Estimation techniques are used to forecast the cost and effort involved in following a particular course of action such as the implementation of a solution.
Estimation techniques are used to help organizations make strategic business decision by analyzing the following.
- The Cost and effort related to following a particular course of action.
- The expected benefits to be realized by implementing that solution.
- The lifecycle cost of the solution such as the cost of developing and operating that solution.
- The potential risk impact of the implemented solution.
Once all these factors are analyzed, the result of the estimation can be shown as a single number, but if the results are described as a range, with minimum and maximum values along with probability, it may be easier for the stakeholders to understand.
This minimum and maximum range is called a confidence interval and it calculates the level of unpredictability of the estimation results.
The greater the uncertainty, the wider the confidence interval will be.
Estimation has some elements, which include the following:
1. Methods: there are different estimation methods that can be used for specific situations.
But it is very important that the stakeholders involved in the estimation have a shared understanding of the elements that are to be estimated.
This shared understanding is usually achieved with the help of some decomposition tool such as a work breakdown structure which would help breakdown a complex problem into simpler pieces.
When creating and communicating an estimate, the constraints and assumptions also need to be clearly communicated to avoid any confusion or misunderstanding.
Examples of some estimation methods include the following:
• Top-down: in this technique, the solution is analyzed from the and then it is broken down into the lower levels and summed up.
for example, when analyzing the organizational budgets, the total cost of each department is first identified and then it is split into the individual units in each of those departments.
• Bottom-up: this technique examines the organization from the lower-level and builds up the estimated individual cost or effort, and then adds them across all elements to provide an overall estimate.
For example, using the same budgetary example from above. The budgets for the individual units in the department would first be identified then they would be summed up to their departments and then summed up to the whole organization.
• Parametric estimation: this technique uses a calibrated parametric model of the element being estimated.
The estimators would identify previous projects or solutions to analyze the costs. This would provide an estimate of what this current solution or project might cost.
It is vital that the organization uses its own historical records to calibrate any parametric model, because the values demonstrate the abilities of its employee and the processes used to perform the work.
• Rough order of magnitude (ROM): this method uses a high-level estimate to estimate the cost of the project or solution.
It usually used when there is little information to work with and is dependent on the estimation skills of the estimators.
• Rolling wave: this technique involves a continuous estimation of the project through out its lifecycle.
It is based on the belief that as the estimators knowledge grows they would be able to give better defined estimates for the next phase of the project.
• Delphi: this technique uses a mix of expert judgment and historical information.
It depends on historical records from the organization which is used to adjust the estimates.
The process involves creating initial estimates, sharing those estimates with the stakeholders, and continuously refining those estimates until they are accepted by all the stakeholders.
• PERT: in this technique, each element of the estimate is given three values, which are:
(1) optimistic value, which represents the best-case scenario.
(2) pessimistic value, which represents the worst-case scenario.
(3) most likely value., which as the name states is the most likely value.
Then a PERT value for each estimated element is computed as a weighted average, using this formula:
(Optimistic + Pessimistic + (4 times Most Likely))/6.
2. Accuracy of the estimate: The accuracy of an estimate is a measure of uncertainty that assesses just how close the estimate is to the actual value.
It can be calculated as a ratio of the width of the confidence interval to its mean value and then expressed as a percentage.
When there is little information, such as early in the development of a solution approach, a Rough Order of Magnitude (ROM) estimate can be used, which is expected to have a wide range of likely values and a high level of uncertainty.
ROM estimates are usually not more than +50% to -50% accurate but a definitive estimate which is more accurate can be made as soon as more information is available.
Definitive estimates that are used for forecasting timelines, final budgets, and resource needs should ideally be accurate within 10% or less.
3. Sources of information: the estimators can use historical information from previous experience along with the element being estimated to calculate the estimation.
But there are also some other sources of information which might be helpful and they include the following :
• Analogous situations: this uses estimates from a similar initiative in the organizational’s industry for example a competitor, to calculate the element being estimated.
• Organization history: this involves using historical records from similar projects in the organization, especially if the same people and resources would be used to perform the work.
• Expert judgment: this involves using the expertise of individuals who are knowledgeable in the element being estimated.
It relies on the knowledge of those who have done similar work in the past and this include both internal or external people.
When using external experts, estimators should consider the relevant skills and abilities of those doing the estimation.
4. Precision and reliability of estimates: when numerous estimates are made for a specific attribute, the accuracy of the resulting estimate would be an average of the estimates.
By analyzing the measures of inaccuracy such as variances, estimators can agree on a final estimate.
The accuracy of an estimate is shown in a range of estimates made by different estimators.
To show the degree of accuracy and precision, an estimate is often shown as a range of values with a confidence interval, which is its probability level.
For example, if a team estimated that some task would take 50 hours, a 90% confidence interval might be 44 to 54 hours, depending on what they gave as individual estimates.
A 95% confidence interval might be 48 to 52 hours.
The PERT techniques is used to calculate the confidence interval.
5. Contributors to estimates: The estimators of an element are usually in charge of the element.
Team estimates are usually more accurate than those of a single individual especially if the team members are those people who would do the actual work.
Field experts can also provide estimates especially for sensitive projects such as those use to fulfil industry regulations.
When should the estimation technique be used ?
Estimation techniques have both their strengths and limitations which include the following:
Strengths
- Estimates provide an explanation for an allocated budget, their time frame, or magnitude of a set of elements.
- If projects are planned without the use of estimates, It could lead to inadequate budgets and unrealistic time frames.
- If there is limited information or knowledge in a project, a rough estimate can initially be created. As more information becomes available this estimate can be refined over time to improve its accuracy and help ensure the projects success.
Limitations
• Estimates are only as accurate as the knowledge level of the estimators. If the estimators are novices, their estimates can be way off the mark.
• Using just one estimation method may lead to unrealistic expectations of the projects feasibility.