How can entrepreneurs best manage their time


Over 130 years ago, Herman Hollerith developed his first tabulating machine and thus initiated the industrialization of data processing (DV). As early as the 1890 US census, his system received good ratings: "This machine works like the mill of God, but it beats it when it comes to speed." Even today, companies still try to fulfill the dictum in the best possible way - to process more data efficiently, in high quality, from different data sources, in "real time" and beyond their own organization. Data management can do a good job here.

To the study "Data Management 2020"

Data culture? Running!

The study "Data Management & Data Quality 2020" by COMPUTERWOCHE and CIO in cooperation with Tableau Germany and Datavard has now examined the state of data management in German companies in 2020. After all, data represents an important competitive advantage, especially in the digital world, if you know how to use its potential. The present survey shows that companies and institutions are actively working on the implementation and optimization of data management - only a small proportion of the respondents are currently unable to gain anything from the topic. For more than 80 percent of organizations, the discipline is at least more important, and in every fifth company it is even very relevant. A clear trend: rising. Many companies share data with external partners, they consider their data culture to be good, have a positive assessment of the visibility of data sources for end users and have coupled data management with tools for artificial intelligence (AI). And last but not least, they are working on keeping the data quality high or improving it.

No wonder, because concrete and timeless goals have always been behind the use of data. They are primarily intended to improve existing processes and products, optimize business models and administrative workflows, monitor IT itself and increase the security of business decisions. Only 7.6 percent of the study participants stated that they wanted to use data to optimize "FTE costs". This point was mentioned above average by larger organizations and IT staff among the respondents.

Open construction sites en masse

However, weaknesses also emerged in the study. For example, given the multiple demands for disruptive business models, there is no clear picture. Almost 27 percent of those surveyed would like to develop a new business model based on data. Whether there are surprisingly many or noticeably few voices depends on your own perspective. In addition, the study shows that representatives from departments respond far less optimistically than study participants from top management - it is precisely business users whose decisions are to be accelerated and improved through data. There are also construction sites such as the search for suitable skills, the right "mindset" and a modern corporate culture. These challenges cannot be solved with software; above all, they require time and commitment.

Last but not least, there are doubts about the overarching vision: Not even 38 percent of companies have a digitization strategy at the beginning of 2020. Less than half of the companies have an IT strategy - hard to believe. So it is not surprising that the question of the data strategy cannot arouse euphoria: Almost 30 percent of companies have a general data strategy, and only one in five companies has dedicated data management or data analytics strategies. The rule of thumb: the bigger the organization, the sooner. In almost all companies, the integration of the data or data analytics strategy into the overarching digitization projects is rated as strong.

Showstopper data silo?

Data silos, on the other hand, one of the greatest challenges on the way to digitization, are not the expected show stopper - decentralized data storage acts like a manageable challenge for data management. After all, 85 percent of companies store their data (mostly) centrally, a good 30 percent store it completely centrally. However, the gray area for "predominantly centralized / decentralized" is quite large, it encompasses more than two thirds of the organizations. Silos can form and harden at their edges. Nevertheless, only 23.5 percent of the study participants describe the phenomenon as (very) a hindrance to data management; It is 60 percent in total with the votes that find silos "rather obstructive". In contrast, 39.2 percent of those surveyed see data silos as hardly or not a hindrance. More often than not, these are IT managers and employees as well as companies with a lower IT budget. In the case of IT budgets over ten million euros, however, the opinion "rather obstructive" prevails.

However, it also fits in with the fact that many data-related processes are not yet automated. Four out of ten companies work manually (at least partially) on linking data, and 28 percent of organizations use software tools. However, it can be assumed that the approaches are not mutually exclusive, but complement one another. This is especially true for larger companies that mainly use internal meta-databases and tools for data discovery, for example. When it comes to connecting data management to AI systems, however, the integration processes are almost identical. Here, too, larger organizations tend to resort to software more than small companies. Almost 72 percent of the companies use AI for data acquisition and 65 percent for data analysis / evaluation. Predictive analytics, on the other hand, has not yet established itself on a broad front; the focus here is also on larger organizations.

In view of the required time-to-market, small and medium-sized companies in particular need to increase the degree of automation so that the data (within the framework of the law) can flow between the instances. The study also showed that smaller organizations often lag behind large companies in terms of maturity and implementation. The latter tend to have more resources and rely more consistently on tools and the support of external service providers. In addition, where available, they integrate the data strategy more closely into digitization.

A question of data quality

There is a slight all-clear on a traditionally hard-fought front, that of data quality. According to the present survey, companies have done their homework. Almost 58 percent of those surveyed are satisfied or very satisfied with the data quality in their organization. On average, just one in eight study participants is not satisfied. Only among the respondents from specialist areas was dissatisfaction higher or satisfaction lower. The values ​​for the relevance of the data quality are similarly clear. This should also increase, the topic is becoming more and more important: With a view to the future, almost two thirds of the study participants describe the importance of data quality as great or very great.

According to the COMPUTERWOCHE study, the status quo is at least optimistic when it comes to companies' awareness of the value of data in digitization and the tasks associated with it. In the years to come, the vision needs to be turned into an integral part of the business. The organizational challenges are great, data management covers not only the tools but also cultural, structural and personal qualifications. Every third company complains about a shortage of skilled workers in data management, an innovation backlog and an unsuitable or missing "mindset" of the employees. 130 years after Hollerith's world-shattering invention, it would be time for another breakthrough.

To the study "Data Management 2020"

Study profile

Editor: COMPUTERWOCHE, CIO, TecChannel and ChannelPartner

Platinum partner: Tableau Germany GmbH

Gold partner: Datavard AG

Population: Top (IT) responsible for companies in the D-A-CH region: strategic (IT) decision-makers in the C-level area and in the departments (LoBs), IT decision-makers and IT specialists from the IT area

Participant generation: Sampling in the IT decision maker database of IDG Business Media; personal e-mail invitations to the survey

Total sample: 349 completed and qualified interviews

Investigation period: February 5th to 14th, 2020

Method: Online survey (CAWI)

Questionnaire development: IDG Research Services in coordination with the study partners

Execution: IDG Research Services