Estimating company’s project costs with advanced analytics : case study

Abstract

Today’s fragmented and constantly changing business environment pushes companies more and more to forecast their future performance as accurately as possible. One approach for forecasting future can be done with estimation. Estimation help organization’s executives and external stakeholders to gain understanding how well the company is going to perform in the following time periods. Estimation has challenges especially in project estimation, where fluctuation of costs and unpredictable events during the project can be challenging to see proactively. Case company is a big multinational organization that has added estimation besides their traditional budgeting practices. Due to the demands from recent IFRS 15 standard, the company has changed their income recognition process from milestone practice to cost-to-cost income recognition. The change has caused challenges among estimators because the company’s current practice leans vigorously on historical project data and the quality of that data is not as good as it is required to be. The purpose of this thesis was to develop a method for project cost estimation that provides automation and more accurate numbers than current procedure. The thesis was qualitative research and followed constructive research approach. The primary data was gathered through various group interviews from different sectors both inside and outside of organization. The secondary data contained clarified discussions, meetings and researcher’s own notes. The results disclosed that instead of enhancing current practice, a whole new method was needed to be developed. Historical data-based estimating does not provide accurate estimates due to the false assumption that there being similar projects in the past and quality of data being good enough. Furthermore, company has comparatively large number of unique projects which does not have prior data at all. As a conclusion, the new model for estimating project costs connects company’s project scheduling, progress reporting and pricing data together and uses Advanced Analytics platform for calculating estimations automatically. Based on the results of this thesis, the company is going to invest in Advanced Analytics platform and export the model in to practice and implement it to the use of whole organization.