Making the Leap from Lab to Market: the BigDataOcean Approach

Acknowledging that recent years of crisis called for innovations able to generate tangible business opportunities resulting in economic growth and job creation, H2020 program demands remarkable focus on impact, coupled with a reduction in the distance between project results and the competitive market, especially when it comes to the Innovation Action funding scheme.

To answer such pressures, BigDataOcean – as an ambitious market-oriented H2020 Innovation Action – considers the stream of activities related to exploitation as fulcrum for making project results sustainable over time and capable of generating returns for project partners and well beyond.

As far as exploitation is concerned, BigDataOcean consortium relies on the innovation advisory practice made available by LINKS Foundation, namely ‘Journey from Lab to Market’ (JLM). It consists in a comprehensive methodological portfolio that unpacks the journey that every consortium has to undertake in order to turn research-led project results – data, algorithms and technological assets at large – into sustainable business ventures, either brand-new startups (i.e., entrepreneurship) or new business lines within existing organisations (i.e., intrapreneurship).

Looking back at the last five years, JLM innovation advisory practice has a successful track history in 10+ H2020 and EIT projects as well as in several industrial contracts. Worth of note is the strategic support provided so far to world-class business champions like ATOS, Amadeus, Engineering, and Reply, resulting in 3M€+ of revenue already secured by LINKS Foundation on this consulting service.

Taking a helicopter view, JLM methodology comprises four macro-phases, which are as follows:

  • The exploration phase proves the existence of customers’ gains and pains, and outlines a compelling proposition for addressing them.
  • The validation phase focuses on the iterative experimentation with real prospects meant to validate/invalidate relevant market hypotheses.
  • The execution phase deals with the ramp-up needed to turn the implemented strategy into a fully market-ready product reality.
  • The diffusion phase allows entering a path of revenue expansion, financial scale-up, and impact amplification in the quest for sustainable growth.

By means of JLM practice, business champions within the consortium have the opportunity to establish an experimentation playground where the value proposition and the business model are tested and iteratively refined during the project lifecycle in view of market feedback collected, latest sectoral dynamics and nascent business opportunities. This reflects the fact that companies often go through many iterations before they find a sufficiently large and lucrative set of customers that resonate with their product, either inside or outside the boundaries of a project backed by a funding agency. This evidence calls for a mechanism allowing to continuously incorporate outcomes of hypotheses tested into the business development process. As a result, JLM leverages lean startup and customer development principles to favour hypothesis-driven experimentation through a spiral of steps: this leads to an agile approach based on MVP tweaks and pivots, which has been the backbone of BigDataOcean operations in the second half of the project.

When it comes to operationalising such an experimentation playground, a noticeable strength of JLM has to do with not requiring a quantum leap in terms of ‘innovator toolkit’. In fact, consortia – especially business partners appointed for implementing exploitation-related activities – can rely on the portfolio of tools that they are already accustomed with, without the need to become acquainted with a new breed of tools previously unknown. As far as BigDataOcean is concerned, this strength is exemplified in the table below, which reports – without any claim to be exhaustive – prominent tools chosen for supporting BigDataOcean-enabled innovation in its various stages. The resulting portfolio encompasses both state of the art instruments and ad-hoc tools (marked with an asterisk) conceived by LINKS Foundation’s analysts to fill-in gaps identified in existing practices.

In the case of BigDataOcean, JLM innovation advisory practice has been adopted according to a three-pronged perspective:

  1. Establish a commercial partnership meant to valorise BigDataOcean platform by creating a long-term destination for forward-looking companies, organisations and professionals willing to redefine the way in which maritime data is collected, integrated, curated and harnessed.
  2. Support pilot partners in the exploitation of BigDataOcean end-user applications that extract knowledge, enable comprehension, and unlock value from maritime Big Data through BigDataOcean platform.
  3. Put each consortium partner – including non-profit entities – in the position of harvesting the fruits of BigDataOcean by turning them into seeds for organisations’ growth and societal impact.

Drawing on the extensive fieldwork experimentation – including the one held within the scope of BigDataOcean – JLM proved to be able to activate a new ‘innovation kernel’ that challenges some of the most ingrained habits in the circle of organisations familiar with EU-funded projects. In fact, JLM approach implies substantial changes with respect to the status quo, which are summarised as follows.
In terms of mind set, exploitation is no longer an obligation to be dealt with in the second half of the project lifecycle but it becomes the heart, the engine, and the ‘metronome’ of the project. This pronounced penchant for beginning with the end in mind – since the dawn of proposal drafting – results in a continued market-oriented approach that, in turn, brings the notions of sustainability, scalability, and replicability to the forefront.

As far as timing is concerned, this approach allows to accelerate technological development when needed and to keep pace with fast-evolving market dynamics: this marks a discontinuity with respect to rigid implementation-driven Gantt charts that usually determine the schedule of project activities on a contractual basis.

In regard to project monitoring and control, in the current state of play the progress of EU-funded projects is ultimately dependent on project management metrics related to the adherence with what is stipulated by the binding contract with the funding agency. Conversely, placing prospect engagement at the core of project development can alter performance priorities: this makes explicit the need to shift to metrics that capture specific prospect behaviour with the purpose of keeping track of the progress along the customer acquisition funnel and facilitating possible growth tactics.

Finally, validated learning adopted as modus operandi drastically changes consortia’s attitude towards failure. In fact, failure becomes an expected norm rather than an exception or an incident: this turns failure into an unparalleled chance to continually distil lessons learnt.

By Michele Osella, Matteo Ferraris

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