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Topics: Source lines of code, Project management, Mathematics Pages: 12 (3885 words) Published: June 18, 2013
Estimation has always been one of the riskiest aspects of project or program planning. This is not because estimators are regularly unqualified or poorly informed -- it is primarily because of the large and growing number of complexities and dependencies that must be factored into software project estimates. Inevitably, as software projects, software products, and IT environments all become more and more complex, so, too, does the task of estimating what they will cost and how long they will take. To compound the challenge, established parameters that form the basis for many estimation techniques are not as universally applicable, or as straightforward to calculate, as they once were. Many estimators are thus left searching for methods that can yield more accurate results. In this, Part 1 of a two-part article, I'll examine approaches, techniques, models, and tools that have gained momentum and support among estimation experts, as well as some intriguing innovations that seem to have bright futures. In Part 2 I will discuss different estimation scenarios, what methods are best under what circumstances, and how to most efficaciously apply them. Why we estimate

We human beings tend to estimate constantly in our everyday lives. We estimate how long something will take, how much something will cost, how many calories are in that dessert, and so on and on. Estimation is just as vitally important to an organization, as its economic viability depends in great part on the quality of the decisions made by its executives. Which, in turn, are driven to a large if not a primary extent by estimates. Business decision-makers estimate for reasons like: * Budgeting. Budgeting is not only about how to spend cash sitting in a bank account, but also about how to strategically allocate available and future resources for the greatest benefit to the organization. Some of the cash you're planning to spend may not yet be readily available; and, indeed, may never materialize -- factors an estimator will try to predict. * Project planning. For software projects, estimation is part of predicting costs, schedules, and resources, and striking a balance among them that best meets enterprise objectives and goals. Estimates are also very important for internal project planning and execution, as they influence project lifecycles (iterations, increments, etc.), and thus ultimately project results and even individual productivity. * Risk management and trade-off analysis. Estimation is a major factor in enterprise risk analysis and risk management because every enterprise decision makes assumptions about the flow of events, which is largely based on estimates. * IT infrastructure and process improvement analysis. Estimation is an essential part of the enterprise architecture implementation and governance, which includes (among other things) assessing enterprise process improvement alternatives and their impacts on other processes, as well as considering options for building versus buying software, hardware, and services. Estimating approaches, techniques, models, and tools

In the early days of IT, people invented straightforward ways of estimating software development work. Back then, software estimating was by-and-large a matter of applying a linear equation with variables for lines of code and staff headcount. As the nature and role of IT has become vastly more complex and diverse, so have the estimating techniques applied on software projects. Something that worked in an environment with a single programming language may no longer work in today's heterogeneous environments. Other aspects that have contributed to the evolution of the estimation discipline and prompted introduction of non-linear factors include the emergence of multiple platforms and frameworks, commoditization of IT services, and increased complexity and size of IT projects. To cope with this growing estimating challenge, innovators came up with numerous approaches and...
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