273136_l_srgb_s_glHave you read Forrester’s 2016 predictions for business? Analytics is clearly indicated as a core competitive weapon that you need to be successful and win in your business. Forrester emphasizes correctly that analytics should be on the top of any CXO’s agenda in 2016. I cannot agree more. Let’s discuss why this is so important.

In 2015 Big Data had the momentum that we had foreseen. Big Data initiatives gave us a broader range of data, a range that brought additional data from two directions:

  1. Access to more levels of detail – In-memory computing allows for immediate access to archived data which is available for analytics. In-memory computing also allows you to present the full level of detail to the end users because of its capabilities to handle the processing and calculations that come with the huge volumes.
  2. Access a broad scope of data – This scope might include connected networks, sensor data, or social media metrics.

Does this all seem like good news ….really? Yes it is good news, but it also brings some challenges that aren’t fully under control today. It assumes you are able to get value from your new data. It assumes organizations are capable of analysing the new data and to act upon it, moving them ahead of the competition. Big Data is of use if you have access to it, understand it, and are able to do valuable things with it. It is exactly at this point that the difference is made as to whether analytics is a competitive weapon or just a commodity. Getting valuable insights from Big Data is the ultimate goal. Business analytics is the sole way to achieve this and that’s what the Forrester report is talking about.

The Issue with Big Data

So what issues do organizations face?

The amount of Big Data – both in volume and in scope – increases so intensely, that organizations start facing issues to quickly get value. Unknown data is coming to you, and you need to understand what the data is about, where it is located, and where it is coming from before you can start analysing and searching for insights. If you have answers to these questions, it should be possible to easily access, explore, and interact with the data at reasonable response times. When necessary, you may require additional resources to search for data correlations and unknown patterns. Depending on the outcome, you might want to involve others to discuss if the new data is of use or if it 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 a minimum, 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, you can define a number of pre-requisites. Pre-requisites that need to be fulfilled allow business analytics to be your competitive weapon.:

Prerequisites to Utilize Big Data with Business Analytics

  • 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 I described the business cases for in-memory computing for business analytics. In-memory computing is the only method that allows you to interactively explore the new data, find correlations, and create valuable insights.

  • 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.

  • Self-service

Working with new data, that is structured or unstructured, means the analyst needs 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 you both need the calculation power as the tool capabilities. The very useful BI Component selection tool helps you decide which tool is best. Tools like SAP Lumira and SAP Cloud for Analytics seem very well positioned for this.

  • Predictive analytics

New structured and – definitely – unstructured data is analysed looking for patterns and correlations that help you to better position against your competitors or find new ways to serve your customers. The business analysts working on Big Data require predictive capabilities in their tools. Even more, they need 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.

  • Continuous feedback loop

New data means new insights if you can fulfill the above requirements. Your new insights might need to be incorporated into existing insights. With this you need a constant feedback-loop to your Business Intelligence Competency Centre (BICC).

Analytics Weapons

These pre-requisites are a must to guarantee that business analytics, as predicted is the competitive weapon for business in 2016. 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, and even find new ways to approach business activities.

I am looking forward to 2016 – the future is ours !

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