Build an ROI-based business case for your big-data project.

Big Data Analytics are increasingly essential to gaining competitive advantage.  But, where do you start?

Intelligently analyzing more data results in better business decisions. Right? I should just dig in and do it. Right? Well, not necessarily. As the volume of structured, unstructured and semi-structured data accelerates, you should start by answering a few business-oriented questions:

  • Where, when and how do I make big data a strategic advantage?
  • Which of my business processes will benefit the most from big data analytics?
  • After you make those strategic business driven data strategy questions, then you ask the technical and project questions:
  • How will I deal with large and rapidly growing data volumes and poor performance?
  • How do I integrate and analyze new data sources, such as unstructured data?
  • What tools do I need to achieve this?
  • How do I get there?
  • How big an effort will it be?

So, you are asking, “How can Big Data technologies, tools and processes transform my organization with game-changing capabilities?”

Your approach to big data analytics should start with business strategy.  Target business processes where a data-centric approach can drive significant improvements.   What data, analytics and KPIs will provide a significant business ROI?  Before you can accurately determine ROI, your first technical step should be to evaluate your data quality and completeness.  You need to know how much work you have to do in terms of data cleaning, ERP systems enhancements and how much new data you are going to have to collect.  For example, you might have to alter your business systems to make sure you are collecting good data on an ongoing basis.  Once you know the amount of work needed, you can build an accurate ROI-based business case.

Once the business case is made, you’ll dive into choosing specific technologies.  There are lots of choices to make, including analytics, business intelligence, data visualization, in-memory technologies, columnar and MPP databases, Hadoop-based systems, data warehouse appliances, big data integration and cloud storage platforms.  Make your choices with sustainability and evolution at the center of your thinking, so that you can continue to benefit from, and expand, your investments, building on them, as opposed to building a one-off.

Evaluating, installing, configuring and implementing cutting-edge in-memory database appliances or real-time data warehousing solutions is exciting.  They promise the advantage of high-capacity, parallel computing performance for your big data endeavor.  But remember, these technology decisions are not made in a vacuum.  They are made with business process and ROI at the forefront.  And, make sure your solution is designed to be flexible, and scalable, in terms of performance with future add-on capacity to avoid unnecessary up-front costs due to over-provisioning.  Keep your eye on the ROI ball.

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