What do SMEs and startups need to succeed in open data innovation?
With the flexibility to experiment and be more innovative, startups and SMEs are increasingly incorporating open data into their business models. In this blog, ODI Fellow Tom Wainwright explores what it takes for these organisations to succeed
Open data is viewed as a vital resource that can assist businesses in creating new, innovative products and services. Researchers, policymakers and technical experts have celebrated the potential of open data innovation for businesses: they can access data at virtually no cost, obtain novel datasets that were previously unavailable, and create disruptive products and services. It is also argued that SMEs are particularly well-placed to benefit from open data innovation.
Compared to their larger corporate counterparts, SMEs and startups are smaller and more agile, enabling them to respond quickly to new ideas and market demands. They are also able to freely experiment with open data to explore the potential of new products and services. However, as our recent study shows, SMEs and startups can often struggle to fully exploit open data in innovation. Fortunately, the study also identifies key skills and capabilities that businesses should look to build and harness in order to maximise their innovation success.
SME benefits of open data innovation
Inbound open innovation, i.e. using the knowledge and assets of an external organisation to create your products and services, can help SMEs considerably. It speeds up the innovation process dramatically and keeps development costs low. In the context of open data, external sources collected and collated by others can be used with virtually no cost. Using inbound open data in innovation can replace sources of expensive proprietary data, or enable businesses to access new data sources that were previously unavailable, enabling novel innovation. Combining open data with closed proprietary data sources, either internal or shared by partners, can also create new data products and services. SMEs and startups can also grow and scale up using open data through coupled open innovation. An SME may open up their product catalogue data, enabling third parties to partner and advertise or sell the products to new markets in exchange for a small fee. This enables SMEs and startups to grow quickly with limited resources. These low cost innovative advantages are incredibly useful to SMEs and startups.
SME inhibitors to open data innovation
Despite the overwhelming potential for open data innovation in SMEs and startups, there exists many barriers. The limited size of SMEs can be a double-edged sword – while flexibility is beneficial, limited resources can derail the innovation process. SMEs and startups face a series of inhibitors: barriers, costs, and future uncertainty and risks. Due to their smaller size, they can struggle to identify and assess the usefulness of open data, particularly in a world of expanding open data sources. This may be due to time and multitasking limitations, or a limited understanding of open data use. Opportunities to integrate open data into an existing product or service may be overlooked due to time pressures, competing priorities and limited open data knowledge.
These issues can be compounded for data-centric businesses who need skilled data scientists (in short supply) who can not only process open data, but understand how it can be used to solve business problems. Concerns about the future availability of open data as a critical business asset can also deter some SMEs, while a lack of knowledge about managing the legal and reputational risks of open data can also undermine or limit the full application of open data in new innovations. A particular concern is product or service imitation by competitors, which is easier when using open data. Not knowing how to limit that risk can also reduce the full potential of using open data.
Which skills and competencies smash barriers to innovation?
One of the key issues that SMEs and startups face due to their smaller size is reduced time to explore and seize possibilities. However, a narrower breadth of skills and competencies within the venture team can also hold back innovation. Emerging skill gaps can reduce a business’s innovative potential for using open data.
Skills that are particularly important (and unique) are being able to develop and understand the full range of business cases for open data. Understanding the legal aspects of open data are also central to knowing what it can and cannot be used for in innovation. Perhaps less unique, but still critical, is the need to bridge the gaps between the technical side of data science and ‘softer’ management skills, to use open data to create new products and to develop market intelligence which identifies customer needs. At the heart of this are relationship management skills, to work with external open data publishers and consumers to assist in co-innovation.
Wider organisational capabilities are important to any business, but for users of open data some specific expertise is also needed. Unsurprisingly, an open culture is required to facilitate relationships and the sharing of knowledge with external partners to make your innovations work. Beyond the individual skills of relationship management, the business needs to be connected to open data publishers and consumers across all levels of the SME, to learn and share knowledge as well as open data.
To defend against imitators, SMEs need to be able to innovate continually and stay ahead of competitors – in other words, ‘new’ needs to be business as usual. Finally, the SME needs to be able to retain and hire a mix of interdisciplinary talent. Technical skills, to capture the value of open data, but also ‘softer’ management expertise to understand the demand for new innovations and products. While this sounds obvious, a failure to balance different sets of expertise and to facilitate clear dialogue and understanding between, say, data scientists and marketers, will undermine the ability to innovate.
Identify and address skill and capability gaps
SMEs and startups should undertake gap analyses to identify where key open data skills and competencies are missing or underdeveloped. Where possible, businesses may need to seek new hires to capture these specific capabilities, or undertake external training to help gain the skills and competencies to accelerate open data innovation. Open data use is virtually free, but this doesn’t guarantee innovations will be successful. SMEs need to invest in developing their skills and competencies, because innovative SMEs and startups are only as good as their team, and successful teams need to excel in catching and adopting open data.