“How long does it take to go to the airport?”
This is a question my out-of-town guests frequently ask. I suppose they want to budget enough time for their taxi or Uber trip to avoid missing their flight home.
I live in Chicago, Illinois. Both my residence and office are downtown, less than two blocks away from each other. I travel a lot for business and most of my trips require domestic and international plane travel.
Over the last two decades I must have made at least 25 round trips a year between home and Chicago’s O’Hare International Airport. So I’m considered to be a subject matter expert (SME) on travelling between downtown Chicago and O’Hare; hence, why I am frequently asked how long it takes to get to the airport.
“It depends,” is how I start my answer. I don’t mean to be a smart aleck or non-committal. How long it takes of course depends on many “normal” conditions such as the day of the week, time of day, traffic light patterns, etc., not to mention specific uncertain events like snow, construction work, and major accidents.
I follow up my initial evasive answer with a specific one. “Most likely 30 minutes if there is no snow, construction, major accidents, and things like that.” But when my guests make the actual trip, it’s unlikely that it’ll take exactly 30 minutes. Often it takes longer but occasionally it is quicker. It could take as long as 77 minutes and no less than 22 minutes.
Are these numbers real or my guess work? Actually, I analyzed real data from 100 consecutive Uber trips. I excluded data from trips when there were specific afore-mentioned events. The reason for that is I did not want to account for uncertain events that may or may not happen in a given trip. I only wanted to account for uncertainty that’s virtually guaranteed on any trip because of “normal” conditions. (Two of my previous blogs address risks caused by specific events including “unknown unknowns” and “known unknowns.”)
What’s the potential risk this uncertainty may cause? My guest won’t be too pleased if I simply said it’d most likely take 30 minutes for the trip, but it actually ended up taking 60 minutes or even more. Even worse, they’d be upset if they missed the flight altogether. On the other hand, if I share the key points of my data, they have better insight into the trip variability and can better manage the risk of missing their flight.
Variability risk in projects
The non-event risk created by the virtually 100% uncertainty associated with the estimated value of a parameter is called variability risk. You may estimate it to be X, but the actual value will likely be higher or lower. It may also turn out to be exactly the same, but the chances are slim.
For example, in planning a project, you may estimate the cost of an activity to be $X, but when it’s completed, the actual cost will be different or in a few cases EXACTLY the same. This is true for the duration of an activity, resource productivity, and any other individual project activity estimate. The uncertainty of the estimates of various activities can collectively create variability risk for an overall estimate such as project cost or duration.
Whereas the variability risk is virtually 100% certain, what’s uncertain is its magnitude. The project team’s objective is to minimize the uncertainty, thereby minimize the variability risk, so you can complete your project as close to the original cost and schedule estimates as possible. You may achieve it by following a structured process.
Define scope of work clearly
The first key step is to clarify project requirements and define the scope of work as clearly as possible. The more detailed the scope of work is, the lower the uncertainty (and the variability risk) with your cost and schedule estimates.
If you only know that you want to build a house on a given parcel of land with three levels including basement, four bed rooms, three full-baths, a three-car garage, 3,000 sq ft of living area, etc. your estimates will have high uncertainty. And you’re more likely to exceed your budget. But on the other hand, if you start with a detailed design of the house and a highly specific bill of materials, the uncertainty will be low and the likelihood of meeting your budget target high. This is pretty much commonsense but most commonly forgotten.
Estimate uncertainty
In my airport trip example, I collected actual data to estimate the uncertainty. I calculated the most likely, minimum, maximum, and average values. I plotted the data to see if the values are normally distributed (bell curve) or followed some other distribution. (Without getting too technical, “pert” distribution showed the best fit.)
Obviously, we cannot do such an experiment on our real world project activities. Therefore, to define the uncertainty, let’s consult with SMEs with experience and the team members responsible for performing the actual work.
Being an SME on Chicago airport trips, even if I had not statistically analyzed actual trip duration data, I could estimate the uncertainty fairly accurately. These estimates can be expressed in terms of nominal values or as a percentage difference from the most likely value (for example, +X% and –Y%).
Analyze and prioritize sources of uncertainty
Once you’ve assessed the uncertainty associated with an estimate, analyze its impact on the overall project cost and schedule. Some project activities will have more impact and others less.
You can prioritize the activities based on simple qualitative estimation of their impact (for example, low medium, high). Or it can be based on quantitative tools involving Monte Carlo simulations, coupled with sensitivity and what-if analyses.
Decrease uncertainty
The aim is to decrease uncertainty thereby decreasing the variability risk. Start with the activity that has the highest risk on your priority list and work your way down. You may want to avoid, if at all possible, the high priority risks at the top of the list and accept/ignore the ones towards the bottom. For the middle of the pack, you may consider mitigation by decreasing the uncertainty.
As an example, if the cost uncertainty and impact are very high with a time-and-materials contract for a particular project activity, you can virtually avoid the risk by using a fixed-price contract that carries almost no cost uncertainty. If the duration of an activity on the project’s critical path has high uncertainty that could potentially result in significant project schedule slippage, you may be able to remove it from the critical path by changing the sequence of activities or dependencies.
Set schedule and budget targets as ranges
Executives want projects to be completed without exceeding a specific target schedule and budget. But it’s unlikely for teams to deliver on the EXACT targets due to variability risk. So instead of agreeing to an exact schedule and budget, good management practice is to set targets as ranges.
As an example, the project target cost can be $1 million +/-10%. But the range could vary based on the amount of uncertainty associated with the estimates, which as we said before is a function of the level of clarity of the work scope. So, for instance, you may consider a broader range for research/development projects and a narrow range for capital projects.
When executives are aware of the uncertainty and risks associated with project estimates, they can manage their project and portfolio budgets and schedules better—like my guests can better manage their time knowing the uncertainty surrounding their trip to the airport.
In the next blog, I’ll summarize the four types of risks I’ve talked about in my last four blog posts.
[…] In the next blog, I’ll look at another type of risk—variability risk. […]