Prediction is synonymous with forecasting. And the quality of your forecasting depends on how many data points you use in the process, and also how accurate those data are.

This is found to be the case when predicting the estimated delivery date of a project too.

You need the correct data points for this- the tasks that fall under the project, who is assigned a particular task, the amount of time one spends on a task, how many tasks are pending, how many are under review, and so on and so forth.

Getting all these data points accurately is rarely possible in an analogue environment. Even with digital tools, the data you get needn’t always be accurate. Case in point: the amount of time someone works on a task may have their break times also included.

I’m producing a tool that helps you get accurate data points for prediction. Not only that, the system’s advanced AI(Artificial Intelligence) gives highly reliable predictions in real-time for the end date of a project.

How to predict the project end date using I’m Productive?

To predict using I’m Productive is as easy as it gets. All you have to do is click on the “AI Predict” button and you will get a detailed graph of the project’s progression along with the end date at the current rate of progress.

The map’s Y-axis will chart the workload while the X-axis would have the time of progression- starting from the date on which the project began. The current date will be marked on the X-axis and also the predicted completion date and the project deadline. Both the latter dates are also mentioned in day and month format so that you can easily read them even if you don’t want to go deeper into the details on the graph.

Above the graph, you will also get an accurate prediction of when a current task will be finished at its ongoing rate of progress.

How I’m Productive gives you accurate prediction?

There are two ways in which I’m Productive to ensure accurate prediction.

1. Eliminating human errors

The planning fallacy is a term psychologists have given to the problem of people underestimating not just the time to finish a task but also the costs involved. The curious thing is this happens even when they know from previous projects that there is a high chance of the project going over budget or running late.

Delusional optimism is cited as the reason for this. Rational decision-making takes a backseat while unwarranted optimism becomes the basis for decisions.

Anchoring is yet another human error that hampers timely project delivery. Anchoring refers to the phenomenon by which we refer back to an original estimate each time we need to revise the forecast during a project run.

The original estimate almost always is made with over-optimism, and it rarely forms a solid yardstick to measure against the current realities of the project. Delays and other contingencies might have happened during the project run. But while reviewing delivery dates, Project Managers tend to fall victim to Anchoring- they still back the original estimate because humans are subconsciously affected by such estimates while taking decisions.

2. Using accurate data points

This idea was touched upon earlier: accurate prediction depends on getting the right data points. To use a simple example, we can look at weather forecasting. There are six primary data points that you need to predict the weather: wind, temperature, humidity, atmospheric pressure, level of cloudiness and precipitation.

Even if you get one of these data points wrong, you end up with the wrong weather forecast. This would cause trouble for those who may have planned things for the day based on the forecast.

The case for predicting project end dates in a business is not any different. Multiple parameters should be factored in for accurate predictions. These include the tasks assigned to each person in the team, the status of progress for each task and the number of hours each person has worked so far on a task.

It’s not unusual to have errors in such data if the data gathering is done manually. With I’m Productive, you can be sure that the data points are precise. For example, consider the time a team member spends performing a task. The simplest way to calculate it would be to subtract the current date or time from when they started on the task.

Indeed, that is how most people- and even many digital tools- evaluate it. But I’m Productive goes a step further to ensure you get precise data.

The earlier-mentioned idea of evaluating time would not give only the time the person spent on the task. It would also include his or her break times.

But the timer on I’m Productive halts automatically when someone pauses their work and resumes by itself when they start working again.