Big Data

6 tips for extending business capability of big data projects

Big data projects often have benefits beyond the department where they originate. Here are some tips to help your company maximize a project's reach.

Big data projects focus on technical aspects of system and data integration—but companies get even more value from their big data projects if they have a thorough understanding of all of the systems throughout the company, including the systems that users brought in. Once IT knows how many systems could potentially benefit from a single big data project, it can extend big data business capability to many more functions than were originally thought.

Here's an example:

Your marketing and sales departments track sales leads, but they have no way of identifying which leads are the most likely to turn into customers who buy.

To help with this problem, marketing gets a standalone sales lead scoring system that enables development of a model for a highly qualified sales lead. The system then compares this ideal prospect model to the entire prospect base, scoring and ranking prospects based upon who comes out closest to this model.

The problem: determining who this model prospect is.

Meanwhile, data analysts are busy defining a CRM database that marketing will use to analyze the customer demographics for campaigns. The CRM system was not intended to help with sales lead qualifications, but it could if marketing and IT meet before the project is designed.

Marketing can tell IT about the standalone sales lead scoring system, and together, both departments can determine if there is potential to integrate CRM analytics and information. In the process, other business processes that formerly stood alone could be incorporated.

SEE: IT leader's guide to big data security (Tech Pro Research)

How would this integration work?

By importing an analytically-derived "perfect customer" model from the CRM system that marketing uses in the lead-scoring system.

Processes like this extend business capability because they integrate disparate business functions beyond the original scope of just developing a CRM data repository and analytics.

The irony is that most data analysts (and their managers) miss these opportunities.

One reason is that they are so tightly focused on the immediate goal of a project, that they neglect to look beyond it. A second reason is that IT tends to look at integration as the integration of data and systems, rather than business processes and information value chains within the company itself.

Here are a few ways to improve the integration and extension of business processes and capability with your big data projects:

1. Identify what you want to accomplish in your big data projects

Once you define the primary goals of a big data project, you have a foundation from which you can look for possible business capability leveraging opportunities.

2. Collaborate with other departments to identify ancillary business uses for your project

It is vital to collaborate with business users on this step, because you will often find that there are many island systems and business processes out there that your big data project could give value to, and that you might not even know about.

3. Don't design big data projects until you have identified the ancillary business capability opportunities

The goal is to make the plan, database, and processing large enough to enable expansion into other areas of the business where you feel the project can deliver capability. What you want to avoid is a future risk of having to reinvent or even abandon the system because the design wasn't flexible or large enough.

SEE: Special report: Turning big data into business insights (free PDF) (ZDNet/TechRepublic)

4. Establish ROI goals for ancillary as well as for core business functions

If you and other users see value in adding ancillary business functions to the scope of your big data project, ROI justifications and projections for these ancillary functions should be developed and verified before additional work is undertaken.

5. Deliver the big data project in incremental phases

Just because you deliver more value to more areas of the business, doesn't mean that your big data project is going to get an extended deadline. You can manage expectations by delivering your big data project incrementally. Deliver core functionality first, then incrementally phase in the ancillary areas.

6. Communicate with upper management and the board

If you decide to perform additional pre-project analysis to look for ancillary areas of business capability, take the preliminary step of explaining this new approach to your upper management and the board. Most will be delighted because they will see an opportunity to extend business capability and better integrate business processes. However, some will perceive this as a delay in getting projects done. Your management must be on board before you make a change.

Also see:

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Image: iStock/WDnet

About Mary Shacklett

Mary E. Shacklett is president of Transworld Data, a technology research and market development firm. Prior to founding the company, Mary was Senior Vice President of Marketing and Technology at TCCU, Inc., a financial services firm; Vice President o...

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