Is it better for a project estimate to be precise or accurate?
It’s my experience, over hundreds of AV integration projects and hundreds more in numerous industries, that most people believe a precise estimate is more accurate — and that most of the time, “precise” and “accurate” are considered synonymous.
So let’s look at the science of estimation and dispel some myths and confusion about what makes a ‘perfect project estimate.’
First, let’s define some terms: Precision typically means a degree of reproducibility or exactness; whereas Accuracy is a degree of probability or veracity.
Most people think that a precise (exact) estimate must also be the most accurate (or predictable).
But nothing is further from the truth, especially when it comes to AV (or other) projects.
That is because projects occur in the present but mostly the future, and they always have some level of uniqueness, whether that uniqueness be the client, purpose, equipment, parts, venue, location, project team or other subcontractors. And it’s this uniqueness — as well as the uncertain prospect of project risks — does not allow for precision, no matter how much we desire it.
The less certainty we have, the more our ‘perfect project estimate’ must include a measure of variance.
Precision, therefore, is truly unattainable.
But if we’re still looking to create an accurate estimate, we need to understand four interrelated facets that make up the estimation process: Assumptions, Methodologies, Presentation and Tracking/Analyzing.
We will explore each of these facets in this four-part blog series on project estimating.
Defining Assumptions in the Estimation Process
In a previous blog post, we discussed project assumptions and risks in detail.
In a nutshell, assumptions are conditions that project stakeholders (client, general contractor, sales, project manager, implementation team, etc.) believe are true now or will be true at some future point in time. These conditions form the basis of an estimate and often become driving factors in its determination.
To make it through each and every day, we routinely make assumptions to plan our activities, such as figuring the amount of time needed to go somewhere (grocery shopping, work, etc.), determining how long it will take to complete a weekend “to-do” list, or estimating how much a vacation may cost.
These assumptions are often based on our belief that past experiences will somehow shape future ones, especially if the future contains similarities to the past (such as our commute to work, which may have been the same for years). Although we might not think we’re making assumptions (some would say we’re “using common sense”), we definitely are and it’s often based on each person’s experience and creates the context in which each person makes decisions.
You’ve probably heard the saying, “When you assume, you make an a** out of u and me.” But that saying and its interpretation are among the major causes of poorly estimated and subsequently failed projects. A more powerful and proactive saying would be, “Undocumented and uncommunicated assumptions make an a** out of u and me.”
Assumptions are essential, and they form the basis of the plan. A project shouldn’t start without assumptions being documented and shared amongst the stakeholders.
“Assumptions are essential, and they form the basis of the plan. I often say assumptions are the paper the plan will be written on.”
This is because projects are, by nature, forward-looking endeavors that are a combination of similarities and uniqueness. The more similarity, the more we can use our past experiences to plan for the future in a predictable fashion. The more uniqueness, the more we have to make qualified guesses about what may occur in an uncertain future.
How do assumptions factor into creating the perfect project estimate?
Let’s break down a typical commute to work.
Recently, I was with a client and asked her how long it took her to get to work in the morning and how long she’d been driving that same route.
“Seven minutes – and I’ve been commuting for 10 years,” she said.
“Seven minutes? Every day?” I asked. She said, “Yes, every day.”
“Really? No variance at all?” I asked.
“Well, anywhere between 5 and 10 minutes, with an average of 7 minutes,” she said.
Then I asked her another question, assuming she drove the same route every day: “Do those 5 to 10 minutes cover every commute?”
Her answer: “Same route every day, 95 percent of the time it takes only 5 to 10 minutes; 5 percent of the time it can be as high as 15 minutes.”
Sound familiar? Let’s take a closer look at this scenario.
Each individual commute is a recurring operation and going to work every day for a decade provides us knowledge and high degree of certainty about the drive’s characteristics. 10 years of driving the same route results in approximately 2,000 past data points, which can be used to predict the future with some level of certainty.
She initially gave me an exact number, which was a number she averaged, but potentially never hit exactly. Looking at variance, 95% of the time she was between 5 and 10 minutes, and she averaged 7 minutes, with the variance being approximately -30% and +43% (at 95% probability).
Considering that the commute sometimes took her 15 minutes, you have a variance from -30% to +114% at 100% probability.
What’s amazing to me is that when we actually measure operations (things we’ve done the same way thousands of times) we find that they often have much more variance in them than our project estimates do, even though our projects always contain uniqueness and uncertainty. That’s something to think about.
What conditions impacted her drive? She identified three factors that impacted her commute before she ever left her house: day of the week, time of day, and weather conditions. And there were three factors that could impact her drive along the way: a school bus stop, a railroad track crossing, and one potentially busy intersection.
Think of the three in-drive factors as project milestones – points in time where we can firm up our estimate based on what occurred at that milestone.
Risk events may also enter this scenario: traffic accidents, traffic light malfunctions, a train passing which stops traffic when we arrive at the crossing, etc. These risk events have the potential to impact her drive time based on their occurrence and the magnitude of their impact (a fender-bender vs. an injury requiring an ambulance; a long train vs. short train).
In order to make a more precise (less variant range) estimate, we would have to make assumptions based on those six determinant factors and an assessment of the probability and impact of the identified risks.
We could say, for example, that she can drive to work in 5 to 7 minutes on a sunny Tuesday, when she leaves between 7:15 and 7:30 a.m., and doesn’t encounter school buses, trains, nor traffic at the intersection, nor any accidents. We’ve made six assumptions plus a risk assessment that help us narrow the estimate and make it more precise.
If we want a project estimate with a very narrow range, we must document the assumptions within the Proposal / Scope of Work and get the Client to sign off on those assumptions – thus transferring the risk to the Client when they prove false.
Will these assumptions and risk assessment prove to be true?
And what happens when they’re not?
Stay tuned for Part II of this series when we discuss Methodologies for Estimating.