Understanding of how business processes are executed in real-life is vitally important for a company. Any process leaves a digital footprint that can be transformed into so-called event logs and analyzed with process mining techniques. A software platform with the purpose of near realtime processes monitoring is implemented. Design of the represented platform is based on the lambda architecture combining online and offline process mining algorithms with advanced analytics based on machine learning.

Estimation is an essential step of software development project planning that has a significant impact on project success—underestimation often leads to problems with the delivery or even causes project failure. An important aspect that the classical estimation methods are usually missing is the Agile nature of development processes in the implementation phase. The estimation method proposed in this article aims at software development projects implemented by Scrum teams with differentiated specializations. The method is based on the authors’ system of working-time balance equations and the approach to measuring project scope with time-based units—normalized development estimates. In order to reduce efforts spent on the estimation itself, an analysis of dependencies among project tasks is not mandatory. The outputs of the methods are not recommended to be treated as commitments; instead, they are supposed to be used to inform project stakeholders about the forecasted duration of a potential project. The method is simple enough to allow even an inexpensive spreadsheet-based implementation.

In the early software development stages, the aim of estimation is to obtain a rough understanding of the timeline and resources required to implement a potential project. The current study is devoted to a method of preliminary estimation applicable at the beginning of the software development life cycle when the level of uncertainty is high. The authors’ concepts of the estimation life cycle, the estimable items breakdown structure, and a system of working-time balance equations in conjunction with an agile-fashioned sizing approach are used. To minimize the experts’ working time spent on preliminary estimation, the authors applied a decision support procedure based on integer programming and the analytic hierarchy process. The method’s outcomes are not definitive enough to make commitments; instead, they are supposed to be used for communication with project stakeholders or as inputs for the subsequent estimation stages. For practical usage of the preliminary estimation method, a semistructured business process is proposed.

From the business standpoint, predictability of the resources and time required for successful project completion is one of the key aspects of software development. This estimate significantly impacts project implementation and its outcomes – underestimation often leads to failures. An implementation schedule is one of the key ingredients of software development project estimation. Over recent years, the software development business has become even more competitive which, in turn, has imposed more demanding requirements on estimates – the more accurate an estimate is, and the less working time is spent on its preparation, the higher chance to overperform the competitors. This is why automation of such a manual assignment as project implementation schedule preparation is a relevant scientific and technical task. The current article is devoted to a method of building a software development project tasks implementation schedule. The project is supposed to be done by a scrum team with non-differentiated specializations. The resource constraints are expressed as balancing of the task effort estimates and the project team development capacity for each of the sprints. In order to unify measurement of software development productivity, a "normalization" approach is applied. The order of adding tasks to a schedule considers dependencies between the tasks and utilizes the List Scheduling method. As the method's outcomes, a set of feasible project implementation schedules is produced. Over a feasible schedule, a fine objective function is defined. This objective function minimizes the project team's idle time assuming that such idle time in the beginning of the project is "worse" than in its ending. Being applied along with the Multi-Stage Estimation method, the method proposed in the current article allows to reduce the working time spent by experts on preparation of estimates. Because of its simplicity, the software implementation of the current method version can be done without writing source code – a spreadsheet editor can be used instead. The priority ways of the further evolution of the method are the following: supporting of scrum teams with differentiated and mixed specializations; transition from a normalized project implementation schedule to the "full" one considering the project tasks' lifecycle and the structure of software developers' working time.