We’re often asked, what makes NexJ Customer Data Management unique from other data management solutions in the market? CDM allows and encourages firms to leave data in the source system that is appropriate for it to operate in. Should there be a specific need to augment, modify, enrich, or correct source data elements, business rules can be employed to provide that capability. No rip-and-replace required. This means that regional efforts can move at their own pace and satisfy their specific needs without complex schedules or onerous overhead.
The flexible nature of the CDM implementation lends itself well to both agile and iterative processes. But how is this different than any other implementation? Why would you choose CDM over, say, a data warehouse or MDM initiative or another compelling data analytics product? Well, in a nutshell, when your organization is powered by CDM, it is getting the best of being able to execute locally but manage globally.
Empowering business units is a both a key step and vital ingredient. Nothing takes the life out of a strategic initiative faster than a formal directive removing regional flexibilities. And no technical initiative fails faster than one that attempts to straddle all requirements in a single deployment: either no requirements are satisfied or many are completely marginalized. But not with CDM.
CDM is designed to share content immediately across many different platforms. Business units can see their results in their portals, embedded into their existing applications, or in reports and analytics projects built directly off the data. No need to define complex data models. No need to transport the data to another host. No need to prepare data. CDM takes care of that. And it tracks the changes made by the source system, by the user that made that change on the date that it occurred.
Compliance requirements vary by region as well, and satisfying these requirements forms a mandatory project for many organizations. So why not invest in a data centralization initiative? Not a data warehouse; that’s too expensive while MDM systems are too slow. Coupling selected applications from NexJ to sustain compliance data through enforced business processes can be an agile and iterative undertaking when CDM is used. You see, data elements can easily be added to the model. No complex reloads. No catch-up loading. No rigorous delivery schedules. And since models are built by combining attributes, many new models can be quickly created just by combining existing components with new data sources or computed attributes. CDM does the heavy lifting for you.
Offsetting the centralization investment for some organizations can make for a nasty ROI calculation. But with CDM, analytics integration is readily available and provisioned through the CDM tool itself. Optimization and automation are the key activities to recover those investments through aligned analytic undertakings. Remember to get pieces you need to satisfy your Data Science models up front; it’s okay if you forget, though, as they can always be added in later. But the more history you have to draw on, the less bumpy the ride, the fewer course corrections your models will require.
Build once and share many times is what CDM is all about. What changes would you make to your methodology? How much labor, resources or time could you save in your implementation? We welcome your thoughts, value your insights and action your feedback: share below!