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PoliVisu Value Proposition Workshop, Antwerp, 2018

21c’s Susie Ruston McAleer and Pavel Kogut ran a Value Proposition workshop at PoliVisu’s Consortium meeting in Antwerp this September. The aim was for the Consortium to to place themselves in the potential customers’ shoes to better understand which elements of the PoliVisu solution provide most value to them. Organised as part of the Antwerp meeting, the exercise required partners to work in teams with the pre-designed/printed templates. The brainstorming centered around ‘pains’ and ‘gains.’ Pains are inhibiting factors that trouble potential customers, preventing them from getting the job done. An example would be the lack of knowledge and skills needed to work with big data to produce insightful visualisations on a specific policy issue. Gains, on the other hand, are things that – put simply – make customers happy. Unlike pains, they enable decision makers to get the job done easier, faster and more effectively. A big data training course, a how-to guide for policy visualisation, an interactive map with built-in exploratory analysis tools – these are just some examples of gains that could help end users succeed in their job. And it is with the job-to-be-done that partners started their brainstorming session.

What do potential PoliVisu customers need to do in their job? A synthesis of answers produced three broad jobs/tasks: (1) translate political views into concrete measures, (2) advise politicians on how to solve specific problems; (3) implement policy using the most appropriate data/tools. Interestingly, the conceived job description seems to match that of a city manager or a municipal policy officer despite there being other roles in the pool of potential target customers e.g. communications staff, community groups, researchers.

What barriers/pains make the job difficult? Partners generated a wealth of ideas in answering this question, using as a basis their previous knowledge and experience. The issue of cost was highlighted in relation to big data access/management, with some partners making references to a recent Amazon study which found that costs associated with building and maintaining data warehouses can run up to €25,000 per terabyte annually. That means a data warehouse containing 40TB of information (a modest repository for many large organisations) requires a yearly budget of around €1 million. Another oft-cited barrier was the lack of skills. Indeed, the lack of skilled analysts has affected not only the public sector but also the industry more generally, at a time when demand for AI and big data analytics has never been higher. The third issue raised by partners is linked to data security. True, big data can bring many benefits but it can also lead to big privacy problems. As recent security breaches show, some organisations are in such a rush to implement big data solutions that they take a somewhat careless approach to security. And when security becomes an afterthought, the potential for disaster increases dramatically. Other pains that emerged from brainstorming include difficult relations with data owners, lack of public support for policy/measures, and lack of common view on an issue/course of action among stakeholders.

When thinking about gains, partners tried to find a matching solution for each of the foregoing problems as best they could. The cost issue cannot be easily addressed as cutting down the size of data warehouse is rarely a viable option. While there may be little cost saving to be made in big data access/management, one area where this could be achieved is analytics. Specifically, public administrations could save money by switching to open source tools for their visualisation/processing needs. The lack of big data skills is not necessarily a human resource problem but rather an issue with roots in organisational culture. Organisations with a thriving/established big data culture are less likely to suffer from skills shortages and vice versa. The security aspect of working with big data can be addressed by developing appropriate frameworks (e.g. security, confidentiality, privacy), which in turn can be embedded into the broader big data culture. Relations with data owners can be improved through new PPP initiatives, while open government projects that make use of open data, standards and tools can go a long way toward minimising the gap between citizens and policy makers.

The last remaining item on the canvas was value proposition, whose purpose is essentially twofold: to maximise gains and minimise pains. The value of PoliVisu does not lie solely in the visualisations themselves. The mobility sector has been using visualizations for policy making for a number of years. However, these visualisations were usually based upon a snapshot of data (e.g. think people with clipboards counting cars) so were not very accurate and the data was not necessarily timely. PoliVisu's main advantage is that it offers not a single product or service but rather a multi-faceted solution, thereby addressing both pains and gains, hard (data, tools) and soft (knowledge, methods) elements needed for effective policy making.

The results of the exercise will be embedded into Business Modelling workshops due to take place in 2019.

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