Analytics: your core competitive weapon in 2016

Did you also read Forrester’s predictions 2016 for business? Analytics is clearly indicated as core competitive weapon to be successful and win your business. Forrester emphasizes correctly that analytics should be on the top of any CXO’s agenda in 2016. I cannot agree more. So let’s discuss why this is so important?

Big data in 2015 took its momentum we had foreseen already. Those Big data initiatives gave us a broader range of data. A range that brings additional data from two directions:

  • First, we have access to more levels of details. In-memory computing allows for immediate access to archived data which is now available for analytics. In-memory also allows to present the full level of detail to the end users because its capabilities to handle the processing and calculations that come with the huge volumes.

  • The second axe is about the scope of data we have access too. Connected networks, sensor data or social media metrics.

This all seems good news ........... Uh really? ....... Yes it is good news, but it also brought some challenges we haven’t fully under control today. It all assumes we are able to do get value from our new data. It assumes people are capable of analysing the new data and act upon it, bringing them ahead of the competition. The big data is of use if we understand it, have access to it and are able to do valuable things with it. And exactly on this point the difference is made whether analytics is a competitive weapon or just a commodity process. Getting valuable insights from big data is the ultimate key word here. Business analytics is the sole way to do so and that’s what the Forrester report is talking about.

The issue with Big Data

So what issues do people face? The thing is that the amount – both in volume and in scope – increases so intensely, people start facing issues to quickly get valuable outcome. Think from the basis over here: unknown data is coming to us, so we need to understand what the data is about, where it is located and where it comes from before we can start analysing searching for insights. If we have answers to these questions, it should be possible to easily access, explore and interact with the data at reasonable response times. In case necessary, we require additional resources to search for data-correlations and unknown patterns. Depending on the outcome we might want to involve others discussing the new data is of use or needs to be further enriched. This could affect ETL processes for example.

Personally I believe a core base of business analysts is needed to at least document, explore and maintain the core flows of new data: people who can advise business users what structured and unstructured data is available, where it is, how to access it and how it relates to the corporate data that is already available to users.

In order to follow the above flow which is necessary to use Business Analytics with big data, we thus can define a number of pre-requisites. Pre-requisites that need to be fulfilled allow business analytics as your competitive weapon. Here they are:

Prerequisites to utilize big data with Business Analytics

We need in-memory computing for Business Analytics

In order to process, calculate and analyse the extreme level of data, in-memory computing is a must. In this article we already described the business cases for in-memory computing towards business analytics. In-memory computing is the only way that allows to interactively explore the new data, find correlations and create valuable insights.

We need a core base of business analysts

A small team of analysts that acts as gate keeper for new structured and unstructured data informing users where it is and what it is about. The team ensures the new data is compliant to company standards, secure and governed.

We need self-service

Working with new data that is structured or unstructured means the analyst need to be able to interact with it. Explore, filter, exclude, calculate, enrich, correlate and visualize: these activities should be possible on the fly with a decent response time. It means we both need the calculation power as the tool capabilities. The very useful BI Component selection tool helps you deciding what tool is best suited. Tools like SAP Lumira and SAP Cloud for Analytics seem very well positioned to do the trick.

We need Predictive Analytics capabilities

New structured and – definitely – unstructured data is being analysed looking for patterns and correlations that help us better positioning against competitors or finding new ways of serving our customers. Therefor the business analysts working on big data require predictive capabilities in their tools. Even more, they require to use predictive capabilities without having to have the statistical background knowledge. The latest predicative analytics tools are capable of doing so respecting R algorithms. We need a continuous feedback-loop New data means new insights if we can fulfil the above requirements. There is one left: our new insights might need to be incorporated in existing insights and as such we need a constant feedback-loop towards the Business Intelligence Competence Centre (BICC) to do so.


The above mentioned pre-requisites are a must to guarantee that business analytics is the competitive weapon for business in 2016 as predicted. I fully agree with this. The pre-requisites are not complex and can be implemented in any organization. If implemented well, business analytics is your new 2016 currency allowing you to get ahead of others, find new ways to serve your customers or even find new ways of business activities. I am looking forward to 2016: the future is ours !

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