There's a disconnect between the emphasis companies place on real-time metrics and the amount of time IT organizations spend developing policies and procedures for managing the data that comprises those metrics. Everyone wants to turn raw stats into wisdom in real time, but you can't even begin to do that if you don't have a handle on your data. And, complicating things further, cloud providers rarely provide customers with the tools necessary to manage their data stored off site--meaning it's being copied, moved around, and inevitably pushed out of sync.
Consider a manufacturer of steel widgets that sells to the public as well as in bulk to major suppliers. A customer orders online and gets a quote, but when the product is received, the cost is higher than expected because the price of the item on the customer front end was less than the actual cost on the back-end billing system. Hopefully, with good customer service, the problem will get resolved, and the customer will return for future purchases--and not tweet derogatory remarks about the experience.
The problem could have been avoided altogether, however, with a master data record for widget prices that's referenced by both the front- and back-end systems. In response, an entire industry has emerged to offer IT organizations ways to ensure they can offer the business authoritative data sources. But this isn't a problem that can be solved with technology, and, sadly, the discipline of master data management (MDM) hasn't gotten the attention it deserves in many enterprises. For example, in our most recent InformationWeek Analytics Business Intelligence and Information Management Survey, MDM systems came in seventh out of 10 information management technologies (see chart, below). MDM is in extensive use by just 11% of survey respondents.
We think it's time to change that.
For years, we've talked about the value of having a "single version of the truth," but the concept of master data involves a bunch of different elements, including how information is created, read, updated, deleted, and searched.
What's keeping many companies we work with from taking advantage of their master data? A methodology to manage it. A master data set with errors can wreak havoc, especially if multiple applications depend on it. Beyond outright errors, such as incorrect pricing, overlapping data sets from acquisitions can lead to subtle inconsistencies, like one customer having multiple entries in the CRM system.
The solution, MDM, isn't available in a nice little application you can buy, install, and forget. Rather, it's a cohesive collection of technologies and processes that combine to create and maintain consistent and accurate data throughout your entire company, including data that resides off site.
You can spend a small fortune on data warehouses and connectors to enterprise systems, and the technology piece is important. However, without the business processes to maintain consistent data, undertaking an MDM project is pointless. Processes critical to MDM include data collection, normalization, transformation, governance, and consolidation. MDM may be applied to customer data integration (CDI) and product information management (PIM). CDI is about the management of customer information for internal use. PIM is related to managing product data from a central location for internal, and potentially external, consumption.
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- The top 10 areas to focus on when buying MDM software
- Four best practices to get high-quality data--no matter how you define "quality"