MACHINE LEARNING

Attain a higher value from your data with machine learning

Improve efficiency with intelligent systems

Machine learning enables you to automate time-consuming and repetitive tasks and predict user behavior. This opens up possibilities for improving the organization and implementation of machine learning solutions can help you optimize the work week, decrease errors or improve the user experience.

The simple explanation is that machine learning is all about using and utilize the data in an intelligent manner. Most companies have big amounts of data, and the challenge lies in how it best can be used to create value. IIH Nordic have successfully helped many Danish and international organizations with implementing machine learning technology to efficiently reduce their costs. We have great experience with seeing the possibilities and utilize them in the best possible way. our experts are ready to help you get started!

Henrik Stenmann

CEO

henrik@iihnordic.com
+45 70 20 29 19

What is machine learning?

Short and sweet, machine learning is about creating computer systems that can learn. By collecting data and analyzing it, the system can, for example, learn that certain inputs lead to a specific output. This enables the system to make predictions or recommendations, that with a high likelihood lead to the desired result.

Machine learning can create intelligent systems that can solve complex assignments without manual interaction and programming for each and every single task.

If you want to know more about machine learning and what it can do for your organization, you are welcome to contact us for a meeting where we show you the endless possibilities of machine learning.

Unlimited possibilities

The biggest barriers for organizations to use machine learning are usually related to a lack of data or lack of understanding of the possible situations it could improve. The truth is that there are endless opportunities, making it a challenge to assess what creates the most value for your organization.

Digital understanding and application of data are fundamental to our work at IIH Noric, and therefore we also have the required experience and understanding for the implementation of machine learning solutions that create value for your organization. Over the years we have helped several larger organizations to execute ambitious technological projects, that increased their value. We have among others:

  • Automated tasks

    For example, prioritization of inquiries to customer service or identification of irregularities in complex datasets

  • Understand the context

    For example, understand how specific product-features impact sales or how the number of customers in a store varies during a day.

  • Predict the user behaviour

    For example, understand what link a user will click on or what products a user is interested in

Case: Intelligent Prefetching

IIH Nordic has developed an Intelligent Prefetching tool that enables you to improve the load speed of your site without changing your content or structure on the site. The tool can predict where the user will click next and can preload that page, making it show instantly as soon as the user clicks on the link. The tool makes predictions based on a machine learning model, that use data from that single user’s session to predict what page the user most likely will visit next.

By continuously analyzing the results of the Intelligent prefetching, the engine can learn to use the accessible data better and make more precise predictions. Based on this, the Intelligent Prefetching tool learns from itself and becomes more precise the more users it gets to analyze. Intelligent Prefetching can, therefore, improve the user-friendliness of your page, as the user will experience a page that loads instantly.

Do you want our help with improving your user experience? Read more about Intelligent Prefetching here or contact us to hear more.

Read more about Intelligent Prefetching

Case: Optimization of resources at Falck

We collaborate together with Falck to implement machine learning solutions, that can use data to predict the need for roadside assistance. This enables them to improve their scheduling and thereby optimize their use of resources.

  • By predicting the overall use of roadside assistance, Falck can now more easily match their staffing across the different hours of the day based on the need for assistance. This helps them optimize their scheduling and minimize waiting time, which can be seen at the bottom line at the end of the year.

  • By more precisely predicting when and where there is a need for their different services, Falck can plan their routes better. This means that the routes and driving time can be optimized, by for example let a car stay in an area after completed work, based on a high likelihood for another demand in the same area, instead of driving back to the station. This enables Falck to reduce their response time for customers in need, as they will experience shorter waiting times.