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Data Pitch (case study)

Wed Dec 18, 2019
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Learn how Data Pitch – a three-year open-innovation programme that explored how data shared by large organisations – worked with startups and innovators to tackle specific company and sector challenges

Summary of the project

Data has the potential to create huge value for organisations but often only a small percentage of this is used to create innovative solutions that solve real problems.

Data Pitch was a three-year open-innovation programme that explored how data shared by large organisations – from government bodies to multinational corporations – could be used by startups and innovators to tackle specific company and sector challenges and generate direct benefit to them.

The programme is part of the ODI’s work that recognises that startups are motivated by fixing problems and have the right creative mindset and determination to build agile solutions to meet modern challenges. Data Pitch encapsulates this vision, and helps startups accelerate their growth by pairing them with data providers.

Data Pitch was developed to respond to the fact that there are many startups across Europe that are building innovative solutions using data and new technologies, recognising that many of them struggle to get access to real data from public and private sector organisations. Data Pitch bridges the gap between these two groups, supporting them throughout the process, removing risk and providing necessary expertise and credibility.

The programme was launched in 2017 and was funded by the European Commission’s Horizon 2020 research and innovation programme. Alongside the ODI, the other partners delivering it were the University of Southampton, Beta-i (a Portugese innovation agency) and Dawex (a French marketplace for private and worldwide data monetization and acquisition). Data Pitch drew to a close at the end of 2019.

The overarching goal of the programme was to provide insight into how the data economy can be strengthened through data sharing. The ODI believes data can inspire and fuel innovation, and this programme looked to enable large businesses, startups and governments to solve problems through sharing data outside their organisations, thereby creating value from data.

Key facts and figures

  • Supported 47 startups and small and medium-sized enterprises (SMEs) from 13 different EU countries.
  • Worked with 11 data-holding corporate and public sector organisations that shared data with their startup partners.
  • Data sharing was used to tackle 28 challenges, of which 22 found suitable startups to pair with.
  • 112 additional jobs were created by Data Pitch startups and SMEs.
  • €18m in sales, investments and efficiencies was unlocked by accelerated startups and SMEs.

What was the ODI’s role?

Initially, we contributed to finding corporate and public sector organisations interested in joining the programme. We co-defined suitable challenges and identifying relevant datasets they could share with the selected startups and SMEs.

We selected the challenges and datasets as part of a panel of experts including all programme partners. We then launched the open call for startups and SMEs, scouting for and selecting the most relevant, capable and interesting startups to pair with the data providing organisations.

We ran two six-month startup accelerators, working with Beta-i, Southampton University and Dawex. During the two acceleration programmes, we actively managed the delivery of the support curriculum in partnership with Beta-i. We have found that there is often a trust barrier between large organisations and startups, and independent facilitating programmes such as Data Pitch can help broker these relationships. To aid this trust and relationship building, programme partners helped manage the relationships between the data providers and data users, ensuring focus, momentum and providing expert advice.

Startups and SMEs put forward proposals for creating innovative products and services in response to the challenges defined by Data Pitch. The successful applicants received up to €100,000 equity-free funding, mentoring, business and data training, high-quality comms support, visibility at international events, and introductions to investors.

The programme team evaluated and helped develop the startups’ work roadmap and milestones. The programme provided financial and advisory support to sharpen their value proposition, and helped them to develop it into a robust and commercially-sustainable business.

The Data Pitch model was built around challenges. These were tricky problems that the data providers (or the sector as a whole) were struggling with. Data Pitch offered to help solve these challenges by defining the right problems, choosing valuable datasets and introducing the data-holding companies to innovative startups that had the right skills and resources to solve the problems. As a team, we then spent time designing an appropriate proof of concept as a product that would address the challenge for the data provider, as well as be profitable for the startups, who could then sell that product to other similar clients.

The project specifically looked at shared data, not open data. The difference between using shared and open data is not necessarily a difference in impact – as shared data projects still create economic, social and, potentially, environmental impact. The difference is often in the methodology and implementation. Shared data was different, as when the data is not under an open licence, there needs to be a sharing agreement governing the licensing terms for accessing the data. Data Pitch acted as the independent facilitator, to reduce the data access risk for the big organisations (the data providers), build trust between the parties and to provide access to valuable real datasets for the startups/SMEs (the data users) to feed into the algorithms and train their models.

What was challenging?

Securing the data providers was a more complex and lengthy process than we initially envisaged. While we had several expressions of interest, getting these to the signed-contract stage was complicated and time-consuming. Agreeing on the challenges, identifying the appropriate datasets and seeking approval for the legal agreements all took longer than expected. This was a useful learning experience, and ensured that we had a more realistic timeframe for this scoping exercise for the second cohort.

Evaluating and prioritising outreach channels was challenging. It was crucial to network effectively to build relationships, share key Data Pitch messages and scout for (and find) great startups and data-holding companies. To do this, and to grow the Data Pitch community, the ODI and the partners attended a range of conferences, hackathons and meet-ups. To help ensure good engagement, we booked speaking slots where possible, presented on panels with well-known/respected industry experts, and used social media to generate interest.

Finding the right startups. Attracting the right startups was crucial due to the specialised nature of the challenges. At the same time, we wanted to have geographically-diverse cohorts representing as many European countries as possible. To help with this, we were proactive in trying a number of approaches, including undertaking desk research, engaging with online startup communities and forums, and attending local networking events and tech conferences.

For future projects that have similar requirements in terms of scope, and specific aims to match challenges with appropriate partners, it is important to allow enough time to find committed data providers, scout relevant startups and build the necessary trust to support the relationships. It would also be useful to engage with networks operating within the space/sector, through meet-ups or more formal meetings, to get advice on the best networking opportunities.

What went well?

Getting the basics sorted first, and keeping the vision in sight. Even though there were  high-level aspirations for the Data Pitch programme, the day-to-day challenges still needed to be solved. It is vital to have someone at ground level who can solve basic problems, such as aggregation of data or quality of data.

Engaging with decision-makers from the start. We found that when we engaged with decision-makers within the data provider organisations early on, the process of designing the challenges was made much quicker. These people were often from the innovation department or were the head of the business unit that faced the challenge.

Adding value by aggregating data. Many of the Data Pitch startups aggregated data from lots of different places, which allowed them to draw on a wide range of intelligence. This gave them contextual insight; being able to provide personalised results based on a set of criteria.

Working with an organisation that we had an existing relationship with. We have worked with the University of Southampton before and so have shared experiences and work together well as ‘trusted partners’. As we have a good understanding of each other’s working practices, and a joint shared history on several projects, it was easy to work together, present a harmonious working relationship, and to gain credibility, both from the funder and the partners.

Building an accelerator team with the right mix of skills. We ensured the accelerator team had data expertise to advise on sharing data securely; business expertise to help startups with their ideas; legal expertise to set up agreements; technical skills to support the companies in building their products; and communications expertise to help disseminate the successes of the programme. We also ensured the startups had access to a wide range of industry expertise through external mentors and partners.

What have we learned?

We learned about the challenges and opportunities of data sharing. By running the programme we found out what can slow down the process, what the enablers are, and how to make it work for the individual partners.

Technology and legal ‘issues’ are not the blockers. It is crucial to get the culture and business model right up front, rather than to focus on the discrete technical or legal issues which are generally straightforward and fixable. At a programme level, legal issues can be a challenge, but it is not a blocker as we have experience of working around and dealing with specific challenges. The real challenge is persuading people and companies to think less conservatively about data sharing, and how to address the fact that business models don’t often allow for data sharing.

Create a compelling offer for businesses. The offer that Data Pitch presented to data providers was ‘we can help you solve a pressing challenge by introducing you to innovative startups’. We needed to make sure that we created something that delivered value to those businesses providing the data, bearing in mind that many of them are risk-averse in their business approach. So being clear about how the programme would help them deliver their goals was vital.

Demonstrate impact. It was important for the programme to demonstrate return on investment, especially when the startups wouldn’t be able to show the financial impact in the short term. This involved capturing both quantitative and qualitative metrics: human success stories as well as hard figures.

It is important to embrace shared data, as well as open data opportunities. There are huge opportunities with shared data. Europe doesn’t have the big players with lots of data, unlike the US with Google, Amazon and Facebook or Asia with Alibaba. So, to be competitive globally, medium-sized companies need to share more data, and this requires a strong data ecosystem.

For future programmes, it is important to set out clear objectives for all parties from the start, with specific metrics for success for the data providers, and also for the data users, so that these can be measured against. It is also crucial to capture and share success stories, to ensure recognition and promotion for the successful pairings, and to provide compelling stories and case studies for future/similar projects.