Chapter 9 Customer Relationship Management and Business Intelligence

CHAPTER 9 CUSTOMER RELATIONSHIP MANAGEMENT AND BUSINESS INTELLIGENCE
1. What is your understanding of CRM?
Customer relationship management (CRM) involves managing all aspects of a customer’s relationship with an organisation to increase customer loyalty and retention as well as an organisation’s profitability. As organisations begin to migrate from the traditional product-focused organisation toward customer-driven organizations, they are recognising their customers as experts, not just revenue generators. Organisations are quickly realizing that without customers they simply would not exist, and it is critical they do everything they can to ensure their customers’ satisfaction. In an age when product differentiation is difficult, CRM is one of the most valuable assets a company can acquire. The sooner a company embraces CRM the better if it will be and the harder it will be for competitors to steal loyal and devoted customers.




2. Compare operational and analytical customer relationship management.
The two primary components of a CRM strategy are operational CRM and analytical CRM. Operational CRM supports traditional transactional processing for day to day front-office operations or systems that deal directly with the customers. Analytical CRM supports back-office operations and strategic analysis and includes all systems that do not deal directly with the customers. The primary difference between operational CRM and analytical CRM is the direct interaction between the organisation and it’s customers. The enterprise CRM includes front office-operational CRM includes: Sales systems, Marketing Systems and Customer service Systems. The back office-analytical CRM includes: Collaborative CRM system, Data warehouse and Data mining.






3. Describe and differentiate the CRM technologies used by marketing departments and sales departments?
The CRM technologies used for marketing departments are:
 List generators compile customer information from a variety of sources and segment the information for different marketing campaigns. Information sources include website visits, website questionnaires, online and off-line surveys, flyers, toll-free numbers, current customer lists and so on. After compiling the customer list, an organisation can use criteria to filter and sort the list for potential customers. Filter and sort criteria can include such things as household income, education level and age. List generators provide the marketing department with a solid understanding of the type of customer it needs to target for marketing campaigns.
 Campaign management systems guide users through marketing campaigns performing such task as campaign definition, planning, scheduling, segmentation and success analysis. These advanced systems can even calculate quantifiable results for return on investment (ROI) for each campaign and track the results in order to analyse and understand how the company can fine-tune future campaigns.
 Cross-selling is selling additional products or services to a customer. Up-selling is increasing the value of the sale. For example, Mc Donald’s performs cross-selling by asking customers if they would like ‘fries with that’. Mc Donald’s performs up-selling by asking customers if they would like to super-size their meals. CRM systems offer marketing department all kinds of information about their customers and their products, which can help them identify cross-selling and up-selling marketing campaigns.
The CRM technologies used for sales departments are:
 Sales management automates each phase of the sales process, helping individual sales representatives co-ordinate and organize all of their accounts. Features include calendars to help plan customer meetings, alarm reminders signaling important tasks, customizable multimedia presentations and document generation. These systems can even provide an analysis of the sales cycle and calculate how each individual sales representative is performing during the sales process.
 Contact management maintains customer contact information and identifies prospective customers for future sales. Contact management systems include such features as maintaining organizational charts, detailed customer notes and supplemental sales information. One of the more successful campaigns driven by the CRM system allowed 3M to deliver direct mail to targeted government agencies and emergency services in response to the US anthrax attacks in 2002. All inquiries to the mail campaign were automatically assigned to a sales representative who followed up with a quote. In little more than a week, the company had received orders for 35000 respirator masks.
 Opportunity management CRM systems target sales opportunities by finding new customers or companies for future sales. Opportunities management systems determine potential customers and competitors and define selling efforts, including budgets, and schedules. Advanced opportunity management systems can even calculate the probability of a sale, which can save sales representatives significant time and money when attempting to find new customers. The primary difference between contact management and opportunity management is that contact management deals with existing customers and opportunity management deals with new customers.



4. How could a sales department use operational CRM technologies?
Sales departments were the first to begin developing CRM systems. Sales departments had two primary reasons to track customer sales information electronically. First, sales representatives were struggling with the overwhelming amount of customer account information they were required to maintain and track. Second, companies were struggling with the issue that much of their vital customer and sales information remained in the heads of their sales representatives. One of the first CRM components built to help address these issues was the sales force automation component. Sales force automation (SFA) is a system that automatically tracks all of the steps in the sales process. SFA products focus on increasing customer satisfaction, building customer relationships and improving product sales by tracking all sales information. Leads and potential customers are the lifeblood of all sales organizations., whether the products they are peddling are computers, clothing or cars. The three primary operational CRM technologies a sales department can implement to increase customer satisfaction are:
 Sales management automates each phase of the sales process, helping individual sales representatives co-ordinate and organize all of their accounts. Features include calendars to help plan customer meetings, alarm reminders signaling important tasks, customizable multimedia presentations and document generation. These systems can even provide an analysis of the sales cycle and calculate how each individual sales representative is performing during the sales process.
 Contact management maintains customer contact information and identifies prospective customers for future sales. Contact management systems include such features as maintaining organizational charts, detailed customer notes and supplemental sales information. One of the more successful campaigns driven by the CRM system allowed 3M to deliver direct mail to targeted government agencies and emergency services in response to the US anthrax attacks in 2002. All inquiries to the mail campaign were automatically assigned to a sales representative who followed up with a quote. In little more than a week, the company had received orders for 35000 respirator masks.
 Opportunity management CRM systems target sales opportunities by finding new customers or companies for future sales. Opportunities management systems determine potential customers and competitors and define selling efforts, including budgets, and schedules. Advanced opportunity management systems can even calculate the probability of a sale, which can save sales representatives significant time and money when attempting to find new customers. The primary difference between contact management and opportunity management is that contact management deals with existing customers and opportunity management deals with new customers.



5. Describe business intelligence and its value to businesses?
Business Intelligence (BI) refers to computer-based techniques used in spotting, digging-out, and analyzing business data, such as sales revenue by products and/or departments or associated costs and incomes.
BI technologies provide historical, current, and predictive views of business operations. Common functions of Business Intelligence technologies are reporting, online analytical processing, analytics, data mining, business performance management, benchmarking, text mining, and predictive analytics.
Business Intelligence often aims to support better business decision-making. Thus a BI system can be called a decision support system (DSS). Though the term business intelligence is often used as a synonym for competitive intelligence, because they both support decision making, BI uses technologies, processes, and applications to analyze mostly internal, structured data and business processes while competitive intelligence, is done by gathering, analyzing and disseminating information with or without support from technology and applications, and focuses on all-source information and data (unstructured or structured), mostly external to, but also internal to a company, to support decision making.
Although there could be many factors that could affect the implementation process of a BI system, research by 'Naveen K. Vodapalli' shows that the following are the critical success factors for business intelligence implementation:
a. Business-driven methodology & project management
b. Clear vision & planning
c. Committed management support & sponsorship
d. Data management & quality
e. Mapping solutions to user requirements
f. Performance considerations of the BI system
g. Robust & expandable framework

www.youtube.com/watch?v=ArOFlLzblHo





6. Explain the problem associated with business intelligence. Describe the solution to this business problem?

Organizations need to have an agreed and documented business intelligence (BI) and
performance management (PM) strategy to enable them to deliver real business value from BI technology investments. The important thing is not the format and presentation of the strategy itself, but rather the collaborative process of building and agreeing a BI and PM strategy that identifies a shared set of goals based on an appraisal of the current situation. Gartner analysts often hear about cases where BI has produced a poor return on investment (ROI) — many of these can be attributed
directly to an organization’s lack of a BI strategy. Many organizations have defined an application architecture for their operational and transactional applications. However, they have not taken the same architectural approach to BI applications. BI applications, and the technology infrastructure that supports them, are often required to provide
capabilities that service multiple user types, provide for a variety of planning and analytic functions and allow information to be acquired from multiple
sources.
Taking a siloed technology or opportunistic/ tactical approach can lead to inconsistent results, inflexible applications and infrastructure, and higher cost of ownership. Most BI deployments view the end user as thedesign point. The goal is to deliver the right information to the right user at the right time. The problem is, most BI deployments require the user to stop operating in their traditional work space and
move to another environment to view information.

Most users are just too busy “putting out fires” to stop and browse through the reports in a data warehouse. Increasingly, BI and PM initiatives will think of the process itself as the design point. Technology options for BI and PM applications are at different stages of maturity. Some emerging technologies, such as interactive visualization and in-memory analytics, have been embraced by hundreds of customers and are ready for mainstream adoption. Others, such as BI integrated search, content analytics and BI via software-as-a-service, have not been widely adopted yet, but warrant closer examination. DM&I initiatives include establishing an enterprise wide data integration and quality improvement program, creating a robust data warehouse infrastructure, and implementing a comprehensive metadata strategy.

Technology advancements in these areas can influence or even completely revise a solution strategy and can make obsolete existing best practices in favor of new practices, and organizations must understand and plan for the impact of these changes. not be construed or used as such. Gartner shall have no liability for errors, omissions or inadequacies in the information contained herein or for interpretations thereof. The opinions expressed herein are subject to change without notice. The BI and performance management space is now dominated by megavendors, and further consolidation is likely as these vendors build out their portfolios.

The megavendors are driving the convergence of the BI platform and CPM suites markets, and are also increasingly moving into other areas of performance management. These areas have distinctly different customer bases and these different customer constituencies will complicate standardization decisions as vendors attempt to sell suites that combine BI and performance management functionality. Users must understand the shifting market dynamics and the capabilities of service providers to support their BI and PM initiatives. Previous research has shown that one of the biggest barriers to the success of BI is a lack of skills surrounding the use of information, tools
and applications that are available as part of its implementation.

Organizations need to develop and organize the program management, development and user skills necessary to turn business intelligence and performance management into a core competency. Using the term “business intelligence and performance management initiative” implies a change from the status quo. Executing change requires the ability of leaders to convince others that the change is justified. Often it is the leaders of ITcentric BI deployments that first envision the use of information to improve the company’s ability to make decisions and improve performance. Unfortunately, IT rarely has the political power to enforce this change. As a result, the key issue of building the business case for BI and PM is paramount to convincing executives to sponsor such a change.
One of the fatal flaws of BI is believing: “If we build it, they will come.” Indeed, lack of adoption is one of the most common and visible signs of failure. The situation often confounds leaders of IT-centric BI teams. They collect the requirements directly from the users and build solutions that exactly match their requirements. Yet the users still don’t come.

Unless they view the reports as strategic, and make reviewing them a part of their workflow, most business workers are too busy “putting out fires” to stop and review reports. Most organizations equate BI with information delivery. However, the real value of BI is strongly linked to achieving business goals and improving business performance. A growing range of analytic applications is emerging that leverage BI technologies to better understand and manage business performance.
Based on this trend, BI capabilities will become more pervasive in operational and workplace applications, as organizations seek to use BI to lead, support decisions, explore, measure, manage and optimize their businesses, and thereby drive business transformation.

Building dashboards for most organizations has been relatively straightforward. This is because the measures in most report-centric BI deployments
can be swiftly turned into a performance metric by providing a target goal and displaying the measure in an easy to consume graphic, such as a dial or traffic light. Performing this task transforms a report into a dashboard. BI and PM initiatives need to go further, linking the measures together with a cause and- effect relationship, enabling a user to perform root-cause analysis. BI projects rarely focus on governance because they usually evolve from departmental and workgroup applications. Contrast this with top-down-driven enterprise resource planning (ERP) application deployments that have strict security controls, and a formal process for application life cycle management which ensures proper development and testing before moving to production. This problem will be exacerbated when BI and PM projects are more widely adopted by a broader user community — inside and outside the company.
http://www.gartner.com/it/content/660400/660408/key_issues_bi_research.pdf










4. What are two possible outcomes a company could get from using data mining?


Data mining is the application of statistical techniques to find patterns and relationships among data and to classify and predict.
 Data mining represents a convergence of disciplines
 Data-mining techniques emerged from statistics and mathematics and from artificial intelligence and machine-learning fields in computer science.
Benefits of BI include:
 Single point of access to information for all users
 BI across organisational departments
 Up-to-the-minute information for everyone
http://en.wikipedia.org/wiki/Business_intelligence