Utskrift från Malmö universitets webbplats www.mah.se

Accelerating Digitalization Through Data: Towards Digitally Enhanced and Digital Products and Services

Kontaktperson: Helena Holmström Olsson
Ansvarig: Helena Holmström Olsson
Samarbetspartner: Chalmers, Axis communications, Grundfos, Ericsson, Jeppesen, AB Volvo
Finansiär: Finansierat av samtliga deltagande företag samt universitet i Software Center.
Tidsram: 2014-06-30 -- 2019-12-31
Fakultet/institution: Fakulteten för teknik och samhälle, Institutionen för datavetenskap och medieteknik, Institutionen för datavetenskap
Hemsida: http://www.software-center.se/

Background

Today’s software-intensive business is in the midst of profound changes in relation to development of software systems. With rapid pace, and across industry domains, sophisticated technologies for data collection and analysis are implemented to provide developers with real-time input on how the systems they develop perform in the field. Also, this data helps developers understand what functionality is used by customers and it allows product managers to confirm whether feature prioritizations were accurate. With automated practices for data collection and analysis, queries can be processed frequently to provide software developers and managers with rapid feedback and as a result, continuous improvements can be made to the systems. This reflects an interesting shift in that traditional requirement driven development practices that have been the de fault approach for decades are being complemented by data driven development practices where teams use data to continuously improve and optimize the system to a certain outcome. We can already now see that companies that are adept at acquiring, processing and leveraging data become more profitable as decision-making and prioritization based on accurate data from the filed can have a profound impact on annual revenue.

With systems being connected to the Internet and technologies that facilitate data collection and analysis, we see that companies are increasingly complementing their traditional development approaches with other approaches. As one of the most influential trends in software industry, continuous deployment of software is challenging traditional ways-of-working in that it by-passes the notion of early requirements specification. Continuous deployment is a software engineering practice in which incremental software updates and improvements are developed, tested and deployed to the production environment on a continuous basis and in an automated fashion. In this way, customer preferences and needs can be continuously collected, analyzed and deployed and rather than the traditional view of a system being finalized when delivered to customers continuous deployment allows for systems to evolve and improve over time and with delivery to customers as the starting-point for this. In online companies, continuous deployment of software and customer data from A/B tests are the norm for evaluating ideas and understanding customer value and with companies such as e.g. Amazon, eBay, Facebook, Google and Microsoft running thousands of parallel experiments to evaluate and improve their sites at any point in time. The trends described above reflect an interesting shift from a situation where traditional requirements engineering practices inform development of new features, towards a situation in which customer and product data is continuously collected and where companies use this data to inform development during run-time

As soon as companies are able to deploy continuously, they are able to adopt what we refer to as outcome/data driven development.  We define outcome driven development as an approach where development teams receive a quantitative target to realize, such as conversion rate for part of an e-commerce website or throughput for a telecom system and are asked to experiment with different solutions to improve the metric. Examples of this type of development are new features used frequently by customers as well as innovation efforts. Outcome driven development is based on data from (1) experimentation with users (e.g. by using A/B testing techniques), and (2) data collected from the product itself (e.g. by product performance measurements or user’s behavior measurements). With these two types of data as input, and by using short feedback cycles, it is possible to iteratively build new functionality and continuously measure to what extent this functionality is delivering on the expected outcomes.

In addition, and as a new focus area in this project, the adoption of continuous deployment and continuous data collection allows for a fundamental shift for product management (PdM) in terms of decision-making and feature prioritization. Rather than relying on opinions and internal assumptions that exist in the organization, PdM can use experimentation and data driven decision-making as mechanisms to prioritize R&D resources. This allows for a significant improvement in the effectiveness of R&D in terms of business value created for each unit of R&D resources and it allows product managers to complement qualitative customer feedback with quantitative product data.

The overall project goal is to help companies transition from requirements driven towards outcome/data driven development where business strategy is defined in quantitative targets that help development teams to optimize, prioritize and focus their efforts. We operationalize the concepts that were developed in previous sprints and we develop methods, techniques and tools that help companies validate that their development teams deliver on the desired business outcomes.

Senast uppdaterad av Magnus Jando