inflation problem. Its guidelines have the effect of now limiting A's on average to 35 per cent of students in a class. Those guidelines have worked. Grades are going back down at Princeton and academic rigour is making a comeback. A similar successful effort has taken place at Wellesley College in Massachusetts. And through a concerted effort on the part of faculty and leadership, grades at Reed College in Oregon have stayed essentially constant for 20 years.

Princeton, Wellesley, and Reed provide evidence that the effort to keep grade inflation in check is not impossible. This effort takes two major steps. First, school officials must admit that there is a problem. Then they must implement policies or guidelines that truly restore excellence.

I asked Dean Nancy Malkiel at Princeton why so few schools seem to be following Princeton's lead. Because its hard work, she answered. Because you have to persuade the faculty that its important to do the work.

Making a switch will take hard work, but the effort is worthwhile. The alternative is a student body that barely studies and drinks out of boredom. That's not acceptable. Colleges and universities must roll up their sleeves, bring down inflated grades, and encourage real learning. It's not an impossible task. There are successful examples that can be followed. I am looking forward to the day when we can return to being proud of the education that our nation's colleges and universities provide.

Analyze Stuart Rojstaczer's argument in Grade Inflation Gone Wild, addressing the following questions:
What evidence does Rojstaczer use to indicate that there is a problem?
How would you characterize this evidence (for example, scientific, anecdotal), and to what extent are you persuaded by the evidence he provides to suggest that grade inflation has a profound effect on life and learning?
To what extent does he persuade you that a change in policy is
necessary or that such a change would make a difference?