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- Staron, Miroslaw, 1977, et al.
(författare)
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Selecting the Right Visualization of Indicators and Measures - Dashboard Selection Model
- 2015
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Ingår i: International Conference on Software Measurement (Mensura).
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Konferensbidrag (refereegranskat)abstract
- Background: Contemporary software development organizations utilize multiple channels to disseminate information about their indicators, measures, trends and predictions. Selecting these channels is usually done based on the availability of the visualization technology and a set of requirements elicited from stakeholders at the company. Eliciting these kind of requirements can be labor-intensive and time-consuming. Goal: The objective of this research is to develop a method for selecting which dashboard should be used. As the set of dissemination patterns of measures in modern organizations is limited, this method should be able to identify the needs of visualizations at the company and match them to the dissemination patterns and their supporting technology. Method: The research method applied is action research conducted at Volvo Car Group. The action research is conducted as part of a project redesigning a large project status reporting tool and has been designed to quantify the requirements elicited from the stakeholders of the system. Results: The results is the dashboard selection model which consists of seven dimensions { type of reporting, data acquisition method, type of stakeholders, method of delivery, frequency of updates, aim of the information, and length of data processing ( ow). Conclusions: The conclusions show that using this model leads to a rapid identification of the best visualization method for measurement data, which has a cost-saving impact on measurement programs and ect-maximizing impact on the companies.
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| 2. |
- Staron, Miroslaw, 1977, et al.
(författare)
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A Key Performance Indicator Quality Model and Its Industrial Evaluation
- 2016
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Ingår i: IWSM Mensura 2016.
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Konferensbidrag (refereegranskat)abstract
- Background: Modern software development companies increasingly rely on quantitative data in their decisionmaking for product releases, organizational performance assessment and monitoring of product quality. KPIs (Key Performance Indicators) are a critical element in the transformation of raw data (numbers) into decisions (indicators). Goal: The goal of the paper is to develop, document and evaluate a quality model for KPIs – addressing the research question of What characterizes a good KPI? In this paper we consider a KPI to be ”good” when it is actionable and supports the organization in achieving its strategic goals. Method: We use an action research collaborative project with an infrastructure provider company and an automotive OEM to develop and evaluate the model. We analyze a set of KPIs used at both companies and verify whether the organization’s perception of these evaluated KPIs is aligned with the KPI’s assessment according to our model. Results: The results show that the model organizes good practices of KPI development and that it is easily used by the stakeholders to improve the quality of the KPIs or reduce the number of the KPIs. Conclusions: Using the KPI quality model provides the possibility to increase the effect of the KPIs in the organization and decreases the risk of wasting resources for collecting KPI data which cannot be used in practice.
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| 3. |
- Staron, Miroslaw, 1977, et al.
(författare)
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Dashboards for continuous monitoring of quality for software product under development
- 2014
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Ingår i: System Qualities and Software Architecture (SQSA). - Amsterdam : Elsevier. - 9780124171688
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Bokkapitel (refereegranskat)abstract
- This chapter contributes with a systematic overview of good examples on how dashboards are used to monitor quality of software products under development – both using multiple measures and a single indicator which combines quality and development progress. In this chapter we extract recommendations for building such dashboards for practitioners by exploring how three companies use dashboards for monitoring and controlling external and internal quality of large software products under development. The dashboards presented by each company contain a number of indicators each, and have different premises due to the domain of the product, its purpose and the organization. We describe a number of common principles behind a set of measures, which address the challenge of quantifying readiness to deliver of software products to their end customers. The experiences presented in this chapter come from multiple case studies at Ericsson, two studies at Volvo Car Corporation (VCC) and one at Saab Electronic Defense Systems in Sweden. All companies have a long experience with software development and have undergone a transition into Agile and Lean software development; however the experience with these new paradigms differs from two to five years depending on the company. The difference in the experience provide a possibility to observe that companies with longer experience tend to focus on using measures to support self-organized teams whereas companies with shorter experience tend to focus on using measures to communicate the status from teams to management.
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