Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Deeva project introduction


Published on

Introduction to DEEVA research project

Published in: Science
  • Login to see the comments

  • Be the first to like this

Deeva project introduction

  1. 1. “Fully [emotionally] connected customers are 52% more valuable, on average, than those who are just highly satisfied. In fact, their relative value is striking across a variety of metrics, such as purchases and frequency of use.” Magids et al. (2015): The New Science of Customer Emotions USING DATA AND EXPERIENCES IN NOVEL ECOSYSTEM LEVEL VALUE CO-CREATION I: THE NEED - Digitalisation and social media as change drivers - Open source data, MyData - risks and uncovered possibilities - New understanding of emotions as drivers for decision-making and actions OUR WORKING METHODS …? • Combining cross-platform information and knowledge through modern state-of-the-art data analytics • Combining multiple open source data (local and national) • Interdisciplinary, heterogeneous co-working practices • Co-learning in international “skill-workshops” • Using sentiment and affective experience analysis • Visualisation and storytelling • Company specific guidance through service design • Continuous knowledge share between different research focus groups. WHY DEEVA? The The competitive advantage of data analytics is strongly declining. More and more companies are challenged in taking advantage of their data, with many yet uncovered possibilities. To achieve competitive advantage with analytics, companies need to understand why and how to change the role of data in decision-making. Blending analytical insights with intuition can produce more effective results than either alone, especially when making strategic decisions. Investments and cultural changes are needed in e.g. the processes of customer services, new service and product design, R&D, branding and business modeling. Succeeding in analytics strategies demands significant growth in data awareness at all levels of the business ecosystem. As such, it is essential to understand who owns the data and what kind of values and qualities does it have. Some sources: Lerner et al., 2014, Emotion and Decision Making; Magids et al., 2015, The New Science of Customer Emotions; Magids et al., 2015, What Separates the Best Customers from the Merely Satisfied; McKinely et al., 2016, Data Storytelling; Ransbotham et al., 2016, Beyond the Hype – The Hard Work Behind Analytics Success; Reeves et al., 2016, The Biology of Corporate Survival
  2. 2. PROJECT MANAGEMENT Coordinator: Contact: prof., 050 400 4275 Partners: Execution of the project: 1.1.2017-31.12.2019 Budget (estimation): 1,5M€ International partners: Key expertise: Management, Marketing, Knowledge management, Pervasive computing, Human-computer interaction, Mathematics, Signal processing, Gamification, Journalism SOME OF THE EXPECTED RESULTS New, improved competences of nowcasting and predicting customer behavior, thus resulting in better understanding of customer experiences. Expertise on emotional connections as a science - and as a strategy for value creation. Advanced use of visualisation and storytelling for logic reasoning and decision-making. Development of tools, methods and processes for e.g. improved (customer) services, product design and knowledge management. New, divergent and internationally collaborative understanding of data-driven, service-based business ecosystems. New insights on how to use data analytics to manage change, uncertainty and reciprocity. PAD -FRAMEWORK FOR SENTIMENT ANALYSIS ON Source: Reeves et al., 2016, The Biology of Corporate Survival THE NESTEDNESS OF COMPLEX ADAPTIVE SYSTEMS. Source: Jussila, Boedeker, Jalonen & Helander, 2016, Manuscript “Data tells you what’s happening. Stories tell you why it matters.” McKinley et al., 2016, Data Storytelling CTF not yet confirmed. / CARPE consortium includes Turku University of Applied Sciences, Hamburg University of Applied Sciences, Universitat Politècnica de Valencia, Manchester Metropolitan University and HU University of Applied Sciences Utrecht.