Like other corporate assets, customer data has measurable value that is integral to achieving strategic objectives. Likewise, the value of data can increase or decrease depending on how effectively you manage this asset over time. Last week we examined how data quality affects marketing initiatives. Today we look at operational efficiency and in Part III we will examine compliance and risk management.
4. Point-of-Entry Correction. A recent Gartner study estimated that poor data quality cost organizations an average of $8.2 million a year. At that price tag, companies are taking steps to help ensure that “bad data” does not even reach their database. Real-time address validation tools are being integrated at any point where customer data may be entered into the system, including customer service, order processing and Web self-service apps.
5. Data Quality-Data Integration-Data Governance. Analysts from The Data Warehouse Institute have recently identified how organizations can create more value by unifying their data profiling, data integration and data quality initiatives. While the concept seems obvious, in practice these functions have traditionally reported into different teams. In 2010, look for organizations to overcome the lack of coordination and redundant effort by leveraging new tools to synchronize deliverables across all aspects of data management.
6. Routing and Fleet Management. The increase in online purchasing has created challenges for manufacturers, retailers and shippers who must identify more cost-effective ways to plan distribution networks and manage their fleets. Fortunately, today’s leading data quality solutions provide for the geocoding and spatial analysis necessary to calculate routes, determine points within a boundary and move goods from one point to another at the lowest possible cost.
7. System Optimization. After investing millions in sophisticated CRM and ERP platforms, including Oracle® e-Business Suite, Salesforce.com®, SAP® and Siebel®, over two-thirds of all companies have issues with non-standard data and incomplete information. Rather than re-invent the wheel, more organizations are increasing the returns on past IT investments by using out-of-the-box “connectors” that extract data, analyze information and provide users the visibility necessary to effectively run their business.
Clearly, the challenges associated with corporate data can overwhelm even the most sophisticated organization as each new system and customer initiative adds new levels of complexity. Solutions like our SpectrumTM Technology Platform complement your existing business platforms, making it easier to improve the quality, accessibility and value of your data assets. Obviously, there are many other ways data quality impacts customer service… how is your company using data more effectively?
0 Response to “10 ways to maximize value of customer data – Part II”