Currently, software companies are in a great demand. Most of the companies believe in decreasing costs while increasing software productivity. Today, improving software productivity is becoming more serious as there is a lot of competition between different software companies. Every single percentage of increase in productivity results in drawing out huge amount of profits. To increase the productivity, it is essential first to know certain kinds of measurements that would lead into growth of productivity. The measurement phenomenon may include parameters like theory development measurement, testing and verification and performance evaluation. To reach to the decision about planning to increase the productivity, one has to undergo number of data collection. The planning for increasing the productivity would primarily depend on:

- Data collection versus cost of alternative instrumentation, collection and sampling strategies.

- Displaying the results of data analysis for various audiences.

- Handling the anomalous data.

- Use of collected data to monitor, evaluate, and intervene.

- Developing a narrative, diagrammatic, or operational abstraction.

Measuring software productivity is a critical task and requires an excellent strategy. It is a pre-requisite for any planning related to software productivity that the measured parameters must be reliable, accurate, valid and repeatable. A research design for software productivity shall essentially contain three elements viz. qualitative case studies, quantitative surveys and triangular studies. Qualitative case studies would reveal information like how software product works occurs, what sorts of problems arise and when. Quantitative surveys are sensitive and must be carried out carefully to insure reliable and valid statistical results. Triangular studies are specially accomplished to find out the strengths of both qualitative and quantitative studies.

Software productivity is a critical task and must be offered to responsible people of the company. Programmer or managers can be offered the responsibility of collecting the data. As they are authorized to every developmental stage, the data collection would finish without spending much time. Project manager or team leader can also be occupied for the purpose as they can use their experience to provide enhancements in the process. Outside analysts or automated performance monitors can also be hired to accomplish the task but this would increase the cost of the process.

The foremost reason for measuring software productivity is to reduce software development costs, improve software quality and to improve the rate at which the software is developed. It is also implied to avoid hiring additional staff and accomplishing the same volume of work with a smaller staff. The software productivity measurements also help in developing products of greater complexity or market value with the same staff workload. It also helps is finding out possible product defects in the early developmental stages. This eventually helps in prohibiting severe defects in software products in future. There are many other reasons behind measurement of software productivity and the foremost being to produce a quality product by implying least number of employees. Productivity measures thus become an essential process of any developing software company.

The main benefit of measuring and controlling productivity is that you always know where to invest money and where to invest time. These answers will help to run business in a better way.