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Data silos prevent digital transformation

Data Black Holes Survey: Chapter 2
Urgent Need for action on raising awareness regarding the consequences of data silos When asked about the biggest challenge in the use of data caused by their current data landscape, there is a clear message from participants. 41 percent agree that having key personas tied up with elementary data problems instead of working on the digital future of the company is the most pressing issue. A central data warehouse is of little help if it is undermined by individually created data sets. However, the detailed analysis shows that investments in defining uniform business terminology pay off. Companies that have not implemented such terminology have significantly more problems in using their data for new questions. This includes companies that have a central data warehouse that is undermined by individually created data sets. What are the main challenges in the use of data caused by the current data landscape? (n=318) But even a uniform data language is not the sole remedy. Companies that have implemented uniform terminology in a decentralized data landscape obviously have fewer problems in using their data than those without uniform terminology, but not as few as companies with a centralized data landscape. Insufficient data transparency and limited availability of data experts are major obstacles Regardless of whether you use a uniform data language, distributed data is difficult to keep track of. 46 percent of respondents consider a lack of documentation on existing data and analysis processes to be a major obstacle in improving their data landscape. It is the second highest rated organizational challenge when it comes to implementing chosen approaches. In companies where there is a lack of uniform terminology for data, an even higher proportion of companies have faced this challenge (55 percent). 46 percent of respondents consider a lack of documentation on existing data and analysis processes to be a major obstacle in improving their data landscape. This lack of transparency drives the creation of even more silos. 45 percent agree that existing data sets are not reused because they are not documented. Respondents from companies with a decentralized, non-uniform data landscape see an even higher risk (52 percent). What organizational and technical challenges have you experienced in implementing approaches to improve the current data landscape? (n=312) This is clearly why the highest rated approach to dealing with the challenges caused by data silos is to create transparency about existing knowledge of data and foster collaboration (49 percent). Participants from companies across all data landscapes agree here. Best-in-class companies in particular are taking this measure (60 percent). Lack of business accountability for data impede digitalization However, documentation cannot be made by magic. It requires the contribution of data experts. But data experts are in short supply. The majority of all respondents (55 percent) sees personnel bottlenecks as the most serious hurdle in the implementation of measures to improve their data landscape. Companies with a centralized, uniform data landscape perform significantly better in comparison to others. Yet there is also a lack of organization and processes as well as business accountability for data. While best-in-class companies appear to have achieved advances here (31 and 26 percent respectively), laggards struggle at an above-average rate (48 and 54 percent respectively). What organizational and technical challenges have you experienced in implementing approaches to improve the current data landscape? Excerpt, by best-in-class (n=87) Companies with a centralized, uniform data landscape perform significantly better in comparison to others. Only 29 percent see a lack of business responsibilities as a problem. Organization and processes are also significantly less likely to be lacking (only 27 percent agree). These measures therefore appear to promote the implementation of an orderly data landscape.

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