The current “Tech Trend Radar” amongst analysing opportunities and risks of the top tech trends is listing digitalisation and data analytics as the ones certain to transform the entire insurance value chain. But what does it need to handle data in a modern organisation? Michał Denka and Krzysztof Krzosek, experts from ERGO Technology & Services, are breaking down the subject into the prime factors.
Krzysztof Krzosek, Head of AI & Data Delivery Division at ERGO Technology & Services, and Michał Denka, Senior Project Manager in the AI & Data team
We increasingly hear declarations that some company wants to become a data-driven organisation. But what does it actually mean? And how can it translate into achieving business goals?
Simply having the data is not enough. Anyway, everyone has access to some data – historical collected in the course of doing business, external market data, etc. It would seem that the most important thing is a good idea of how to use it. After all, it is enough to skillfully weave the collected data into the company’s strategy. It will undoubtedly allow you to navigate the organisation toward successful goal achievement with greater ease.
Meanwhile, it is not the mere fact of having data, nor the idea of using it, that is crucial – in the first place, we need to know what data we are dealing with and manage it correctly. Data Management is perhaps the most important aspect of working on data from an enterprise perspective. The value of data is what you do with it. To handle this process comprehensively, you need professionals who bring together the worlds of technology, business and data science – strongly supported by soft skills in working with stakeholders. So called “Data Leaders”.
So what kind of skills do these “Data Leaders” need? From my point of view, they are diplomats who need to be advocates for the proper creation and comprehensive implementation of data strategy in a challenging corporate environment. And this is not always an easy task as it requires convincing key stakeholders that their strategy for running the company needs to change. In this case, it is not just a matter of adding a “data” component but also modifying processes – and sometimes abandoning certain forms of market activities. The company’s transformation into a data-driven organisation will be incomplete without a comprehensive approach. It will clash with constraints and will not allow for effective change management.
Does it mean that “Data Leaders” should form a stand-alone unit, separate from the company’s organisational structure? Not really. This is because such a solution often results in their placement in an IT department or other technology-related structure. Meanwhile, what they do is not quite related to the creation and implementation of technological solutions. A good data strategy for real business process optimisation can be created on a simple sheet of paper. In my opinion, it is important that people representing different areas and different levels of sensitivity feel the need to be “Data Leaders”. Consequently, they are able to be ambassadors of the right approach to data in their departments and build a unique set of competencies to find synergy in the creative collision of different experiences and personalities. A community of leaders built in this way enables real innovation.
At every stage of our work on data, we must remember that without people, it has no meaning. Their cataloguing, management and interpretation must allow them to solve real problems and serve business objectives. Disconnecting data from the business can lead to its downplaying and losing the market advantage.
This risk is particularly high because good practices in data management and data strategy building come from academia. And while the scientific basis for using data is fundamental, university standards do not always align with rapidly changing business needs. Some activities undertaken by academics often do not have a strongly established business case. In the world of science, this does not invalidate the study being conducted, as such cases defend themselves by the intellectual value they bring. On the business side, the approach needs to be more focused on tangible and measurable results. The actions taken are expected to bring profits – both direct (e.g., increased sales due to a better understanding of customer characteristics) and indirect (e.g., building an image as an innovator, making the organisation an attractive employer).
When building a data-driven organisation, we need to lay a solid intellectual and technological foundation but also keep in mind the culture of the organisation working with data. This is especially true for the self-improvement of “Data Leaders”, who should keep in mind several essential conditions, perfectly described by Thomas Davenport of the MIT Initiative on the Digital Economy:
Text: Michał Denka, Senior Project Manager in the AI & Data team at ERGO Technology & Services and Krzysztof Krzosek, Head of AI & Data Delivery Division
Zur deutschen Version des Artikels geht es hier: Data Leadership: Wie sollten Unternehmen mit Daten umgehen?
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