All companies will be data-driven - or disappear. We call them

exponential organizations (ExO) because they are 10 times more successful. 


Companies such as Netflix, Amazon, Uber, Tesla or Airbnb have demonstrated the enormous disruptive effect exponential organizations can have on entire economic sectors.  It is not only the business idea that has made these companies so successful. Rather, it is the characteristics of a data-driven enterprise that shape the organization of these companies into exponential organizations. The future will belong to such exponential organizations, because no companies can exist that are organized differently. The advantages of exponential organization are too great. 

To become data-driven as an organization, you don't need more or better data in the first place. To become a data-driven company it is not enough to collect data and make it available. Hiring data engineers and scientists, letting them experiment and hope for the best is not enough. In the same way, the approach of working on employees mindsets is doomed to failure. In the end, all the talk of data as the new oil and the missing agility of the staff is nothing more than empty phrases of big software vendors and consulting companies to sell their software platforms, expensive workshops, lectures or whole projects.  Or do you know of any company that has successfully undergone such a "change"?

The ability to open up contexts is key

Information is not worth much in itself. Only when viewed in the right context does data deliver the desired value. The key to the data-driven enterprise is in contextual data, we call it "C-Data" for short. The contextual knowledge of employees is the refinery for deriving real value from any data. Only through the contextual knowledge and interpretation of knowledge workers can valuable insights be derived from the information gained and meaningful measures be initiated. It is only through the context knowledge of people that we find out which data will help us in which incidents, which criterion our algorithm lacks in order to function correctly in exceptional situations. 


You always start with the problem, the challenge in the specific situation. Then you create forward-looking actions. This involves designing possible futures and then taking action to realize or avoid one or more of these outcomes. Only then does one collect the data for this. Cross-functional and goal-oriented. The system-supported modeling of such complex cause-effect relationships additionally relieves our brain and helps us to better understand interrelationships. In the future, the work of knowledge workers will shift away from the analysis of data towards the optimization of decision models. 


A successful data strategy therefore does not start with data, but with decision-making. 

Free Whitepaper: 

"Why being data-driven
is no longer enough.


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beeBlum supports knowledge-workers to become data-driven

A company becomes data-driven when data adds value to the daily flow of business processes. When people benefit from it. This is not achieved by making more and more data available, but primarily by improving the opportunities for collaboration in the context of decision-making. The challenge here lies primarily in linking across domain and departmental boundaries. Without artificial barriers such as complicated authorization procedures, which ultimately only lead to misdirected energy to bypass the same. So what you need first and foremost is a more agile approach to collaboration. 

beeBlum is the first collaboration solution designed to make use of contextual knowledge, "C-Data", that is slumbering in your company. This way you not only make more out of your operational data, but also extract valuable knowledge. This can be information that would otherwise have been lost in emails, messengers or group chats, or leading indicators that have a decisive influence on the future of your company. You will be amazed how much knowledge you didn't know about... 


By analyzing the correlation of context and information, you can then find out which decisions can be improved with the help of additional data and derive targeted business cases for your data strategy. Even on a large scale. The result is faster and better, because data-based decisions, lower IT costs and more fun at work. 


Emotional intelligence is the key


It is well-known that we do not have our best ideas in the office. They're suddenly there. In the queue at the bakery, on the way to work or on the bike tour by the lake. Whenever it fits you, you can contribute to the challenges of your colleagues with beeBlum. By evaluating suggestions, making assessments, adding missing information or bringing in completely new ideas.

beeBlum informs you whenever one of your contributions has been particularly useful. This way you are much closer to your colleagues, get feedback and learn more about the benefits of your work. 


Everything gets better with the right people


Complex situations cannot be judged independently any longer. We all work in different directions, in a different context and on the basis of different experiences. The inclusion of different perspectives helps to analyse information more holistically. 

beeBlum makes it easy for you to incorporate the assessments and ideas of your team, the whole company or even the crowd into a given situation. With the help of criterias you make information about resources, KPIs or soft facts measurable and thereby more comparable. 


Solution-oriented action


Decision-making  is the toughest part of team collaboration. It is characterized by insecurity or even uncertainty. beeBlum can help you to deal with these kind of situations. In our decision room you develop model-based alternatives for action based on the collected information. In the interplay of the selection of relevant criteria with different weightings, possible futures can be compared and evaluated. 

The pyramidal access to these models makes it much easier for decision makers to grasp a topic, to act quickly or to request further information.

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made with lots of     in Germany.