{"id":4504,"date":"2022-09-15T10:00:05","date_gmt":"2022-09-15T08:00:05","guid":{"rendered":"https:\/\/getnave.com\/blog\/?p=4504"},"modified":"2023-03-17T23:15:51","modified_gmt":"2023-03-17T21:15:51","slug":"probabilistic-forecasting-in-project-management","status":"publish","type":"post","link":"https:\/\/getnave.com\/blog\/probabilistic-forecasting-in-project-management\/","title":{"rendered":"Why You Need Probabilistic Forecasting as a Project Manager"},"content":{"rendered":"
<\/div>\n

Hey there, my name is Sonya Siderova, founder and CEO of Nave, and my main goal is to make your job as a project manager more efficient and less stressful. Here at Nave, we do that by sharing solutions to help your teams work smarter (not harder), so everyone can go home happy. <\/em><\/p>\n

If you\u2019re struggling to deliver on your commitments, it may be time to break the status quo and try a new solution. We\u2019ve found a lot of success with probabilistic forecasting and today we\u2019ll explore how it works.<\/p>\n

\u201cTrust your gut,\u201d is usually good advice.<\/p>\n

Except when it isn\u2019t.<\/p>\n

Trusting your gut makes sense when it comes to choosing which size T-shirt to order for your best friend\u2019s birthday gift.<\/p>\n

Trusting your gut is not so great when it comes to project forecasting.<\/p>\n

That\u2019s because (surprise) we humans aren\u2019t perfect, despite our best efforts. We miss deadlines, not because we aren\u2019t trying hard enough, but because it\u2019s actually<\/em><\/strong> quite challenging to gauge how long a project will truly take.<\/p>\n

What\u2019s one of the most reliable solutions, then, to make sure your deadlines are realistic?<\/p>\n

Our choice:<\/p>\n

Probabilistic forecasting.<\/strong><\/p>\n

Now, you might be wondering: \u201cWait, \u2018probabilistic\u2019 sounds like there\u2019s a degree of uncertainty involved\u201d, and uncertainty is definitely something most people aren\u2019t comfortable with<\/a>. How is that any better than relying on your gut or your best guess?<\/p>\n

Good question.<\/p>\n

Let me take a step back and start by sharing with you my super simple secret to a happy marriage (that\u2019s lasted over 10 years now): regular date nights!<\/p>\n

My husband and I have date night every single Friday \u2013 we\u2019ve found that this little ritual is what helps us stay connected with each other, feel close, and escape from the hustle and bustle of the week.<\/p>\n

If you\u2019ve been around for a while you probably already know that I\u2019m a huge fan of Michelin-starred restaurants. As such, most of our dates take place in our favorite place \u201cBar Vaccin\u201d.<\/p>\n

On our most recent date, we took a seat as usual at the bar and enjoyed a couple of drinks while our table was being prepared. This time, the staff gave us something new while we waited: a device that told us how many minutes were left until our table was ready.<\/p>\n

So cool!<\/p>\n

Honestly, we didn\u2019t expect it to predict exactly<\/em><\/strong> when we would be seated, but it ended up being quite accurate. In fact, the table ended up being ready even sooner than we were told (a good thing, considering how hungry and excited I was to taste those first appetizers!).<\/p>\n

Of course, my first response was to talk to the owners of the restaurant to figure out what\u2019s behind that small piece of electronics.<\/p>\n

It turned out that the device worked so well because it relied on past data \u2013 a range of wait times – in order to give us a realistic estimate of when our table would be ready for us.<\/p>\n

Imagine my excitement! And, yes, I\u2019m biased, but I\u2019ll be saying this over and over again. You have to use your past performance data to come up with reliable forecasts, especially when it comes to project management. There is just no other way around it.<\/p>\n

Michelin-starred restaurants are world famous for their impeccable quality and attention to detail. I loved that new initiative and I was really impressed by the approach they\u2019ve taken to bring that place to a whole new level.<\/p>\n

When it comes to project forecasting, you want to use that same principle. Let\u2019s take a closer look at how it works.<\/p>\n

What is Probabilistic Forecasting in Project Management?<\/h2>\n

Because it\u2019s impossible to predict anything with 100% certainty, the next-best option is to use your past performance data to come up with a range of project delivery dates and the probability of hitting each of them.<\/p>\n

Here is what probabilistic forecasting isn\u2019t<\/strong>: \u201cWe\u2019ll deliver these 50 items by November 1st!\u201d.<\/p>\n

What\u2019s the problem with this statement, you might ask? There are two major issues with it.<\/p>\n

Firstly, it suggests that there is an actual obligation to deliver all of the 50 items<\/strong> by November 1st. And secondly, it implies that these exact 50 items<\/strong> will be finished by then.<\/p>\n

Can we make that promise knowing that knowledge work is notorious for its unpredictable nature?<\/p>\n

We should always remember that there is uncertainty involved and we should communicate that there is more than one possible scenario that might happen in the future.<\/p>\n

So, a probabilistic forecast would look like this: \u201cWe can deliver 50 items by November 1st with an 85% probability of hitting that target.\u201d<\/p>\n

The difference? You can take any 50 items<\/strong> from your backlog (and yes, feel free to add and remove from that list!).<\/p>\n

Furthermore, you communicate the risk you are managing in terms of percentages<\/strong>. There is an 85% chance you will make it on time.<\/p>\n

This is what probabilistic forecasting is \u2013 and it\u2019s a method that\u2019s actually far more effective, accurate and reliable than just about any other<\/strong>.<\/p>\n

Probabilistic forecasting doesn\u2019t provide perfect<\/em> predictions.<\/p>\n

It provides reliable<\/em><\/strong> predictions. Remember, there\u2019s no such thing as a perfect prediction \u2013 alas, no one has invented the magic crystal ball just yet, unfortunately.<\/p>\n

You can only manage the uncertain and unknown effectively and mitigate the risk of failure. And there is a tool at your disposal that will enable you to do just that.<\/p>\n

How to Make Reliable Probabilistic Forecasts?<\/h2>\n

The tool to make reliable probabilistic forecasts for your project (in just a couple of minutes!)<\/em> is called the Monte Carlo simulation<\/a>.<\/p>\n

This simulation uses a computational algorithm to provide you with a range of possible delivery dates and the likelihood of reaching each of those delivery dates.<\/p>\n

You just enter when you want to start your project and the number of items in your scope and the simulation will build a histogram with percentiles increasing from left to right.<\/p>\n

\"Probabilistic<\/a><\/p>\n

Let\u2019s say the scope of your project is 50 tasks and you want to start working on it on September 13th. The simulation will give you a range of possible dates for completing your project.<\/p>\n

In this example, there is an 85% likelihood of finishing your project by February 28th, compared to a 95% likelihood of finishing your project by March 13th.<\/p>\n

Remember, whether you are using probabilistic forecasting or a different approach, there is no 100% guarantee of completing your project. But Monte Carlo, unlike other approaches, will give you the most probable, least-risky outcome to commit to.<\/p>\n

You can choose to take a higher risk to reach an earlier deadline or mitigate your risk by choosing a more realistic deadline. Ultimately, you are in control of how much risk you and your team feel comfortable taking and are empowered to choose from your options.<\/strong><\/p>\n

\u201cWhen will you deliver your project?\u201d may not be the right question to ask. Monte Carlo will give you that answer. The question now is, \u201cHow much risk are you willing to take?\u201d.<\/p>\n

Probabilistic forecasting can be a counterintuitive approach to adopt at first because people are naturally averse to the notion of \u201cprobability.\u201d If it\u2019s not a sure thing, why are we relying on it?<\/p>\n

The truth is, Monte Carlo allows us to get as close as possible to a \u201csure thing\u201d by running thousands, even millions of trials to get a range of tasks and the confidence levels that come with each of them.<\/p>\n

There is just one prerequisite here: to make accurate and reliable predictions with Monte Carlo (and actually make any other approach to forecasting work), you need to optimize your delivery system for predictability<\/a>.<\/p>\n

<\/div>\n

Why is Forecasting Important in Project Management?<\/h2>\n

Do any of the following sound familiar:<\/p>\n