Big Data – Controlling

Big Data is the trend par excellence in the 21st century. Computers and storage are becoming cheaper, what allows the analysis of vast amounts of data in very short time. The targeted use of Big Data is essential in the future in decisions making.

What does big data mean?

It is characterized by four characteristics: variety, quantity, processing speed and reliability of the data. There are challenges especially at the diversity and trustworthiness. Speed​​, even with large quantities, with today’s servers no longer is a big challenge. Frequently the processing of large amounts of data is instead of called big data also known as business analytics, like the solution name from Microsoft for this area. Worldwide, it was evaluated, that the global amount of data doubles every two years .

Big Data and Controlling

Controlling increasingly takes on the role of business partner management. Here it is important that the vast amounts of data are not only processed by the controlling, but also recommendations for action will be developed. Nowadays the Controlling must analyze data from different areas, not only their own financial indicators. This includes the whole value chain from supplier to end customer. Many companies miss the Big Data trend. Barriers are mainly a lack of know-how, organisational ambiguities, too high costs or lack of qualified personnel.  It appears clear, however, that the trend towards real-time reporting goes on. Operational planning will change radically. In the strategic area, which is indeed a management task, we see rather less influence. Scenario analysis will replace the linear extrapolations often used nowadays. These are easy to generate and play through with Big Data. Thus, the decisions will be made data-driven and abdominal decisions minimized.

How should you build up a big data project

  1. Assessment Phase: Definition benefits and opportunities.
  2. Readiness Phase: Definition of desired and actual state. Analysis IT infrastructure
  3. Implementation and Integration: Existing infrastructure will be adjusted
  4. Consolidation and Migration
  5. Start using Big Data
  6. Reporting Analytics: Beginning analysis of the data collected
  7. End-to-End-Processes: By fully monitoring of business processes, transparency and optimization options can be enforced
  8. Optimization: In the last step you can then optimize the individual areas

Success Factors and risks of Big Data

The Big Data strategy should be value-oriented and have clear goals. The responsibility belongs to the top management and this needs to communicate and control the attainment of the objectives clearly. The project should be implemented in stages. A measurability of project success is obviously very desirable (for example, during the survey of a return on information).

One risk which has to be mentioned is compliance. Privacy Policy may suctioning preclude large amounts of data. Even the theft of data by employee needs to be taken seriously as a risk, and the data has to be protected accordingly. Also a definition and statement risk exist. One has to question whether the figures generated from the models are really correct and still up to date constantly. Not that decisions would be made based on misinterpretations. To the point steady quality of data you should keep an extra eye. Quick it happens, the possibility of errors, but these are not recognized in the large quantity.

Take aways

Surprisingly, today many companies use Big Data hesitant. On CFO level, the issue is indeed talked about,  but the active implementation is still lagging behind. Many corporate leaders see, especially in the integration of unstructured data, a big problem and believe that Big Data is difficult to insert into the existing organizational structure of the company. Likewise, the standardization and automation will be assessed as very important, but also seen as associated with considerable problems .

I have a lot of experience in the finance and IT interface and would be delighted to be able to support you in this area. Contact me under

Thank you for your attention.

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