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Three Ways to Overcome Initial Data Sharing Hurdles

Alex Reynolds

Startup Manager

When we think about startup-corporate collaboration, many of the obstacles that get in the way of progress are the same time and time again. One recurring problem is the availability of data, gaining access to data and restrictions on how the data can be used.

In our conversations with corporates and startups alike, there never seems to be an apprehension in utilizing the other’s data (within reason) in delivering and creating new products and propositions. In fact, I would go so far to say that both are eager to share their data – what prevents them from doing so is the perceived risk. There are of course other reasons, but the management of risk and the associated exposure is the highest barrier to data sharing. All companies (I’m hoping so anyway) are well-versed in the rights and legalities of sharing data, whether Consumer Rights legislation or our modern day magna carta in GDPR. This would only increase their aversion to risk, leading us down a familiar path time and time again.

Proof of Concept and trial scoping conversations take place during the initial stages of an L Marks. It’s usually around the same time that our conflated expectations about sharing data have reached their peak. From this point onwards, the dialogue concerning data becomes entwined more with reality and the stakeholders begin to understand the blockers stopping the collaboration from progressing seamlessly ahead.

The blockers experienced are similar across the incumbents that L Marks works with: they have legacy systems which requires a less than easy checklist of tasks to be undertaken before any data accessibility issues can be addressed; the relevant data for the collaborations are stored in different systems with various controllers and managers, potentially adding a large array of stakeholders to manage; many will require an early-stage firm to comply with a non-exhaustive list of internal compliance and technical requirements. Something which many would be unable to meet given the stage of their development.

Whilst making sure a startup complies with the standards and regulations set by the corporate can be advantageous in securing potential commercial agreements in the future, it can divert the stakeholders away from delivering something spontaneous. By being spontaneous, the parties involved will undoubtedly come up against more problems but you’ll be better for it. If indeed parties find themselves constantly sticking within the parameters of the rules set, there is very little hope of adapting those rules when – let’s say – a new technology or business model emerges or understanding what the new risks are…

Depending on the startup offering, technical capability and the use case scoped out for a PoC/ trial, there are various approaches that could be taken to alleviate the issues concerning the sharing and accessibility of data.

Produce dummy data and simulations

For many, gaining access to data is key in proving value. The trouble is that many firms will not share this with anyone, even if it is anonymised! Whilst engaging in those discussions surrounding gaining access to the data (whether that be compliance/ legal etc), a standard tool in getting over that first hurdle a startup may face is to recreate the data as a dummy. To understand the context of the data it may be necessary to produce a data dictionary. A startup will need to discuss the context surrounding the data (at what touchpoints is this gathered and what’s its use) and set up a number of real-life scenarios which can act as a simulation. This is also a prime time to gain feedback from the prospective users by introducing them to the product. If the startup also has existing clients (especially in a similar industry), then it is worth discussing how they onboarded this client, what challenges they faced and how they worked around it.

Latch onto a cloud adoption strategy

Many incumbents are implementing their cloud adoption strategies. This is a prime time to become a ‘value-added’ service to help deliver additional value streams to what is probably already a resource intensive scope of work. One of the key advantages of cloud adoption is the ability to scale a service quickly. Being able to ‘latch’ onto a cloud adoption strategy and increase the current ROI at relative ease is a good way to sell any future engagement with the client and speed up the process in gaining approval from compliance if they can get the right strings pulled.

No to sandboxes, try synthetic

Previous engagements have seen sandboxes set up on our programmes. I would recommend that sandboxes are not established as part of the data sharing process. We’ve found that the data uploaded to the sandbox environments tend to be out of context and provide little value to a startup. An area of growing interest, specifically in regards to getting over the restrictions placed on using real data and creating data simulations is the use of synthetic data. Synthetic data is created with the help of algorithms and recreates the data needed to showcase value as part of a pilot. Having access to synthetic data to quickly prove a proposition can be extremely beneficial in proving that initial proof-of-value at the early stages of engagement. We would go so far as to suggest that all those corporates looking to build data driven services should be seriously considering utilising data synthetic services.

 

Alex Reynolds, Startup Manager 

If there is an interest in finding out about the outputs and insights from our Startup Innovation Labs or Intrapreneurship Intra-Labs then reach out to alex.reynolds@lmarks.com.

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