strategic planning

Let us conduct a psychological experiment. Which formula do you think will yield a more precise and accurate result:

or

I guarantee that the majority of the readers will select the second formula as the one that would provide the best result. Unfortunately nothing can be further from the truth because any formula is as good as the data going into it. Some of you may have heard the following expression used by statisticians:

Garbage in, garbage out

It basically means that, no matter how complicated the formula is, if you “infuse” it with inaccurate data, the model will produce an inaccurate answer. Having said that take a closer look at the formulas above: the first model only has two ingredients, while the second one has multiple variables. Hence with a larger number of variables we end up with more room for estimation errors.

Why did I start this article with such a strange example? I have recently taught a project portfolio management course in London, UK and the following conversation took place between a Portfolio Manager of a large utility company and your humble servant:

PM: Oh, our executives will never sign up for PPM. We tried it before and it didn’t work

Me: Why didn’t it work?

PM: Well take a look here … (proceeds to show me a very complicated spreadsheet that incorporates not one, not two, but three scoring models for different types of projects at the same company. In order to assess the project proposal one has to answer several dozen questions by selecting appropriate choices from the dropdown menus. Once the choices are made, the spreadsheet “tells” you which scoring model to use. The models are also far from simple; close to a dozen scoring categories with five different potential scores for each variable …)

Me: So, did you use that model?

Very frequently when teaching my Project Portfolio Management Masterclass I get asked the following question:

One of our major challenges is assessing the size of our resource pool.  No matter how meticulous our calculations are, we constantly end up with way more projects than we can handle! Sometimes we are talking orders-of-magnitude errors in estimation!

So, here is an example of a "back of the envelope" calculation of total project resources bucket at a company that has proven to be extremely robust.

Imagine that there are 250 employees working at the head office. It has been estimated via survey or questionnaires that approximately 30% of their time is spent on project work and 70% on business as usual, i.e. normal daily non-project tasks. Based on that information we can assess the size of the total project resource bucket at the company:

Total number of people at the head office = 250 people

Total number of working months in a year = 10  minus two months for vacation, holidays and sick days)

Percentage of time spent on projects = 30% (estimated based on surveys)

Thus:

Total Project Resource Pool = 250 people X 10 months X 0.30 = 750 person-months

Therefore the total project human resources available for the entire portfolio are 750 person-months. Using this figure and knowing that there are 12 months in a year we can calculate the approximate resource pipeline throughput at the company as follows:

Project Pipeline Capacity = Total Project Resources/Number of Months in a Year = 750 person-months/12 months = 62.5 person-months/month

 

In other words the total project resource requirements at the organization should not exceed 62.5 person-months in any given month.

So, here is my traditional multiple-choice question for you:

How do you measure your portfolio resource pool?