Five drivers of success for the data-driven company

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Data management is one of today’s most important strategic instruments for companies striving to make the best possible timely decisions and to assert themselves successfully in the digitalized world. We outline five key factors and provide even more helpful tips for transforming into a data-driven enterprise.

The digitization of enterprises and society significantly influences today’s business world and, even more, future business models. Offerings and value chains are changing drastically. Individualized offers and services, personalized approaches and automated processes are crucial to be and remain competitive.

Key to this is the management of data. It has become a must-have for the modern company to develop and live its own data-driven culture, to set up its processes and infrastructure accordingly and to equip its employees with the possibilities and skills they need.

A company that wants to remain successful in the future has to become a data-driven company. Of course, this does not work in an ad-hoc manner, but in a transformation process that integrates the following five factors:

1. Having a mindset and clear objectives

In order to successfully complete digital development and create an individual strategy for their own specific challenges, companies need a modern way of thinking first of all. It is essential to approach things from a data perspective and to think generally about the extent to which internal and external data can promote one’s own business. We call it Data Thinking.

2. Enabling employees

To concentrate the know-how on a few employees – usually on “the IT” and in best case the data scientists – is neither up-to-date nor sensible. In order to design and implement sustainable processes, it is crucial to train all participants in the specialist departments, provide them with the necessary know-how and impart the corresponding basic knowledge under expert guidance.

3. Keeping data up-to-date and clean

The knowledge to apply algorithmic, machine learning based tools – the artificial intelligence – also as a smaller company, is commonly available by now. However, often it is not used due to an inadequate data management in the company. Data is incomplete, inconsistent or erroneous. We are changing this through Data Cleansing.

4. Providing easy and secure access to data

In order to use data specifically for case-related analyses and reports, it is important to have access to all relevant data sources inside and outside the company. A technical requirement for this is to initially include differently structured data and to consolidate them all in one Data Lake for further processing. In the whitepaper below, we show how this works.

5. Making quick and good decisions based on data

To enable companies to react immediately to market conditions and secure decisive competitive advantages, infrastructure and employees need to be able to efficiently support and accelerate decision-making processes. Employees in the specialist departments need the means to quickly and easily compile and evaluate the necessary data and to create substantiated analytics and reports by themselves.

Exactly for this purpose, our self-service big data solution makes all existing data available and provides the interface to appropriate analysis and reporting tools. It gives easy and secure access to all relevant and ready-to-use structured data. And it empowers employees to deliver the best for the company.


This post is also available in: German