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Delivering decision support through user centric design

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Although research has shown that analytics systems that are designed with the user in mind lead to greater confidence in the decisions being made, user-centric design is often an afterthought.

Edgar Kautzner, Managing Consultant at Minerra discusses a successful approach that Minerra took with a large, multi-divisional organisation in the USA. They were able to significantly increase user adoption of the analytics functionality by delivering an outcome with a very strong focus on usability and user experience. The project was also underpinned by a sophisticated data warehouse automation mechanism.

The solution delivered a level of decision support not previously seen in the sector, and won an award for innovation.

The presentation was delivered at the Melbourne Business Analytics Conference on Thursday 13th of June, 2017.

A video of the presentation can be found on YouTube:
https://www.youtube.com/watch?v=0raamq0Pqps&t=3s

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Delivering decision support through user centric design

  1. 1. Presentation by: Edgar Kautzner, Managing Consultant, Minerra Delivering decision support through user-centric design 13th July, 2017 Melbourne Business AnalyticsConference Centre for Business Analytics, Melbourne Business School
  2. 2. Minerra Delivering decision support through user- centric design Edgar Kautzner, Managing Consultant
  3. 3. Access Unlock the power of your data Understand Make sense of your data Decide Use your data to inform decision- making About Minerra • Training and mentoring • Analytics as a service – outsourced analytics function • Analytics report / dashboard development • Analytics architecture consulting & design review • Data integration and preparation • Data warehouse design & delivery through data warehouse automation
  4. 4. Setting the scene Large, multi-divisional organisation in USA • 25+ divisions • 100K+ employees • Nationwide reach Online recruitment system processed 1 million job applications annually The system couldn’t cope with demand or user requirements Adoption of recruitment BI system was very low. • Very poor user perception
  5. 5. The Solution
  6. 6. The Solution ■ Complete re-build of recruitment BI system – Using decision-centric design and right-service principles ■ Redesigned to match the recruitment process – Rather than the recruitment system data structures ■ Data warehouse automation technology was used – To quickly implement changing data and business logic requirements ■ Frequently required reports and dashboards were pre-built – Appropriate filters were provided to maximise flexibility and utility ■ A recruitment analytics team was formed from recruitment specialists from within the business
  7. 7. Project Outcomes ■ Users loved it!! – The recruitment analytics team were converted from strong detractors to enthusiastic champions ■ The system delivered an unprecedented level of fit and sophistication ■ 2,000 regular users of the BI system ■ Won an award for technology innovation in the sector
  8. 8. Business Benefits ■ Tighter linking of HR goals with strategic goals – Demographics of workforce to match demographics of USA ■ Significant recruitment cost savings – Reduction in time to hire – Sourcing strategies optimised – Significant improvements to recruitment process – Tighter control of bulk recruitment campaigns
  9. 9. Key Learnings ■ Always start from the decision requirements of the users – Decision-centric design of the data structures – User-centric design of the interface ■ Use data warehouse automation! – BI requirements ALWAYS change and evolve (and this is a good thing!) – Set yourself up to deploy these changes RAPIDLY ■ Usability and user experience is paramount – Use right-service BI principles ■ Design for scale and flexibility
  10. 10. enquiries@minerra.net www.minerra.net Thank you for your time and attendance.

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