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Advanced Analytics

Although the concept of Advanced Analytics has been trending for many years, many organizations today still struggle in really understanding its meaning, envisioning the opportunities and embracing a successful implementation.

As element61, we look towards analytics as the logical ‘next step’ and strengthened by our 10-year experience of guiding many Belgian organizations towards business intelligence maturity, we envision the use of advanced analytics as a valuable addition in a best-practice Business Analytics set-up. In that vision, element61 offers coaching, guidance and implementation support on advanced analytics to those organizations envisioning to getting started.

Advanced Analytics – also called AA - can be defined as:

"the use of new mathematical approaches aimed to turn data into new insights” 

It thus pins more to a concept rather than a specific software or application. It can be applied for pure analyses (e.g., understanding what drives what) but similarly for production solutions (e.g., a product recommendation engine). As such, it’s relevant for technical teams such as BI and IT as well as business teams such as Finance, Marketing and Sales. Specific proven use-cases are understanding the drivers of customer churn, predicting the risk of financial default per supplier, forecasting the revenue taking into account seasonal trends, grouping the customer base into marketing-targeting segments, detecting anomalies in payments, predicting machine or supply-chain maintenance, etc.

The use of advanced analytics is truly visibility all around us: in the news – as we read about smart Messenger service bots, artificial intelligence and digital marketing – but also closer to us as we shop online and see personal product recommendations, receive customized newsletters and listen to recommended playlists.

"Advanced analytics does not need to be as complex as it sounds and does not only suit big organizations.  With the right supporting technology, any analyst can now – without programming – leverage an entire toolbox to analyze big data sets and build models."

- Bart Van Der Vurst, AA & Big Data Architect

There are a lot of new tools available such as cognitive analytics tool within IBM Watson, a machine-learning toolbox using the drag-and-drop tool in Microsoft Azure ML or IBM SPSS Modeler. As element61, we offer our hands-on expertise across technologies and software: our promise is to help an organization find the right solution for the right use-case.

We use software providers such as SAP, IBM and Microsoft to abstract and host the infrastructure technology and to ensure scalability. The key advantage of the latter systems is the ability to first, get started in minutes without the need for any significant investment and second, the ability to add our own tools if needed (e.g., R, python, spark).

  

For many organizations, there is hesitation to get started: there is the bias that it’s new, sounds very complex and must be very expensive. In above paragraphs, we hope we clarified that it doesn’t have to be: it’s accessible for small and medium companies as well, doesn’t require a big investment and will bring added-value.

As such, our belief is that it’s important to go step-by-step and to start with a tangible, measurable but simple use-case (i.e., a proof of concept). This allows the organization to learn and to grasp the output/ROI that advanced analytics can bring. As the organization gains confidence, the organization can proceed in making a choice in technology, applying more complex algorithms, running more use-cases. Along the full learning and implementation cycle, element61 offers to support to design a roadmap, help you get started, co-develop a proof of concept (POCs) and integrate within your existing BI system.

Contact us for more information on our Advanced Analytics offerings.