Posts Tagged ‘EMV’

Project Reality Check #5: The Devil is in the Details

by Gary Monti on January 19, 2011

Expected Monetary Value (EMV) connects the customer with the team, as we saw in the previous blog. This tool is very powerful. The numbers are as serious as a heart attack (the reason will be shown later). This blog addresses the mechanics of the EMV model providing a whirlwind tour of the associated calculations.

Remember, the goal is getting the team more power to help the client by tying risk with quality and projecting changes in performance corresponding to changes in the risk terrain.

Probabilities and Closed Systems

At the core, an EMV calculation comprises probability times impact to get a weighted number:

10% (probability) x $1000(impact) = $100(EMV)

Let’s put it to use in a closed system.

CLOSED SYSTEMS. In closed systems the probabilities add up to 100% (summation rule) and options are mutually exclusive which is also referred to as being mutually dependent. For example, if you toss a die there is a 1 in 6 chance of getting a “1.” If you get a “1” that also means you did not get 2, 3, 4, 5, or 6.

EMV calculation. Here’s an example that also brings in financial consequences. A vendor has a 70% chance of needing to do rework and it will cost you $1000 extra. The other 30% of the time the work is as expected with $0 added cost. The total probabilities for this system are 100% (70 + 30). Now, the expected value for this system is;

(.7 x $1000) + (.3 x $0) = $700.

Let’s make it a little more complicated. Say there’s a 70% chance the vendor needs to do rework costing $1000, 20% chance the work is as expected at $0 cost, and a 10% chance the vendor design exceeds customer expectations and you get a $2000 bonus (cost reduction). The percentages for this system add up to 100% (70+20+10). The expected value for the additional cost to this system is now:

(.7 x $1000) + (.2 x $0) + (.1 x -$2000) = $600 + $0 – $200 = $500.

Open Systems And The EMV Model

An open system has a set of four calculations providing context for making decisions:

  • Baseline
  • Total Project EMV
  • Worst Case
  • Best Case

These provide a range of numbers with the Best- and Worst Case being the bookends and the Baseline and Total Project EMV lying in between. Let’s define an open system and jump into the calculations.

OPEN SYSTEMS. Imagine 3 dice. The summation rule applies for each die but the dice are independent of each other and move freely. In other words, you can still get a “1” on dies B and C even when there is a “1” on die A. Substitute “subcontractors” for “dice” and the stage is set to continue on to the calculations!

Baseline. The baseline sums the costs across the WBS (work breakdown structure). Here’s an example:

You are to provide a circuit board for your client using three subcontractors using the following estimates:

The firmware contractor, Dewey, Cheatum, and Howe, estimates $50,000.

The software contractor, Karen Sympathy, estimates $100,000.

The board manufacturer, Flyby Knight, estimates $80,000.

The Baseline simply sums the estimates:

($50,000 + $100,000 + $80,000) = $230,000

Total Project Expected Monetary Value (TPEMV). The TPEMV combines the baseline with any needed reserves to achieve the desired quality and delivery date. Imagine you are trying to determine what your risk reserves should be in order to protect the margin on the project while meeting the desired quality:

  • The firmware contractor, Dewey, Cheatum, and Howe, has a 50% chance of needing $5,000 extra to achieve the desired quality;
  • The software contractor, Karen Sympathy, has a 90% chance of performing adequately for $10,000 less than the estimate;
  • The board manufacturer, Flyby Knight, has a 70% chance of trying to squeeze you for and additional $10,000 to get the desired quality and delivery date.

The question is, “How much extra money should you add to your fix fee bid to make sure the margin is protected?” Here’s how to do it:

For Dewey, Cheatum, and Howe there is a need for an extra (.5 x $5000) or $2500.

For Karen Sympathy there is some cushion to the tune of (.9 x $10,000) or -$9,000.

For Flyby Knight these is need for an extra (.7 x 10) or $7,000

The net of this is $2,500 – $9,000 + $7,000 = $500 in risk reserve.

TPEMV = Baseline + risk reserves = $230,000 + $500 = $230,500.

Worst Case. But what if everything bad that could happen actually did? In that case you need to do a Worst Case calculation and do 100% calculations for the threat and 0% for the opportunity, i.e., leave Karen Sympathy out and assume the worst for Dewey, Cheatum, and Howe and Flyby Knight.

Increase your bid by (100% x $5,000) + (100% x $10,000) or an extra $15,000.

Worst Case = Baseline + 100% threats = $230,000 + $15,000 = $245,000

Best Case. The Best Case leaves out the threats and adds in the opportunities at 100% or (100% x -$10,000) = -$10,000 for Karen Sympathy. The bid then changes to:

Best Case = $230,000 – $10,000 = $220,000

This has been brief. If you have any questions feel free to contact me. The EMV model is a great way to connect with stakeholders and work rationally while keeping relationships intact.

Oh, about that heart attack. The Securities and Exchange Commission (SEC) was founded during the Great Depression because people offering stock for sale only showed the Baseline and Best Case numbers and a more robust model was needed – the EMV model. Risks and reserves have to be reported. Unfortunately, we are climbing out of a repeat of the same situation caused by ignoring the model.

Project managers (PMs) have to deliver; yet power to get the job done can be elusive. Is there a way PMs can take care of themselves and the team knowing they are lower on the food chain? Can they get some power? Yes. How so? Let’s explore.

Portfolios, Programs, and Projects

First some background. A simple, common hierarchy with a current situation in the transportation industry is:

Location Position Example
External Client EPA
Internal Portfolio Mgr internal combustion engine
Internal Program Mgrs gasoline diesel
Internal Project Mgrs 1000cc 3000cc 4000cc 5000cc

The “client” in this case is the external regulatory agency. The deliverable is a reduction in emissions for the various types of engines a manufacturer produces with standards varying based on the displacement and fuel consumed. We’ll look at the client after examining the internal organization.

Internally, working from the top-down, there is a progression from strategic (market position, profits, etc.) to the tactical/tangible (every engine coming off the assembly line has to meet stringent requirements within the next few years). Teams in the internal combustion industry are feeling the heat with pressure coming down from above. Deadlines and goals have been set.

To maintain a healthy balance in this situation PMs will do best understanding and communicating in the language used by those with more strategic positions and power. This language also needs to provide a portal through which the PMs can express project concerns. The language is risk management.

Now, shift focus to the client. It is through the client the PM can gain influence – better known as power. The connection between the PM and the client is quality. As the old saying goes, “The proof of the pudding is in the eating.” Again, each engine needs to perform per regulatory limitations.

So, in a way, the PM has a direct connection with the client through quality. It is important to avoid being Pollyannaish and think the PM has the power baton of the client. The situation is subtler. This is where risk management comes into play.

By understanding how the performance of the deliverable is impacted by quality the PM can gain leverage communicating through the business case. How? The PM uses a specific aspect of risk management – Expected Monetary Value (EMV). EMV can take quality, time, and money and combine them into one model – a model understandable to both the business unit and project team. A good EMV model tells how good or bad things can get in the current risk environment and points to areas where changes (time, money, resources) are needed.

This seems a bit roundabout if quality is the focus. So, why do this? Simple. There can be an intrinsic desire for quality in an organization. That desire, though, can vary in commitment from organization to organization as well as within an organization.

On the other hand, the focus on time and money is pretty much universal and that is the context in which quality sits – always the bridesmaid, never the bride. EMV flips the situation and addresses time and money squarely in the context of quality looking to see how stable and acceptable the deliverable will be in various risk environments.

Consequently, EMV models can help bridge client power to the team’s need to perform and cross over the obstacles of time, money, and resource constraints by showing how squeezing the team too tightly or working in the current risk environment could hammer profits and viability in the long run.

With the stage set, in the next blog some of the specifics of the EMV model and how it works will be addressed.