Moving further, we have now into the details of three point estimates or effort you can say a triangular distribution or linear distribution or a beta distribution. The point here is again you need to understand that these point estimates and value management bottom up you cannot do first you cannot have a full power and the usage of it until and unless you have a very good work breakdown structure defined for your project, because these they all depends on a work package level they all work on a work package level they identify that how the, all the all the deliverables will sum up and then you have a whole project timeline. So, this is how this is where you will be actually Linking every single estimate to the work package level, and then it will help you identify the risk of why this specific deliverable is identified. The reason why this specific deliverable is at risk.

This is where it comes Soviet technique used to estimate cost or duration, cost and duration both by applying an average or a weighted average. So, we have two formulas one is called triangular distribution or a linear distribution, where we will take the pessimistic, most likely and optimistic and we'll divided by three in this, when you are talking of a triangular distribution, it does take risk and uncertainty in account, but it is saying that the weightage of a risk and uncertainity which is optimistic and pessimistic is same as what the most likely So, it becomes a trap, the triangular distribution or linear distribution on the other hand, When you are talking of a normal distribution or nonlinear distribution or a beta distribution, we are actually saying that our formula is based on optimists one on optimistic one of pessimistic into four of most likely what we are saying that there are 60% chances on a project that we will be delivering a project on time.

So, one of so we divide hundred in terms of six, which is almost let's say 80 or 60. And then most likely is four times higher than optimistic and so, because we are an expert we have given you the timeline. So, we are more we are sure about that if these things would not go wrong, the plan that we have given you is the most optimistic plan which is now most likely. So, the formula which is a beta distribution is c o plus four cm plus EP divided by six. In this case, one of risk one of risk into four and four of most likely to do. So you need to identify that create work breakdown structure, we this is the basis for any proper estimation, which will tell you that how much time you actually need on the project.

And this is where the progressive elaboration and the rolling wave plan comes in that you don't know about your project from day one. But you need to wait for a little bit then you have to go near future and far future near future and far future. I'm sure you remember that dynamic of current near future and far future that how you need to move in terms of rolling with plan to interview brainstorm how best we can do the job. Then ask what kind of risk associated with this and what could go wrong which is a pessimistic, grill down the idea of nothing could go wrong. nothing could go wrong. Definitely does not mean that nothing is absolutely would go wrong you go straight a highway and are very fast no there is something will happen.

There's something which is not but most likely, but it is most optimistic that could happen then calculate the single three point estimate using the calculation. So most likely pessimistic and optimistic and then if I divide the butt formula or a beta distribution, this will give you the idea behind this will give you the calculated buffer. So, if we go further it will give us the distribution of a beta distribution which if you could see that starting with the shorter then you have a most likely using original CPM calculation, which is actually upward a little bit next is a part which is optimistic plus for most likely into pessimistic plus pessimistic divided by six. And then we are saying optimistic as a pessimistic as our two extremes. We would like to go in between the whole concept we would like to stay in between that sometime it is if most likely is for for one, either able to finish in 3.8 or 4.2.

We don't want to go into the optimistic which is he and Mitchell if we don't want to either go into the pessimistic which is seven two important points to remember if you have identified your estimation in terms of optimistic, most likely and pessimistic and all your results in actual when you are doing a variance analysis when you are collecting that data as a data information. And most of the data point that you have collected against every activity is falling between most likely and optimistic You could say between optimistic and most likely optimistic and most likely so optimistic most likely and pessimistic three columns. So optimistic and most likely, it means you have given you have already padded the estimation as a normal human being we would like to live in the normal distribution, a beta distribution or a bell curve, where actually we say that yes, sometimes we will be a little bit early sometimes we will be a little bit late.

If we are all most of the data points most of the activities are finishing in a real time between most ly optimistic and the most likely it means you have already added the activity unnaturally without identifying the risk. Second point, if most of your data points in terms of actual data, data collection is between Most likely and a pessimistic between most likely NFS or mystic it means your initial assumptions were wrong, you're most likely is wrong you might need to go back and reevaluate because it could not happen that you are already going always into the in this range of most likely pessimistic. This could happen for multiple reasons was either your estimations are wrong, or you might need to reevaluate that or you were pushed to give the most likely estimate just to say, to save your bag or to present in the CSM, most likely we will finish in 15 days, but if something would go wrong, we will go into the 25 days.

These these could be the reasons