Customer Data Integration – Separating the Hype from the Reality

Insurance Analytics Boot Camp: Cut Through the Buzzwords and Learn How Analytics can Maximize Your Insurance Data Assets
April 25, 2011
Master Data Management (MDM) – Going Where the Enterprise Data Warehouse has Gone Before
May 4, 2011
Show all

Customer Data Integration – Separating the Hype from the Reality

There is a lot of buzz in the industry about the emerging class of customer data integration software that businesses are using to gain a single view of their customer.

But let’s separate the hype from the reality.

Certainly, implementing a successful customer data-integration solution is critical to business.  But what is necessary to accomplish that? There are three aspects to implementing a customer data integration solution: people, process and product.

Dog_people_process_product Let’s start with product since that’s where a lot of the buzz is. The most important product is a data-integration platform. Generally, enterprises buy discrete data-integration products, such as ETL and data quality (DQ) tools, on a tactical basis.

That’s fine, but customer data integration requires a more holistic approach to data integration that I’ll label as Enterprise Data Integration (EDI). This approach looks to leverage and reuse existing data-integration technologies while expanding these capabilities as needed.

For instance, a company using ETL and DQ may add EII and web services to provide a real-time capability.  The cautionary flag with customer data integration solutions is that they often bundle data-integration software with their offering. In fact, much of the value of the solution derives from the data integration components.

Two questions to ask: Do the bundled data-integration products overlap with products you already have (aren’t we trying to standardize?) and, more importantly, haven’t you already started working on customer data integration in your data warehouse (DW) or operational data store (ODS)?

Maybe you should renovate and revitalize what you have been doing rather than starting from scratch by buying a new stand-alone customer data integration solution. In addition, most enterprises fail to appreciate how much effort will be needed to customize the customer data integration solution they purchased, and how much time will be necessary to re-engineer exiting data-integration processes. Rather than buying yet another data and application stovepipe, critically examine whether you have implemented an enterprise data-integration platform. If  not, determine what components you need to establish an infrastructure that can be used by your customer data integration processes and all your other data integration efforts.

People and process are critical success factors for any customer data integration initiative regardless of the software that you might purchase. You need an Enterprise Data Management (EDM) initiative if you are truly going to create and maintain a single view of your customers. From the business perspective, data governance has to be implemented to establish business ownership and custodianship of the customer data. Without it, IT will be chasing windmills like Don Quixote. From an IT perspective, a data integration center of excellence (COE) or competency center (CC) needs to be created to leverage existing expertise and continue to expand you data integration platform.

Customer data integration will provide great business value and has been the holy grail of many an enterprise. It may be closer than many think IF they expand what they have AND bring in people and processes into the solution. As tempting as an off-the-shelf product offering may be, the reality is you still have to implement enterprise data integration (EDI) and enterprise data management (EDM) if you want to establish a long-term, sustainable customer data integration solution.

 

4 Comments

  1. C-Chad says:

    Who’s dogs are those? 🙂

  2. lest I forget my manners… I’ve been folloowing your writings since the days of DM Magazine, which at one point I thought stood for Data Mining. So, nice dogs (in picture) and kudos for success in training consulting.

  3. rick sherman says:

    Thanks.
    My dog is on the left, his sister from the same liter is in the middle and another family dog, although no dog relation to the other two, is on the right.
    All Portuguese Water Dogs.

  4. rick sherman says:

    …and thank you for reading my articles, posts. etc.

Leave a Reply to Chandler Caulkins Cancel reply

Your email address will not be published. Required fields are marked *