Enterprise Vs. Departmental CRM Comparing Departmental And Essay

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Enterprise vs. Departmental CRM Comparing Departmental and Enterprise Information Systems

Customer Relationship Management (CRM) Teams in Cincom Systems

It is paradoxical that the majority of enterprise software companies today have highly fragmented Information Systems (IS) departments with one entire series of departments dedicated to enterprise computing and a second, to specific departments or divisions. As enterprise software systems, specifically in the areas of enterprise CRM are organized to ensure a very high level of data fidelity across departments, there is a conflicting set of priorities for ensuring real-time response to prospective customer requests (Power, 2009). Not only are the differences in enterprise-wide information systems significant in terms of the real-time vs. batch-oriented nature of their information needs, they also vary significantly in terms of the analytics used to evaluate their performance (Power, 2009). At Cincom Systems, these conflicts are accentuated by the speed of new product introductions in their five core enterprise divisions vs. The real-time data and information needs of each department in terms of sales leads or opportunities and market information. This conflict is most often seen when Cincom attempts to launch a strategic services initiative meant to span across the entire company, only to find the vast differences in information needs by business unit slow down or nearly stop the progress of these company-wide initiatives. The strategic implications of service initiatives often must be tailored to the specific requirements of each business unit or division to attain the greatest potential benefit to the organization (Saini, Khatri, Thareja, 2012). This is certainly the case with Cincom, who has attempted to create an enterprise-wide cloud computing initiative to interlink enterprise software products in addition to internal CRM systems to ensure a higher level of data, knowledge and process integration. To date the project has only been somewhat successful due to the vast differences in hwo the enterprise vs. departmental CRM systems are designed and implemented. The intent of this analysis is to examine the policy, team and information technology differences between the enterprise and departmental systems throughout Cincom. Recommendations are also provided for resolving the inherent conflicts in these specific system architectures and the underlying business objectives that drive their development and continued investment.

Enterprise CRM Systems and the Strategies Driving Them

The enterprise-wide CRM systems within Cincom are predicated on the overarching strategic policies of creating a unified system of record that can track Lifetime Customer Value (LCV) while also reporting back the gross margin per strategic initiative, a ranking of the most and least successful marketing and selling programs reaching strategic accounts, and a comprehensive review of the lifetime history of the account. The ability to create a strategic services strategy needs to be based on a unified, reliable system of record that provides insights into strategic accounts across all departments or divisions of an enterprise (Saini, Khatri, Thareja, 2012). This is precisely what Cincom is concentrating on, using the enterprise-wide CRM system to analyze which strategic accounts have the potential to become early adopters of public, private and hybrid cloud computing hosting and application services. Cincom has defined cloud computing as a unified service at the platform or architectural stack level across all enterprise software it sells and services. This creates an integrative layer across all applications and systems that each division can literally integrate their applications into within hours at customer sites. This has turned into a highly profitable business model for Cincom has it charges a license fee for each application up and running on its distributed cloud service. From a strategic level this works exceptionally well as it ensures data quality and Master Data Management at the corporate level. One of the core strengths of the cloud computing platform is the ability to provide applications via the Web in real-time, often integrating these applications at the Platform-as-a-Service (PaaS) and Infrastructure-as-a-Service (IaaS) levels of the could platform. The decision on the part of Cincom to create cloud computing and the analytics that report its relative profitability back to the enterprise-wide CRM system has made it possible for the Chief Information officer (CIO) and general managers of divisions to make more effective new product planning decisions related to SaaS applications for example. All of this is tied back tot the policy within Cincom of having a unified system of record that also includes Master Data Management (MDM) functionality to serve each business unit and their information needs (Power, 2009). In actuality this approach to defining the...

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The analytics and metrics are designed to "roll up" to a corporate level and often mask or make difficult to interpret the contributions of individual departments. This is a concern of the five general managers of the Cincom divisions who are required to launch versions of their software on the cloud platform, in addition to on-premise versions that many customers prefer. This decision of cloud participation vs. on-premise varies significantly across each of the five business units as well, signaling that the corporate IS system architecture including CRM and SaaS, PaaS and IaaS is ideal for large-scale strategic account deployment yet lacks focus on smaller customers. The main concern of the five business unit managers is the analytics that are included in the corporate-wide CRM system that is engrained directly into the cloud architecture has analytics that only partially report their success in financial, operational and service dimensions. It is common to find the need for tailoring corporate-wide or enterprise systems to specific strategy difficult as these systems are designed to provide a broader field of view to decision makers (Wang, Feng, 2012). Teams assigned to the enterprise-wide CRM systems that track cloud-computing performance and profitability for all five divisions are also not designed to delve into the deeper aspects of the overall business units. This gap in coverage for cloud-based applications often can lead to the mistaken impression of higher profitability than is really occurring. The rationalization that is often used is that having a single, unified and strategic CRM system can create a greater level of customer loyalty through service customization; yet in reality distributed systems can deliver as effective if not more targeted strategies in this area (Coelho, Henseler, 2012). The policy, team and information technology in Cincom are given the objective of ensuring accuracy, security and reliability of the enterprise-wide CRM system as the single system of record throughout the organization. At Cincom the key insight emerging is that only those cloud-based applications that have the most fundamental features in their segment or market are best tracked with the more strategic analytics and metrics the could platform provides. The more complex, and therefore more profitable a given software application is the more difficult it is for Cincom to track to the division level the factors contribution to its success. This is the most debated aspect of the enterprise systems in the company today, with many considering it ironic given the $100M generated in enterprise software every year from their own applications being untraceable at the enterprise-level. It requires real-time integration to the department and division systems to capture advanced metrics of financial performance and customer loyalty across the five business divisions.
Analysis of Department-Level Information Systems

and Customer Relationship Management (CRM)

The creation of an effective departmental or divisional strategy needs to begin with a series of analytics quantifying performance of each software application within a business unit. The data quality and MDM aspects of the system of record at the departmental level requires more thoroughness in terms of data cleansing and validation as the source of the data is from CRM system reports from the sales team and distributors. The added step of data cleansing and creation of reporting taxonomies also allows each department to create a more effective representation of their business model. The ability to tailor a given series of CRM applications to a specific strategy provides decision makers with insights that are thorough enough to anticipate change in the overall direction of the market while also pinpointing shifts by prospect and customer (Saini, Khatri, Thareja, 2012). This level of insight and intelligence is not possible with the broader reporting platform that encompasses cloud-based applications and services that are being sold. The conflicts between the teams at the corporate vs. department level are predicated on how to configure the systems to ensure customer management stays customer-centric without deviating off track and becoming more focused on internal metrics and requirements. This is the downfall of many CRM systems that tend to move in the direction substantiating their existence instead of serving as a platform for strategic market planning and more effective customer management (Wang, Feng, 2012). The frequency of CRM updates and the depth of insight within the five divisions has also led to the CRM systems experiencing a higher level of adoption compared to their more corporate-wide counterparts, which is a trend that is consistently found in empirical studies (Molan, Park, Dubinsky, Chaiy, 2012).…

Sources Used in Documents:

References

Coelho, P.S., & Henseler, J. (2012). Creating customer loyalty through service customization. European Journal of Marketing, 46(3), 331-356.

Molan, K., Park, J.E., Dubinsky, A.J., & Chaiy, S. (2012). Frequency of CRM implementation activities: A customer-centric view. The Journal of Services Marketing, 26(2), 83-93.

Ranjan, J., & Bhatnagar, V. (2011). Role of knowledge management and analytical CRM in business: Data mining-based framework. The Learning Organization, 18(2), 131-148.

Saini, A.K., Khatri, P., & Thareja, K. (2012). Customer relationship management in service organisations: Prospects, practices and areas of research. International Journal of Management Practice, 5(1), 1.


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