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Automation improves productivity in major service organization

Automation of high-volume tasks saves time and costs in the largest Nordic service organization in its field

Consultants on the case

Aksel Larsen

Aksel Larsen

Frederik Jørgensen

Frederik Jørgensen

Sector: Trading

Region: Scandinavia

Business intelligence
Data governance
Data strategy
Data streaming
Machine learning
Master data
Process automation
Web app
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Identify

Challenges and opportunities

A major service organization contacted us as it was spending too much time and money on administrative costs. The organization offers specialized knowledge and counseling for businesses and has cases that range widely between employment law, collective agreements, entrepreneurship, and global market affairs. When the company contacted us, each of its cases contained non-digital information and material that was ungoverned and scattered in different documents, e-mails, and human hands. As a result, its cases were rarely closed and journalized which meant relevant information was difficult to find. It also put pressure on onboarding as less experienced employees had a low degree of self-reliance, which put additional pressure on experienced colleagues. Ultimately, these issues led to a high turnover rate and a decreasing service quality and consistency.

 

In collaboration with the company, we identified the opportunity of a new data system. We could automate the administration process related to case management, by tagging cases with the correct keywords and assign them to the correct responsible. In this way, the organization would gain trustworthy information about each case which would increase productivity and onboarding through a standard process with more accessible information. 

 

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Qualify

Analysis and evaluation

To discover the smartest procedure, we made sure to evaluate and assess the course of action and prepare for implications. We decided to split the data strategy into two main data projects. The first project was an internal Master Data system that could assign all cases to the correct responsible and  track the maintenance, hence the credibility of its common knowledge. For example, the correct people would be notified, if any specific law or affair affected the knowledge. In this way, the organization could always be sure that its public information and counseling was up to date. 

 

The second data project was a case-tagging system developed through Machine Learning. The purpose of this system was to digitalize, systemize and automize all case material, so every case and future inquiry would be tagged with the correct field and issue. In this way, the cases would be more accessible and manageable. Additionally, less administrative time and costs would be spent on searching for material and screening cases. Throughout the development of the data projects, we engaged and involved all relevant project stakeholders.

 

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Realize

Implementation and handover

After the qualification of the data projects, we moved on to the stage of realization. The data systems were developed through a process of prototyping, testing, and evaluating. We made sure to validate all data and test the functionality of the data systems on all target devices. Afterwards we designed and executed a handover plan for 250+ employees in the service organization. Through the plan we could ensure that the data systems would be integrated and adopted in daily business processes and IT-operations. After the integration of the data systems, Copenhagen Data was pleased to see that the service organization was much better able to assign responsibility and navigate in its knowledge and cases. Additionally, employee satisfaction and the quality and  consistency of the company’s services increased drastically. 

Results

  • Automation of high-volume administrative tasks carried out by costly subject matter experts to save €200,000 annually
  • Maintenance-free data-driven governance process that assigns data quality ownership based on employee merits saving €50,000 annually
  • Certainty of master data quality used to ensure consistency in client-facing counselling
  • Employee retention improved by 5%
  • Ready to merge services and client base with the other organization and realize economies of scale