Essay on "Business Consultant at Trade Show Trying"

Essay 10 pages (3277 words) Sources: 1+

[EXCERPT] . . . .

business consultant at trade show trying to persuade a variety of different businesses to introduce Business Intelligence tools into its business. Identify and describe three arguments you would use to persuade businesses of the general value that Business Intelligence offers to most companies.

Of the many arguments for the use of Business Intelligence (BI) in companies, one of the most critical is the ability to continually seek out the unmet needs that prospects and customers have and seek to find new insights into how they can be effectively met (Jordan, Ellen, 2009). BI applications provide organizations with the ability to parse or interpret terabytes of data and succinctly define and present key insights about prospects' needs, and also what the unmet needs of customers are as well. Capturing these requirements can provide companies with the necessary intelligence to guide new product and service developments over time. In many companies, the use of customer-based BI analysis and insights are also used to drive innovation as well (Wattanasupachoke, 2009). Traditionally innovation has been seen primarily from a product standpoint, yet it is increasingly being used from a pricing (Baker, 2009) and competitive analysis (Qiu, 2008) standpoint as well to guide key strategies and initiatives.

The arguments of being able to better analyze, interpret and gain insights into the unmet needs of customers and prospects can over time revolutionize a company. Strengthening this use of BI is the innovation that often results from its use throughout a company to create more market-driven products and services (Wattanasupachoke, 2009). The use of BI also can significantly improve the results achieved from marketing strategies when insights gained are used for managing pricing and competitive analysis. When all three of these factors are combined companies significantly increase their chances for competing and winning profitable new business and growing as a result. Investments in BI can deliver results very quickly given the data and insights delivered.

2. You are the CIO who has just returned from a trade show on Business Intelligence technologies and are pretty excited about what you saw there. How would you go about assessing how to incorporate Business Intelligence solutions into your specific business environment to achieve a successful result? How would you measure the success of your implementation?

First, I'd look at the existing approaches to analyzing data and see how well defined these processes were including what their contributions were to decision-making. I'd look closely at each of the process areas to find out where there was knowledge or intelligence gaps between what the existing approaches to generating analytics were delivering and what was needed to make better decisions. Based on this gap analysis I'd recommend that an augmented or strengthened BI strategy be put into place. My approach would be to focus on the areas where there was the biggest gap between needed information and the ability of systems or processes in place to deliver than information. Of all the areas of the company I'd focus on, the first would be using BI to better understand customers and how they make decisions. Understanding why certain products, services and promotional offers were widely accepted and others weren't, and the extent to which my company understood this today would be my first priority. Second, I would look at how well manufacturing, services, pricing, sales and operations all understood why our customers made decisions like they did. I'd look for insights into how customers' decision-making influences how our entire company ran. After competing these two top priorities I'd get the entire company on a common set of Key performance Indicators (KPIs) to measure how well we were doing against metrics that tied to customer satisfaction. The entire BI strategy would be used to measure and monitor how well the company understood customer needs first and then how well individual departments aligned to the goal of increasing customer satisfaction over time. All KPIs would be based on measuring the impact of strategies on customers, looking to grow their trust and sales over time.

3. Many Business Intelligence solutions are based on the use of a data warehouse. Please describe the components of a data warehouse both logically and physically (you can use a diagram that you create). Include a description of the process involved in moving data from source systems to the data warehouse (e.g. ETL). Describe how the data is presented to the user for querying and reporting.

A data warehouse is often defined in four major components that include the operational database layer, the data access layer, metadata layer and informational access layer. Each of these layers are synchronized through the use of process definitions and workflows, contributing specific functions to the goals of classifying, categorizing through taxonomies, grouping for analysis and finally using BI applications, interpreting and presenting results. Data warehouses vary in their design and structure yet it is common to find the operational database layer acting as the system of record for data warehouse implementations. Enterprise-wide applications are often included on the operational database layer including finance, accounting, MRP and ERP systems. Using ETL-based technologies and systems, data generated by these enterprise systems are stored in data warehouses. The ETL functions are accomplished using the data access layer, which is used as an integration layer between enterprise-wide, metadata and informational access layers. The metadata layer includes data directories, data dictionaries, user-defined taxonomies and data organization structures. This layer is critical because it categorizes and makes more efficient the queries and requests from BI applications at the informational access layer. This is the layer where the BI applications and tools reside, including interfaces for ETL-based applications used for transporting data from enterprise applications into and out of the data warehouse. The data is presented to the user for querying and reporting through BI applications also on this layer.

4. What is the difference between a relational database design (ERD) and a dimensional database design. Provide a detailed example of a dimensional model.

A relational database is one that organizes data as independent attributes that can be interlinked and combined into data models, depending on the specific needs of a business and its strategies or the information needs of an organization. Typically relational databases organize data by their attributes, and use domains, row, table, and two-dimensional data structures to define their structure. Relational databases are used the majority of the time for processing current data, one record at a time. As a result, relational databases are best used for highly repetitive, structured tasks that have little if any variability associated with them. A dimensional database is one that defines relationships between data elements and attributes using a multi-dimensional view. Dimensional databases often summarize data that is historical and are more subject- or strategy-based in structure than relational databases. Dimensional databases as a result are often used for highly unstructured tasks where associates between data elements and attributes are needed. As dimensional models are specifically designed to take into account significant variation in data patterns and seek out associations between data elements, they are often used for solving more complex strategic challenges companies face. An example of how a dimensional database would be used can be found in how Proctor & Gamble (P&G) works with its top food retailing partners to plan out how each store shelf will be stocked with their products. These are called planagrams and in defining which products will go on which shelf, P&G and their food retailer partners need to take into account gross margins by product, sales levels, which products have promotions on them, and also what the demographics of each store are.

5. Business analytics covers three general categories of data analysis: information and technology support, decision support and intelligent systems, and visualization. Identify and discuss two examples from each category.

The growing popularity of business analytics can be attributed to the growth of applications in information and technology support, decision support and intelligent systems and visualization. The first example of business analytics being involved in information and technology support include measuring customer service calls by product and use area to gain insights into how specific uses of products lead to support needs. The second example of the use of business analytics for information and technology support is in determining what the dominant needs are of customers and creating automated self-service systems that have the data they need included within it. Using business analytics to determine customer's services needs and the devising self-service strategies is a common cost reduction strategy many companies use. Two applications of business analytics in decision support and intelligent systems include defining the optimal production sequence for a given product in a specific manufacturing center, and defining which manufacturing centers are the most effective in terms of meeting production schedules for a given range of products. Each of these applications requires optimization of constraints for the manufacturing centers being analyzed. Business analytics is often used specifically for this purpose. Visualization is a rapidly growing area of business analytics as well,… READ MORE

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