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Estimating the probabilities of success for your projects is necessary for calculating the expected value of a project and is an essential part of project portfolio management (PPM). Unfortunately, most project managers and project management offices (PMO) don't do this very well. They could learn to do it better by looking at how meteorologists predict the probability of rain.

So, just what does it mean when a meteorologist says "the chance of rain today is 60%?"

Each day in the United States, a massive amount of data is collected from weather stations, satellites, and weather balloons from around the world and sent to the National Meteorological Center near Washington, D.C. The data is processed to give a multi-dimensional picture of global atmospheric conditions, and then it is analyzed using various algorithms to develop local weather forecasts and predictions.

But this isn't how they make the "percent chance of precipitation" predictions. Even with the massive amount of data and super computer speed, their predictive algorithms alone just aren't good enough. So they use comparisons to historical data.

Basically, they take the current atmospheric conditions and compare them with days in the past that had very similar conditions. So when they say that "the chance of rain today is 60%," it means that it rained on 60% of the days in the comparison set.

And guess what? Assuming the data was entered properly, these predictions are 100% reliable all the time. Why? Because they are only predictions of probability - they aren't "wrong" on a particular day, whether it rains or not. But whether they are accurate or not in the long term is an entirely different question.

The only way to determine if the predictions are accurate is to collect the data and plot the actual versus the predicted conditions over time to learn the margin of error. If it only rained on 30% of the days that the prediction was 60%, then there is a problem with the data or the data processing.

You can do the same type of probability prediction and testing with your business projects, too. The more accurate your estimates, the more confidence you will have in your overall project-value ranking in your project portfolios.

Developing more accurate project risk estimates requires 4 basic activities:

1) Identifying the key drivers of cost, time, and resource risks in completing project tasks.

2) Preparing a database of these tasks that includes the corresponding cost, time, and resource estimates assigned to each project and the basis for those estimates at the beginning of the project.

3) Tracking the actual costs, times, and resources used performing the task as each task is completed.

4) Comparing the actual costs, times, and resources with the starting estimates.

After you have maintained this database for your project portfolio for a period of time, you will be able to plot the actual versus the predicted results. This plot will show you the accuracy of your cost, time, and resource estimates as well as revealing the distribution of the actual results. (You will probably learn that your cost estimates were too low, your time estimates were too short, and your resource estimates were for too few. And that is a good thing to learn.) Eventually, you will be able to use the actual results data as a basis for future probability predictions because patterns will emerge. The data will also give you an understanding the uncertainty in those estimates.

I saw the data of one major pharmaceutical company who did this for their project "percent probability of success" estimates over a number of years. The data between 20 and 85% was surprisingly linear; for example, about 50% of the projects that had "percent probability of success estimates" of 50% were ultimately successful. It also showed that all projects that had an estimated "percent probability of success" of 85% or greater succeeded and all that had an estimate of 20% or less failed.

If you're involved in project portfolio management and you're looking for ways to improve your project planning, compiling and analyzing your historical data is a great way to test and improve your future estimates.

DataMachines.com offers a project portfolio management software tool called Optsee® for calculating project and project portfolio value even with uncertain data. By automatically analyzing your project portfolio in thousands of scenarios using easy-to-run Monte Carlo simulations and then optimizing against multiple constraints such as limited funding and resources, Optsee® quickly shows you your best, worst, and most-likely returns from an optimal portfolio.

Data Machines also offer a spreadsheet workbook for easily calculating the return on investment (ROI) for any project portfolio management tool.

About the Author: George F. Huhn, President of Data Machines, Inc, founded the company in 2000. Data Machines offers business applications and consulting to help businesses improve their performance through superior project portfolio valuation and optimization. George has authored or co-authored numerous papers and articles in publications ranging from The Journal of Organic Chemistry to Newsweek, and has delivered seminars and keynote addresses at events across the country. He also holds several U.S. patents, and has been written about in Chemical and Engineering News.

He holds an Executive Masters of Science degree in the Management of Technology from the Wharton School and the University of Pennsylvania. He is also a Moore Fellow in Technology Management at the University of Pennsylvania's School of Engineering and Applied Science, and holds a B.S. degree in chemistry from Drexel University.

Alonso Wins The Monaco Grand Prix - Again

Spain's Fernando Alonso and Britain's Lewis Hamilton achieved first and second for McLaren in the 2007 Monaco Grand Prix.

Alonso started from pole position and achieved the fastest lap time, and for most of the 78 lap race kept a three or four second lead over team-mate Lewis Hamilton. Monaco was Alonso's 17th Formula 1 victory.

With five races in this year's F1 Championship now gone, Spaniard Alonso and Brit Lewis Hamilton share the lead in the drivers' championship with 38 points each, with the next two races scheduled for Canada and the US.

In his first F1 season, Lewis Hamilton has now achieved five podium finishes from five races, extending his record winning run. And although tipped by some commentators to win this year's Monaco GP, Alonso's fluent driving kept him at bay throughout the race.

Fellow Brits - and Monte Carlo residents - Jensen Button and David Coulthard finished the race outside of the points and well down the field, a disappointing result particularly for previous winner Coulthard, who was on the podium to receive his third place trophy in last year's Monaco GP.

David Coulthard is part owner of the Columbus Hotel, in the Fontvieille district of Monaco.

Robert Kubica in a BMW, who like Hamilton was making his debut at Monaco, achieved an impressive fifth position, ahead of team-mate Nick Heidfield.

Appropriately named American Scott Speed was another driver who will leave Monaco happy, having climbed from 18th on the grid to finish 9th.

The final positions were:
1. Alonso (McLaren)

2. Hamilton (McLaren)

3. Massa (Ferrari)

4. Fisichella (Renault)

5. Kubica (BMW Sauber)

6. Heidfeld (BMW Sauber)

7. Wurz (Williams)

Speaking after the race Alonso said 'It has been a fantastic weekend, no doubt, and to score this hat trick of pole, fastest lap and win is something very special and even more here in Monaco. I enjoyed very much today's race, with a perfect car all through the race. It was so good to drive such a nice car for 78 laps and win at the end.'

Lewis Hamilton commented, 'I knew we were both extremely quick, so I could only apply pressure, but he's a two-time world champion and he doesn't really make mistakes.'

The Grand Prix is 77 laps around the narrow, winding streets of Monte Carlo, making the Monaco Grand Prix the most exciting in the world, with little room for driver error.

Since the first Grand Prix on April 14 1929, organised by Monte Carlo resident and founding president of the Automobile Club de Monaco Antony Noghes, the average fastest speed has risen from 50mph (80 kph) to 88mph (143 kph).

The 2008 Monaco Grand Prix will be held on Sunday 25 May.

About the Author

YourMonaco.com is a travel guide for Monaco and Monte Carlo, and includes details of hotels in Monte Carlo
, how the renowned Monte Carlo casino is shaping up to the competition of online casino operators and has Monaco bank information.

does any 1 knows the speed of ftball kicked by robberto carlo (full ;power)?

apparently not

Calling Nadal a clay specialist is not an insult
Tennis.com: While Rafael Nadal has enjoyed success on other surfaces as well, clay courts highlight the particular beauty of his game. It's not demeaning to say he's a clay-court specialist, because it is special to watch him play on his favorite surface.

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