Big Data: Understanding how Creative Organisations Create and Sustain their Networks

Abstract

Big data is an evolving term used to describe the variety, volume and velocity of large amounts of structured and unstructured data. It can offer useful insights at both operational and strategic levels, thereby helping organisations to move forward in times of rapid change and uncertainty. However, there are challenges in terms of how best to capture, store and make sense of data. Many cultural arts organisations generate value through the relationships they create and the networks they sustain, but far too often this data is not clearly articulated or evidenced to leverage insight, support and business opportunities. The ArtsAPI project aimed to understand the connections that underpin the 'relational value' within the arts sector. The R&D project resulted in the development of a proof of concept business modelling and analytic tool to enable arts organisations to generate new insights through data capture, visualisation and analysis. The numerical/analytical technique of Social Network Analysis (SNA) was used to visually map and analyse network structures and relationships found within and across the extended boundaries of five cultural arts organisations located in the UK. Based on the 'blue print' from the SNA research, seven scenario-based insights were generated that offered impact measures for debates around evidencing forms of cultural value. These scenarios were later mapped onto a semantic ontology to create a 'SNA lite' web-based tool. In the paper to be reported here, we will set the context and background of the project, briefly describe the research methodology and the outcomes that influenced the development of the ArtsAPI tool.

Insights on Creative Networks: A Social Network Analysis of Five Arts Organisations

“…It is therefore pragmatic that this paper focuses on the different uses of digital tools and methods and their appropriateness in the Arts and Humanities, particularly in the context of how arts and other cultural organisations can identify and use data to demonstrate impact and drive decision making inside their businesses. Indeed, arts organisations are unique in the way in which they operate, relying heavily upon the informal and formal networks they create and sustain (Bruce, Malcolm and O'Neill 2017). This is largely a result of the precarious employment, and reliance on external funding, which is prevalent in the sector therefore impacting on long-term business commitments (Opara et al, 2019).…”

“…Compared to larger corporations, the creative ecosystem in which they operate depends on "quick business" and requires them to be more agile, adaptive, and faster when identifying and responding to arising opportunities within their networks (Opara et al, 2019). Moreover, their interdisciplinary, inclusive, and collaborative ways of working create emerging opportunities for spin-off companies and other entrepreneurial ventures, which can be better exploited through the analysis of network relationships (Bruce, Malcolm and O'Neill 2017). Therefore, more studies are clearly needed to understand how data can be used to create added value, which in turn helps arts organisations align and strengthen their core competencies and improve their interactions with stakeholders (Pesce et al, 2019).…”

“…Many arts organisations can generate large amounts of data through their activities and networks. The wider aim of the Arts API project was to develop a web-based analytical tool that would allow arts organisations to make more sense of a variety of data sources (such as email or social media) relating to their business activities and networks (Bruce, Malcolm and O'Neill 2017). In doing so, it would enable organisations to improve their decision-making and subsequently increase productivity and innovation potential.…”

“…SNA can therefore be used to make sense of relational data that connects people within a distributed network by capturing a visual representation of social structures (e.g., status, roles, groups, and institutions) across micro, meso and macro levels, as well as deriving insights through deeper quantitative analysis (Bruce, Malcolm and O'Neill 2017). Borgatti, Everett and Johnson (2018) usefully point out that "a generic hypothesis of network theory is that an actor's position in a network determines in part the constraints and opportunities that he or she will encounter, and therefore identifying that position is important for predicting actor outcomes such as performance, behaviour or beliefs" (p. 1).…”

“…In addition, the project aimed to further enhance these relationships through the development of the Arts API Tool. Adopting the technique of SNA, the internal and external networks of five UK-based arts organisations were visually mapped and analysed over the same 4-week period, using a modified version of Cross and Parker (2004) six-step process, as outlined in detail in a previous paper by Bruce, Malcolm and O'Neill (2017):…”