Imagine a charity whose primary donor application is structured around the charitable giving account. The charity knows it has donors associated with more than one account but it can't merge these duplicates because the system won't let them point a single donor to multiple accounts. The donor system is actually prohibiting them from obtaining a total view of donors.
Now consider the retailer that purchased a query and reporting tool to push business intelligence out of IT and into the business community. It collected requirements for sales analysis, extracted the information from its point of sale systems, put it into a reporting database, created some reports with the new tool, and sales was off and running. It did the same for marketing. However, when finance wanted to see information from the sales reports combined with marketing expenditures, neither system sufficed, and IT had to create another database, starting from scratch, with new extracts from both point of sales and marketing. When sales wanted to start viewing changes daily rather than weekly, IT had to start from scratch again, redoing the extracts and redesigning the sales reporting database. All the reports had to be redone as well. The tool may have improved access to data, but the overall reporting process was costing IT more than ever.
Think about one final example; the bank that spent several million dollars on a new call center application. IT, along with the consulting company that implemented the system, touted various benefits to management. Better customer segmentation, robust analysis and reporting capabilities, and an ability to "know the customer" were among the attention getters. Shortly after rolling out the application, several problems were discovered: the segments identified by the CRM application did not match those in the data warehouse and the call center analysis modules did not utilize household profitability calculated using the marketing data mart. Realizing the benefits touted to management required a second project (with additional funds) to link the call center analysis to the data warehouse.
Does your organization have any of these problems? Many companies that we encounter face at least one; often, they deal with several of these.
Migrating From Chaos -- Adopting an Architected Solution
While the intentions of our example companies were good, all three lacked a strategy and architecture or roadmap for implementing their CRM technology solutions. Whenever a complex undertaking is begun, whether it is a building, an airplane, or a new set of applications to support your CRM initiative, the first step must be to create the high-level plan or architecture for what the ultimate product or environment will be. This architecture acts as a road map or diagram, guiding the developer in understanding how all the parts and components interact and cooperate. It also provides a foundation for communicating with the business areas about the role each CRM application will play and the benefits each should deliver. The Corporate Information Factory is such an architecture, (illustrated in Figure 1). The CIF is a logical architecture whose purpose is to provide a framework for implementing integrated technology, in support of the CRM strategy.
If the organizations in our example had adopted an architecture like the CIF, they could have avoided the misunderstandings about what functionality each system should provide, they could have managed expectations about the number of technology projects necessary to meet stated benefits, and they could have pro-actively identified additional CRM applications required to provide the total customer view required by the business.
Figure 1: The Corporate Information Factory
Let's examine the CIF in the context of the situations above. The CIF consists of three primary types of CRM systems.
Business Operations (pictured on the left side of Figure 1) are the core operational systems (billing systems, product or policy systems, call center and sales force automation systems, front-office systems, etc.) that run the day-to-day business processes in an organization. Information originates in these systems and flows through a data acquisition process into the rest of the CIF where it is used to make strategic and tactical decisions. While they may provide some analysis capabilities, these systems, including the CRM system adopted by the bank, are not robust enough to serve all analysis needs in an organization.
Had the bank adopted the CIF prior to purchasing a CRM application, they would have realized that analysis directly from a CRM application does not provide the enterprise analysis capabilities required to drive customer strategy. They would have understood that implementing this solution without a supporting data warehouse would create yet another silo of information with a single department view. The CIF could have highlighted that another project to link the CRM application to the data warehouse would be required for enterprise level segmentation and profitability. This project could have been factored into both the budget and the expectations of the executives could have been better managed.
Business Intelligence (pictured at the top and right of Figure 1) provides the capabilities required for the strategic analysis and decision-making in the organization. Business intelligence, which encompasses the technology infrastructure and information to manage complex relationships and analytics required for CRM, consists of the data warehouse, data marts, and associated analysis and reporting tools. The retailer's difficulties were due to its decision to build independent reporting systems rather than relying on a data warehouse to provide integration, scalability, flexibility, and reusability.
Again, adopting the CIF prior to implementing the reporting tool could have prevented the problems encountered here. The CIF could be used to illustrate that the appropriate architecture for implementing query and reporting tool requires the data warehouse as well as the tools themselves. It could also be used to understand the impacts of skipping the data warehouse step; impacts that include lack of integration, silos of analysis, and lack of reuse, scalability and flexibility.
Business Management (pictured at the bottom and right of Figure 1) enables organizations to act on the analysis results generated within business intelligence. Business management consists of the Operational Data Store (ODS), its associated Transaction Interfaces, and the oper-marts. Business management systems are subject-oriented, integrated, and current valued, and supply a single point of access for near-real time information across the enterprise. An enterprise customer profiling system is a good example of a CRM business management system.
Our charity's donor application does not belong in the business management area of the CIF. It is an operational system that is designed to facilitate the tracking of charitable giving, not to facilitate a total view of the donor. If the technologists for the charity adopt the CIF and educate themselves about its components, they will understand that the charity requires a donor ODS that is linked to the donor application if it desires a total view of donors.
The systems employed by the charity, retailer, and bank all play important roles in an integrated customer information environment. The issues arise from their use (or misuse). Staying true to an architecture such as the Corporate Information Factory will provide you with the guidelines necessary to build the integrated customer information environment required to drive your CRM strategies.