Positive Thinking Company customer, Julius Bär, initiated its own data science start-up and innovation laboratory under the name “Target Insights” in spring 2018, with the aim of using available data more efficiently – for example to improve customer service – and promoting a data-driven culture. In addition to finding and implementing profitable analysis scenarios, another key objective is to build up internal knowledge and experience.
Client relationships in asset management are particularly complex, which is why a deep understanding of these relationships and a high level of client knowledge are important differentiating factors in competition. Since data science projects typically require cross-departmental cooperation, the usual organisational structures with their usually strict separation between IT and specialist departments are conceivably unsuitable. Such projects therefore typically fail due to conflicts of competence, individual interests and a lack of willingness to cooperate rather than due to a lack of technical competence. An important step towards the success of data science projects is therefore the decision for a suitable, easily expandable team structure with clear roles and responsibilities.
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Article by Positive Thinking Company