Sebastian Weyer, CEO of our latest venture, explains how Statice can help your organization with getting maximum utility out of data while respecting and protecting personal information.
Customer-centric and data-driven companies increasingly rely on data to predict, analyze, and innovate their products and services. In case that you identify your company in this statement, you will also agree that the thirst for data is not slowing down at all and that you are generating more and more data from your own customer touchpoints. The IDC is even expecting global revenues through big data to reach $203 billion in 2020 (CAGR of 11.7%).
The problem is that in order to truly drive innovation in your company, you need to extend your focus towards what you don’t know instead of what you know already. For example, data sharing is a key element driving innovation today. HBR shows that already in 2015, 64% of companies were using 5 or more different data sources combined to make operational decisions.
This is already a great start but we think there is way more to be done. Instead of solely accessing external data sources, we see more value in opening up your data for a collaboration together with partners. This does not only help you to innovate on existing products but also to create new product offerings together with partners. One of our favorite examples for such collaboration has been already published by Stefaan Verhulst and David Sangokoya in their medium blog post.
The problem is that “the overwhelming majority of new data is created by consumers.” and utilizing personal data is becoming increasingly difficult.
This is primarily fueled by the new General Data Privacy Regulation (GDPR in short). The GDPR is a new EU-wide regulation that strictly defines the frame of utilizing personal customer data for any company performing business operations in the EU (If you are interested in the exact implications of the GDPR, I strongly suggest to have a look at this blog post by Pedro Vaz Sa).
Starting May 2018, the GDPR will completely change the way your company will deal with private data. It gives a lot of power back to the individual consumer in enabling every single individual to decide what data he or she is willing to share. And this has been long overdue.
Why? Because we tend to forget that at the very core of this information-driven world lies the individual user, a human being with a personal identity, interests, motivations, emotions, and actions that are continuously becoming transparent. While some degree of this transparency is necessary to enable companies to innovate and offer users new and better products, services, and experiences, we are walking a fine line between innovation for the greater good and compromising an individual’s personal life.
Data privacy is turning into an entirely new asset and will allow you to deal with customer data more freely. This might sound like a contradiction in itself but is exactly what we want to achieve with Statice.
We are building Statice to help your company to foster new data-driven collaborations while always ensuring the absolute privacy of your customers’ data.
Statice is a software that allows you or your partners to handle data more freely and efficiently. You can easily share and collaborate over sensitive and private customer data without ever exposing it. We do this by generating synthetic data from your original data.
Synthetic data — what is this?
A synthetic dataset is a newly generated dataset, containing no original data entries — but containing the same statistical validity as the original data.
If we look at the image below, we can see an openly available dataset on heart diseases. The data points in the original as well as the synthetic data have absolutely no overlap. But if we go ahead and extent both data sets by several hundred more entries, we will see that the statistical properties are identical.
Data sources: Hungarian institute for cardiology, Universitätsspital Zürich, Universitätsspital Basel, Long Beach Medical Center
Secondary uses of data, such as BI analyses or training Machine Learning models can be easily done without having to constantly ask for customer consent and without ever having to fear revealing personal information. The benefits are pretty straight forward: More complete decision-making, new business development, and multi-actor and multi-sector collaboration.
We are excited about the journey ahead and want to become a core part of the future collaboration economy. If you are handling data in the finance, insurance, or healthcare sector and want to help us shape our product more closely to your exact needs, you can do so by answering our survey.
And in case you just want to chat, learn more in person, or even want to test our product, we are always happy to chat. You can always drop me a line at firstname.lastname@example.org.