Predictive Analytics detail pageImagine that you could predict when a machine is about to fail, if any of your customers are about to leave, know how your project stakeholders are feeling towards your deliverables and what impact it has on your cash flow.

By applying predictive models, using the MS Azure Machine learning platform this and so much more is now possible, without big upfront investments usually reserved for global corporations.

Here at Hejmdal we are using our extensive MS Dynamics experience, to create standardised Machine Learning packages, these can be made available to your company immediately, enabling you to gain that extra insight in your business data, and truly leverage the value that lies within it.

The best thing is that you only pay for the amount of queries you send to it, so there’s no upfront investment.
If needed then we can fine-tune the algorithms to be more specific to your data set, thereby increasing the accuracy of the predictions.

Hejmdal can apply a number of different types of algorithms to your data through Azure Machine Learning, and we do not just use out the box solutions, although the studio comes with a lot of good standardised algorithms, then applying customised algorithms using R-Code is often needed to achieve the best accuracy in our predictions.

 

Based on registered hours & HR data we are able to measure 21 features on your employees. This allows us to predict the likelyhood that your employees are about to burn out, and therefore intervene before key staff leaves.
Allowing your to keep the knowledge base in-house, realise savings on hiring people and retraining them.
We developed a model, that based on your historical data can predict the impact of assigned resources to individual tasks and projects. This allows project managers and the resource department to identify potential bottlenecks in delivery earlier on.
We are utilising the Microsoft customer churn prediction model, which is based on millions of observations. Allowing you to leverage this insight on your own pool of customers. This enables companies to contact customers before it’s to late.
“Currently under development”