Three Ways to Pursue the Correct Big Data Project

Today’s big data provides more analysis opportunities and puts greater pressure on every company’s business model to produce profits.  Now big data analysis can be applied and used to optimize any and all phases of your company’s business model.

Customer sentiment, website clickstreams, sensor data, geo location data, all operations logs, and any structured or unstructured data can be leveraged for more business insight.  The scale of the data produced, leveraged and available from new web, mobile, social and machine sensors allows new business opportunities to be discovered, profit margins to be increased, and new business insights to be realized.  The following are three ways to determine the next best big data project to enhance your company’s bottom line.

Evaluate new big data discovery opportunities.  

Every company wants to say that they are doing a profitable big data project that is transforming their company, their industry, and the world.  The reality is that most CIOs don’t know what big data to use, where to start, or how to evaluate big data discovery opportunities.

Due to each company’s different business model and existing analytics, the opportunities will be mostly unique for every company.  There are huge numbers of the big data opportunities. Many fall into different areas such as:

  • Tracking customer sentiment allows a company to understand and fix a product manufacturing problem and fix it quickly enough to save the company millions in sales.

  • Web site look/purchase analysis tracking website clicks and paths allows online retailers to improve the purchasing process and upsell a customer on further products, tremendously increasing sales.

  • Sensor maintenance failure analysis of jet engines sensor analysis provides competitive advantage over other manufacture by providing predictable better maintenance schedules to keep the equipment more available and reliable then their competitors.

  • Location related customer marketing near store coupons and in-store geo tracking shows retailers which items customer want as well as many other location marketing opportunities.

  • Logistics or operational log analytics measure company manufacturing timing and quality assurance response time to problems, allowing them to track and improve speed to production and quality, saving companies millions.

  • By leveraging new unstructured data such as emails, video or pictures, companies can measure customer product sentiment using text analysis, count customers as they enter the store with video cameras for inventory projections,  and prevent fraud through customer location analysis, preserving millions in profits.

All of these examples make millions for their companies.  Use them to determine what areas could give you the best big data return on investment and a competitive advantage for your company.

Automate your analytics

All of the existing analytics of the company need to be understood, evaluated and automated, since no company cannot improve anything without measuring it first.  Catalog all existing business analytics measurements being done.  Then look at the measurement gaps to find where new analytics might make a difference.

Look for new opportunities to produce measurement analytics automatically as by-products through business activities and procedures.  It might surprise you to discover the lack of automatic analytics against common business procedures.

Appraise the business value of actions

Business analytics, whether they are simple or complex calculations, can be brought to bear on a business improvement idea. The analytics can help determine the business impact and value.  By using analytics, the best return on investment alternative can be exposed instead of having the HIPPO (highest in-room paid person’s opinion) automatically become the next big data project focus.  The challenge is to convince everyone to rely on the analytics because its role new to the corporate culture.

The big data examples mentioned in the first section of this article are good starting points to develope within your current data management environment.  Sometimes your company’s current internal data isn’t sufficient for the analytical evaluations needed to determine how much big data your big data project needs to be effective and profitable, so you’ll need to develop this corporate knowledge over time

Change your business profit potential, decision making process, and overall profit margins by using big data analytics.  These three techniques can help you expose big data opportunities to improve processes, automate data gathering, and improve company profitability.

Dave Beulke is a system strategist, application architect, and performance expert specializing in Big Data, data warehouses, and high performance internet business solutions. He is an IBM Gold Consultant, Information Champion, and President of DAMA-NCR, former President of International DB2 User Group, and frequent speaker at national and international conferences. His architectures, designs, and performance tuning techniques help organization better leverage their information assets, saving millions in processing costs.

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