cplace Insights
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cplace Insights

Guest Contribution QuinScape: Why modern Low-Code platforms need to make their data available

On modern Low-Code platforms — such as the project management software cplace — data is generated at breakneck speed; the significance and value of this data for analysis purposes is often underestimated. Process data that is generated interdisciplinarily and across departments in collaboratively used software is often of particular importance.

Common master and transaction data can often be easily identified as well as stored and evaluated in a company-wide, central data repository. The further the data reaches into the everyday work process of the departments, the less findable, high-quality and up-to-date the data is. After all, a large part of the daily work still operates in the realm of Shadow IT: project reports are created in PowerPoint, schedules are shared via Excel.

However, it is precisely this data that would be exciting to evaluate. Data on process statuses, current challenges in the maturity of products (e.g. in drug research or vehicle development) and, for example, the current life cycle of a product. This data as a direct result of various participants’ work contains exciting information which could lead to important insights.

Because they are easy and quick to adapt, Low-Code platforms are increasingly covering changing core processes and becoming central building blocks of IT system landscapes. Thanks to their sometimes deep connection to other important core systems of a company, they have holistic and highly up-to-date data at their disposal.

Using the Low-Code platform cplace for project management, answers can be found to questions such as “What happened in my project or product development?”, “Why did it happen?”, “What will happen if I do not intervene?” and “What should I do to ensure that my desired outcome occurs?”

Classic business intelligence questions, also known as the four methods of analysis:

  • descriptive analysis
  • diagnostic analysis
  • predictive analysis
  • and prescriptive analysis

Above all, looking into the future (prescriptive analysis) will become an important topic in project management for many companies. Here, an artificial intelligence (AI) is constantly enriched with the process data of project management to be able to make early predictions for critical paths, tasks or project sections. Based on these results, the corresponding countermeasures are automatically interspersed simultaneously. The problem is therefore solved before it arises.

But let’s not fool ourselves: even with all these analyses, the projects of the future will never run perfectly. But if we manage to significantly increase the number of projects and processes that run according to plan, we will have already achieved a lot. For this, however, we need continuous, simple, and fast access to all relevant data of a company.

That is why QuinScape, for example, has developed the Analytics Connector for cplace together with collaboration Factory. With this extension, data can be transmitted in real time to a central data repository such as a data warehouse. Process and project data can thus be made centrally available and evaluated.

Written by René Weinhardt, IT-Consultant bei QuinScape GmbH.

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collaboration Factory AG

collaboration Factory AG

collaboration Factory AG is the company behind cplace, and helps companies to successfully manage complex business processes.

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