How to Meet Your Long-Term Goals Using Continuous Forecasting
Continuous forecasting is ultimately the best strategy that you can implement to stay on track and keep your commitments in the long run.
When my husband and I moved to Belgium, about 8 years ago, I fell in love with the country right away. The gorgeous natural scenery, the delicious regional beers and surprising flavors of chocolate all made me think about how little you actually need to be happy. Even though Hristo is more of a wine person, he really appreciates all the breweries based in the area we live in. This is especially true when there’s a good football game on.
I’ll always remember the Belgian Red Devils playing at the FIFA World Cup back in 2018. There were thousands of people watching the games on a big screen in the center of our town, drinking beers, singing, dancing and bursting into cheers every time we scored.
I was especially excited about the game against France! If you’re a football fan, you probably know all these websites that give you the probability of how a game will end. I was checking out the forecast every 2 minutes.
The approach that these websites use is pretty smart. As the game progresses, and teams score or don’t score, the chances of your team winning will change as well. Every time a new event happens, the model is updated and a new prediction of how the game will end takes place.
Imagine you are the coach of a team and you observe the probability of your team winning going down. If that’s the case, you’d probably want to make some changes, switch the positions of certain players, let new players enter the game, or swap the initial strategy altogether to increase your chances of winning. Either way, when provided with that information, it would be simply unreasonable not to make any changes. Your tactics have to adjust based on the new information you’re gathering. This is a classic example of continuous forecasting.
Your Project Plan is Not Set in Stone
Once you’ve either determined the delivery date of your project or defined the scope within your next release, don’t fall into the trap of assuming that everything will go as planned. Knowledge work is complicated; a lot of unexpected and surprising things happen and you have to account for these changes as you are working on your project. In order to meet your long-term goals, your plan has to change as you collect new information.
Using Monte Carlo simulations is one of the most effective and accurate methods for making project delivery predictions. However, once you have your initial forecast, you need to continuously reevaluate it and adjust your course accordingly.
Your forecast will change as you deliver more work. Your delivery rate will vary based on the >knowledge discovery process, any changes in the scope, your team or the efficiency of your workflow. All these factors will affect the base you used to perform your initial prediction. That’s why continuous forecasting is essential – to be able to deliver on time, you need to make sure that you have your finger on the pulse of the project.
If you’re interested in learning all about the reliable and unreliable approaches to making delivery predictions, I’d be more than thrilled to welcome you to our Sustainable Predictability program.
Augment Your Project Plan with Continuous Forecasting
When we talk about making delivery predictions, we need to acknowledge that there are many possible scenarios that could occur in the future. Probably the biggest advantage of using the Monte Carlo method is the fact that it produces a range of outcomes and the probabilities associated with each of them. It enables us to think about our commitments in terms of the risk we’re willing to take.
Now, let’s say that our project starts on June 1 and we have a scope of 55 stories to be completed. We’ve committed to delivering on August 27, and that outcome comes with an 85% certainty of us meeting our goal. This is what our Release Tracking Dashboard looks like:
From here on, we should track the release progress on our project on a regular basis. We will start working on June 1 and as we deliver work, we want to apply the continuous forecasting strategy to reevaluate our initial commitment. So, we run the simulation again on June 15. We change the start date of the simulation to June 15 and the throughput date range to account for the work we’ve completed so far. The remaining scope is 53 work items.
The simulation says that, based on our performance in the past 2 weeks, there is an 85% chance of us finishing on September 10 and the probability that comes with our initial commitment has dropped down to 54%. This is a red flag and we need to act accordingly in order to avoid project delays. This is what our release tracking report looks like:
We need to continuously reevaluate our forecast and take actions accordingly to be able to get back on track. Evaluate the impact the adjustments you’ve introduced have on your performance. Use the release tracking spreadsheet to report your progress and the likelihood that comes with delivering on your commitment. After a few releases it will look something like this:
The most important thing is to stay on top of the progress you make and ensure you take action accordingly. In this instance, the team knew that they were off track in the sprint starting on June 15. So, they decided to reduce their WIP limits to be able to stop multitasking and focus on one thing at a time, a decision that ultimately resulted in a record increase in their throughput.
Even if the adjustments you make don’t pay off, you’ve become aware of the situation and you can communicate it to your customers/stakeholders early so they can react on time. Acts like this build credibility and shape our reputation as professionals.
Monte Carlo simulations clearly define the risks associated with a certain outcome. When it comes to planning, the conversation now moves from “When will this be done?” to “How much risk are you willing to take?”. And using continuous forecasting will enable you to understand whether the risk of not meeting the deadline you committed to is increasing or decreasing as you work through your project.
The Monte Carlo simulation is there at your disposal to provide real-time feedback on whether you will make it on time or you need to adjust your course accordingly to mitigate the risk of failure. Take advantage of it! That is the most effective approach to manage realistic expectations.
Meet the Author
Sonya Siderova is a passionate product manager and a driving force behind Nave, a Kanban analytics suite that helps teams improve their delivery speed through data-driven decision making. When she's not catering to her two little ones, you might find Sonya absorbed in a good heavyweight boxing match or behind a screen crafting a new blog post.