Data Accumulation

They say we live in the age of data and information – Big Data, Machine Learning and other techniques that work on big data help drive decisions, innovation and even everyday life.

ALPORA’s fund generation is based on data sets that are analyzed using specially developed methods to identify the most innovation-efficient companies in a market.

The first important and necessary step for this is the creation and maintenance of databases in which all relevant parameters about each company to be evaluated are recorded.

DatA Analysis

The data that ALPORA’s procedures require can be retrieved or provided for almost any company. From the amount invested in research and development to the number of patents filed – the information is usually available.

However, it is by no means all reliably compiled in one place – except at ALPORA.

 Throughout the year, we gather the data we need for our analysis from a variety of sources: From freely available directories on the one hand and through conversations, interviews and cooperations on the other.


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In order to ensure the quality, i.e. in particular the objectivity, of the data, ALPORA itself does not offer consulting services for improving innovation efficiency in companies. Instead, we offer companies an equally objective analysis of their successes and areas of potential as compensation for their efforts.

In this way, ALPORA remains independent and the benefits for both sides are maximized. ALPORA is interested in an independent evaluation for the development of innovation funds. And on the entrepreneur side, only objective analyses based on validated data are valuable feedback.

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Data Parameter


Data Processing

The data ALPORA collects from companies or extracts from available databases is initially available “in raw form” – in the form of table entries, interviews or annual reports.

This means that they must be further processed with great expertise before analysis – for example, by ‘translating’ qualitative answers in an interview into concrete quantitative data, by merging information from different sources or, conversely, by ‘cleaning’ a piece of information of additional, disturbing data.

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What data is included in ALPORA’s calculations?

ALPORA’s analytics methods are each based on several dozen parameters that are used in the calculation of weights and results for each analysis.
In summary, they can be divided into two very broad categories – input and output parameters – and seven somewhat finer categories:

  • Research and development
  • Knowledge creation
  • Innovation culture
  • Collaborations
  • Commercialization
  • Patent success
  • Process improvement
ALPORA analyses various criteria for its innovation funds.

From data to results: ALPORA’s methods

In the second step, the collected, cleaned and processed data is examined using machine learning procedures and the analysis methods developed by ALPORA to identify the most innovation-efficient companies in a market.