Project Description

Calculating the Value of Your Data

SwissRe works to help organisations manage the various risks that threaten their business. A stunning 75% of the risks organisations face are uninsured, which has a significant impact on resilience and business continuity.

For the accurate assessment of risk, data has to be harvested and evaluated on a wide range of fields to provide a holistic perspective of any given situation.  Despite the huge scale of the business, they only have 15,000 employees globally, so have to do a lot with a relatively small workforce.

This is a highly knowledge-intensive business, with each product heavily data-oriented as risk is assessed and priced.  For SwissRe, data has driven the business for 150 years.

The process begins by examining what data is required to understand the customers’ environment, and how it can be acquired, even if it resides in external repositories.  These external sources are an increasingly fertile source of insights, especially as the Internet of Things is generating such huge volumes of data.

With such huge quantities of data, however, comes huge challenges in terms of safely storing the data, and curating it so that insight can be gleaned in an efficient way.  This curation helps to inform analytics, which in turn drives decisions.

Creating value with data

The company realised early on that they had access to really good data, but they weren’t making the most use of it.  A major part of the problem was that people only really looked at data in terms of their own specific use case rather than the whole value chain.

This was emphasised by an event that brought data users together to examine their understanding of the data challenges of people across the business.  The event revealed a lot of commonality in terms of those challenges and greater awareness that fed into a new data strategy for the business.

One SwissRe

Central to the strategy was to think of data in terms of one SwissRe rather than individual teams or silos.  Each of the capabilities in the value chain would provide value to the organisation as a whole.

To embed this capability into the business required the right culture and mindset to ensure that the whole data lifecycle was nurtured.  After conversations across the business, five key elements were identified.

While the company has used data for 150 years, the belief that data is a key competitive asset is something that needed reaffirming.  This was fermented by investing in the skills of the workforce, especially around data and analytics.

It was also important to be able to tell stories that provide a compelling narrative about the importance of data.  This was especially useful in securing buy-in from non-data professionals.

Through all of this, the value of data is being democratised throughout the business and therefore enabling the collective intelligence of the organisation to come to the fore.  Data provides fresh capabilities to augment and extend the knowledge of the 15,000 employees and this shift in mindset is beginning to germinate.

The company has a team of data champions that help to evangelise on the value of data, and through this group, it is hoped that the data-driven transformation of the business will continue apace in the coming years.


Bianca revealed that data literacy is not enough in itself, especially if people are not able to be critical analysts of the data they possess.  Is the data biased, for instance?

Bianca also said that honesty and transparency is key, as data investments are a long-term effort that may not deliver short-term and immediately evident improvements to the bottom line.

Group Discussion

  • Do you have a view of your entire data value chain?
  • What are the steps you take to mature your data value chain?
  • How do you manage to break down the data silos in your organisation?

Data and business strategies need to be the same, but due to a lack of understanding of data among leaders, the narrative can often present them as distinct.  There is also often a discrepancy between the talk about data and its importance, and the actual activities to put data at the heart of the business.  It’s much easier to talk the talk than it is to walk the walk.

Value chain was not a familiar term to all as it wasn’t something they used in their organisations.  Instead, they would often assess the value of data at the end of each project.

Silos were a common problem, especially among those working in multinational businesses.  Breaking them down could either come top-down with executives taking responsibility for the task or bottom-up via a community of data scientists to come together and share ideas, problems, and insights.

Video credit: Bianca Scheffler, SwissRe

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