As I work in the field selling BI, the conversation is increasingly centering around data quality. Unfortunately, many fail to recognize this as the starting point for successful BI. The distraction of getting a reporting tool in place to answer business questions can often lead evaluation teams to focus too heavily on the tool with little emphasis on the quality of the data. In reality, many companies are unaware of the extent of their data quality problem, or how much business value clean data can drive.
How data quality drives business value will vary with each business. To organizations that rely on mass mailings, multiple vendors, or are aligning for heavy acquisitions, data quality is really a no brainer. Think of the inconsistencies that span various business information silos. Duplication of customers can sometimes increase mailing costs up to 50%. How about leveraging vendor spend to realize valuable rebates? SOX compliance, anyone? Good quality data will even help to ensure the success of future IT application projects and serve as an enabler for Master Data Management. In the world of business intelligence and data quality (they are really one), what you don’t know will hurt you, but, what you can discover will help you.
So, what to do? In my world, I offer customers a free data quality assessment that will help give a starting point for success. What is it? It’s a rather simple three day exercise. We take a slice of data from our customer (under NDA, of coarse) and filter it through our insight, match, merge, and consolidation process. We even go to the extend of cleaning the data based on standard address directories and out of the box functionality. The possibilities are endless when custom business rules are applied to your data. What the customer gets is a dashboard indicating the amount of duplicates across silos, amount of data errors, corrections made, and unique pattens we discover on the fly that could have business implications. The process from this point is iterative and agile with the contours of your own business needs.
When you consider the value of good data, the ROI is in most cases large and simple. There is not much explaining to do once you are armed with the insight to where your data faults lie. The insight into how you can/should improve business processes is valuable in itself; not to mention the substantial bottom line savings that reducing your mailing costs, getting vendor rebates, or fast tracking M&A integration will bring.
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