Big Data: 4 Business Areas to Examine for Your Big Data Projects

When developing any new IT initiative, estimating a good return on investment is paramount for getting upper management support and funding.  With all the buzz about Big Data hitting every magazine and financial TV show, the budget process may be a little easier, but not by much.  The best way to get your project funding is to have a focused mission statement that details your big data initiative.

Working with companies, attending the conferences, and reading technology web sites I’ve found that there are four key business areas that are having successful Big Data experiences.  Examine and evaluate these areas in your company for their potential return on investment (ROI) to determine the one with the biggest potential ROI. Then management might fund your Big Data project efforts.

1. Enhancing customer relationships through the mining of web searches, click streams, social comments on Facebook or Twitter are all very popular.  Understanding the customer sentiment, finding product problems early or providing improved or new services has been done through many Big Data projects. Finding the profitable customers, servicing them better, or getting rid of costly customers has been a goal of business intelligence, data warehousing for years. Now it’s Big Data’s turn to tackle these efforts.  Big Data analytics is another great way to determine how to do things faster, cheaper, and better for your customers.  In this new age of commerce your company is not selling to a demographic, region, or age group; it needs to sell to individuals. Some Big Data projects help companies understand each of their individual potential customers better.
2. Sales are always under the microscope and Big Data analysis can provide product, demographic, and customer insights.  Researching sales is already most likely happening in your company.  Taking it to the next level by looking at many more years of sales, sales related to products, new categories and trending sales over new types of detailed comparisons are always valuable.   Find out what sales analytics are used to score salesperson bonuses to help the sales team achieve more wins is a solid proposition because the sales people are usually very good at getting your Big Data ideas discussed and sold to upper management for funding.
3. Fraud management and detection are vital for every business.  In the tight economy 2% improvement in fraud management can mean millions or sometimes billions of dollars of savings that immediately improves the bottom line profits.  Using Big Data to analyze orders, customers, or purchasing attributes and merging that information with other forms of social or customer Big Data can sometimes reduce fraud dramatically.  Fraud departments are doing a lot of analysis, sometimes with a lack of technology. Supporting them with a Big Data initiative is usually well received by upper management because of the improved profit potential.  Being able to significantly speed up a fraud department’s existing workload instantaneously or enable interactive applications with OLTP or web transactions can uncover and prevent more fraudulent transaction and save even more money.
4. Operating costs and product distribution management can be improved through Big Data analytics.  These operation or distribution product costs can add millions of overhead to the business. Reviewing, optimizing, and improving them by only 1% through work force efficiencies, supply chain management improvements, or production costs improvements can mean millions added to the bottom line company profits.  Big Data analytics on supply chain partnerships and product defects are other areas where operational efficiencies and huge time savings can save big amounts money for the company.

Analyze your company in these four areas and pick a few to estimate their ROI for your possible Big Data project.  Go out to all the Big Data vendors and look through and use their customer testimonials as examples on how they have succeeded with their Big Data project.  IBM has many examples on its Big Insights and IBM DB2 Data Analytics (IDAA) on z/OS as do the other vendors.   Estimate what to do and how much it will improve the company’s bottom line and the Big Data money will come to your budget quickly.

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Dave Beulke is an internationally recognized DB2 consultant, DB2 trainer and education instructor.  Dave helps his clients improve their strategic direction, dramatically improve DB2 performance and reduce their CPU demand saving millions in their systems, databases and application areas within their mainframe, UNIX and Windows environments.