Ingenjörsvetenskap & Teknologi

312 följare

AI/ML projects for global Danish Retailer using Google Technology hos Demant

About Demant

We are a world-leading hearing healthcare and technology group built on a heritage of care, health, and innovation since 1904.  From hearing care, hearing aids, diagnostic equipment and services to audio solutions, the group offers innovative technologies, solutions, and expertise to help people hear better.

Headquartered in Denmark, Demant employs around 20,000 people globally and is present in 130 countries where we create life-changing hearing health, high-end audio, and video solutions.


About Audika Group

Audika Group is the largest department within Demant, accounting for approx. Forty-three percent of the company’s revenue. Audika’ s journey began in 1993 when the first stores were acquired in Australia. Through a strong acquisition strategy and healthy growth, we are today in 31 countries with over 2000 stores where we retail our hearing solutions to our customers. Today Audika has its own IT department that works closely together daily to support all our users out in the stores.


Google Technology to support our ERP solutions

Our Audika clinics are mainly driven by two different ERP systems (Microsoft nav and AX2012), Microsoft CRM, Microsoft POS, and an in-house build Diary management solution. All data is shared across systems and collected in our Datawarehouse from where we create data insights and reporting through cubes and PowerBI.

Recently we have decided to change our data strategy and move away from Microsoft and the on prem Datawarehouse to Google Cloud Platform (GCP). Utilizing Big query and Looker within the GCP for all our data & Analytics in the future. The switch has opened a lot of new exiting possibilities around analytics, especially in Artificial Intelligence and Machine Learning.


What project opportunities do we have?

As we are somewhat new in the area of AI/ML, this opens up some exciting project opportunities!

A suggestion of some project hypothesis could be, but is not limited to:

    1. How to organize an organization around AI/ML?
    • Is Audika ready to start on AI/ML?
    • How should our teams look like?
    • How do we succeed with AI?
    • What kind of skills should we have?
    1. AI/ML on Out of Warranty Customers
    • Do we call them in each year? Should we call them? When should we contact them? Should we call, mail or?
    1. Calling lists: What models work, and which don’t.
    • Who do we call first? On which clinic/region do we call first?
    1. Geographical mapping.
    • Where should our clinics be placed?
    • Where do our customers live vs customer DB.
    • How do we look vs competitors?

If any of these project sounds interesting to you or you have a suggestion of your own that could be a good fit, then please reach out to Mattijs Bastiaannet, Data Intelligence Manager at

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