National Financial Partners (NFP) faced a significant challenge in monitoring and analyzing policy processing response rates for over 1,000 open cases. They needed to measure and report the performance of its insurance carriers to improve operational efficiencies and increase customer satisfaction. The Accounting Department was tasked with processing thousands of commission payments to its brokers. Its primary focus was to identify anomalies based on expected values and historical data. NFP was seeking an effective front-end application for data analysis and reporting. Compatibility with Microsoft SQL Server and Excel was critical. PowerPoint integration was also required due to the number of presentations that are given to company executives and to its insurance carriers. The primary evaluation criteria for the application were: (1) it had to be visual and easy to learn, (2) it had to be deployable without servers, IT consultants, and a long implementation cycle, and (3) it had to snap into the existing IT infrastructure.

US Auto Parts, a leading Internet retailer of aftermarket auto parts, was facing challenges in analyzing their sales across the various dimensions of their business. The process was tedious and sometimes overwhelming. They relied heavily on their IT department to build reports—a process that was neither flexible nor fast. They needed a reporting and analysis tool that could be managed by the analytics team, with limited IT involvement. The tool also needed to empower business units to do their own analysis.

Silvaris, a leading wholesale provider of industrial wood products and surplus building materials in North America, needed a real-time view into its data without having to move the data into a separate reporting format. The company works with rapidly fluctuating prices and large volumes of materials, making it crucial to have a system that can handle these variables. Silvaris had developed a proprietary online trading platform to manage transactions and share data with customers and partners in real time. However, the company needed a more efficient way to visualize and analyze this data.

FiberTower, one of the largest alternative backhaul providers in the United States, was facing challenges in analyzing market data to ensure successful offers to the large cell phone companies it serves. The traditional method of data analysis was time-consuming and inefficient, often taking weeks to generate well-scrubbed maps and recommendations for decision-making. The company was also dealing with large and occasionally impure data sets, making it difficult to visualize and understand the information being considered for decision-making. Furthermore, the company was looking to extend its markets to areas that were traditionally unattractive, requiring a nationwide analysis of potential opportunities.

DePauw University in Indiana underwent a massive administration system upgrade. The school needed to extract student metrics, enrollment, peer groups, and financials from their Oracle database and visualize it in a way that would aid in strategic planning. The data also needed to be accessible to people who don't work with it regularly. Another challenge was the production of a large strategic indicator report that took weeks to compile, bringing together disparate reports from various departments and divisions.

The online retailer experienced a significant jump in revenue growth, which doubled. However, the cause of this increase was unknown, leading to concerns. The company had to analyze various factors, including the events in a typical conversion funnel, to understand the reason behind the revenue spike. The traditional conversion funnel elements were not applicable in 2008, and it was discovered that revenue was growing because people were buying higher-priced items. The company then sought to determine the root cause of this increased revenue per unit.

Camelot Strategic Marketing and Media, one of the largest privately-owned strategic marketing and media services companies in the U.S., was looking for ways to differentiate their services. They wanted to present data in meaningful ways to show clients how they’re “moving the needle” and driving business. The company was facing the challenge of growing data in the industry. Their biggest challenge was taking performance data from one system of record and tying it back against cost data. They needed to bring this data to life and optimize the media on a daily basis, and then review that in a rolled up manner very efficiently with the client.

Kaleida Health, the largest health care provider in Western New York, was struggling with traditional reporting tools that were inadequate for handling its large data sets. The company needed a BI tool that could process large amounts of data quickly and efficiently. The existing Oracle Reporting system was found to be clunky and unfriendly, making it difficult for non-technical staff to interpret reports. The result was that important data often went unnoticed. The company wanted a solution that could provide users with reports they could understand and interact with.

The Market Research Department of Amica Insurance was tasked with collecting and analyzing marketing and sales data, particularly in relation to the company's advertising and direct mail campaign calls. The department needed to sift through tens of thousands of call records to identify actionable information for senior management. The challenge was to find an application that would enable marketing analysts to identify important trends, relationships, and outliers in the data. The application needed to be compatible with existing tools such as Excel, Access, PowerPoint, and SPSS. The primary evaluation criteria for the new tool were powerful visual analysis features, ease of use, and quick deployment without the need for servers or IT support.

The Financial Services Administration Department of the Region 4 Education Service Center recognized a need to develop meaningful ways to analyze and visualize state-mandated information submitted by its member districts. The information is contained in ASCII text files that are difficult to use or analyze. Region 4 developed a process to bring multiple years of this data into one cohesive database. However, the significant amount of time needed to build these capabilities into their products was extending their time to market, affecting not only their internal resources and productivity but their customer satisfaction rates as well. The missing piece in this process was the ability to interact with the data in a meaningful way. Region 4 needed a tool for analysis and reporting that was visual, easy to learn and use by school administrators, didn’t require servers or IT support, and was affordable.

Omega wanted to provide data visualization and analysis capabilities to its clients using data from Omega Legal’s finance and time tracking system. Omega sought an analytical software capability that could give its clients a more in-depth and interactive way to analyze their data than ever before possible, enabling users to quickly identify trends, make comparisons and focus on exceptions that may be affecting their firm’s overall performance. But they also wanted to deploy the solution in a fraction of the time typically required to build such capabilities from scratch.

Pearson, a leading education company, was facing challenges in monitoring and measuring their training metrics. The Human Resources department was responsible for keeping track of corporate training programs, which included training over 30,000 people via e-learning on critical subjects like plant safety and data security. The existing system of using Access and Excel for reporting was time-consuming and inefficient, taking up to 30% of Martin Keiser's time. The format also made it difficult to identify trends and outliers.

Eteamz, a publishing platform for sports teams and leagues, was struggling with understanding conversion rates on their site. They had a wealth of data, but making sense of it was a challenge. They needed a way to consolidate all their data in one place and create multi-dimensional charts. The process of doing this in Excel was time-consuming and inefficient. They wanted to understand the relationship between their free and paid memberships and identify which funnel was generating the most conversions. They also wanted to track and respond to any decline in conversions quickly.

The Analytics Group at Rosenblatt Securities is responsible for collecting, analyzing, and interpreting customer trading data. They needed to quickly examine hundreds of thousands of trades, compare those trades to multiple client-specified benchmarks and proprietary measures, highlight outliers and areas for continuous improvement, and prepare a summary for download into intuitive, graphical reports for its clients. The key challenge was to find an application that enabled iterative, visual analysis of thousands of data fields. The group searched for an effective front-end application to perform data analysis and reporting. Compatibility with existing tools such as Microsoft Excel and MySQL was critical.

ThoughtStorm, an investment portfolio company, was struggling with evaluating large amounts of data to come up with business strategies. They had a team of SQL programmers, analysts, and statistical experts, but the process was slow and inefficient. The analysts often didn't understand the strategic and management considerations of the financial experts, and the financial experts didn't have time to run complex statistical software. This was causing ThoughtStorm to lose time and ground, which was unacceptable to the company's co-founder and managing director, Mike Princi.

Stanford University's Computer Graphics laboratory was facing a significant challenge when they received a complaint about a rogue FTP server running within the stanford.edu domain. The machine had produced very high traffic volumes to off-campus locations, and the laboratory manager was asked to investigate. The data used in the analysis consisted of Cisco NetFlow records from a Stanford router. Network flows are highly granular; flow endpoints include a time-stamped summary of source, destination, protocol, and number of packets and bytes. Each source or destination consists of an IP address and a port. The primary challenge was to find and implement an analysis application that supported this type of investigation. The application needed to support Microsoft SQL Server, be able to quickly sift through millions of records of data, and be able to manipulate and display many dimensions of the data simultaneously.

Oco, a provider of business intelligence solutions, wanted to enhance its service by offering sophisticated data visualization capabilities. The company needed a solution that could integrate with its existing data warehouse and provide powerful, easy-to-use reporting and analytics for its clients. Oco's clients span various industries, including retail, consumer packaged goods, and industrial manufacturing, and the company wanted to provide a tool that could present data in many different formats to cater to these diverse needs.

Cornell University needed a reporting tool that would allow its college deans to better track Key Performance Indicators (KPIs). The university receives tens of thousands of applications every year and needed a way to access this information quickly and easily. The university also wanted to meet the needs of both highly sophisticated technical workers and hundreds of other employees who rely on the software everyday to answer important questions but whose jobs don’t revolve around data management.

The Operations Department at First American Corporation was responsible for collecting, shaping, and analyzing sales performance data across all segments, products, and geographies. They were using Excel pivot tables, but they were slow, inflexible, and difficult for people to learn. Also, the graphics being generated from Excel didn’t effectively communicate the critical insights to executive management. The primary challenge was to find and implement an analysis application that supported First American’s wide-ranging requirements. The Operations Department was charged with reporting monthly sales performance trends to senior managers categorized by channel, market segment, and product mix, analyzing price points by product then recommending pricing strategies that would positively impact revenue and simplify current customer pricing plans, and investigating dozens of sources of marketing, customer, and financial data to drive strategic initiatives and uncover trends and themes previously not known.

Flyer Enterprises, a student-run business program at the University of Dayton, was struggling with its traditional methods of analyzing data. The organization was manually entering numbers from flat files generated in internal operating systems, which was not only time-consuming but also prone to errors. The high turnover rates typical for a student-run business meant that the organization couldn’t devote adequate time toward training employees on its complicated analytical processes. Even after consolidating its data into a Data Warehousing environment, Flyer Enterprises was still lacking a method of viewing and analyzing its business information.

Jacksonville State University's Office of Institutional Research and Assessment, a team of four, was tasked with collecting and analyzing organizational data to optimize operations across nearly 100 academic and non-academic departments. The team struggled with making credit hour productivity visible to departments and administrators, which involved identifying trends in student preference in the academic schedule. The goal was to create optimal course calendars from term to term based on a solid understanding of the data. However, the use of spreadsheets for this task proved to be inefficient and time-consuming, preventing the team from producing meaningful results in time for optimal decision-making. The team was unable to easily identify trends, such as the popularity of 8am classes over the same course at 3pm, leading to missed opportunities to adjust the schedule to meet the needs of the diverse student body.

The Ingenuity Media Group, a part of The Martin Agency, heavily relies on measurement capabilities to gauge how external audiences perceive their clients’ online advertising and interactive media, the overall success of campaigns and, most importantly, quickly identify and correct any issues with a campaign. Speed, accuracy and flexibility are vital to the creation of useful reports, and how they are presented helps showcase the Ingenuity Media Group’s work by quickly identifying which brands and campaigns are effective or, alternately, what changes need to be made to increase their effectiveness. However, producing these analyses with Ingenuity Media Group’s traditional processes was an extremely time-consuming task. Analysts were forced to spend hours processing data and converting it into visual form, creating an Excel document, converting to PDF before finally sending the information to the client. Preparing weekly, bi-weekly or monthly reports took hours.

First Choice Power, a Texas-based electric company, was struggling with the challenge of pulling together a centralized data warehouse from multiple large transaction-based data systems. The company was looking for a reporting software package that could sit on top of this data warehouse and provide meaningful insights to the executive team. The transactional-based data systems where they housed all their data were not designed for reporting, making it difficult to produce meaningful reports for the executive team. The company was also looking for a solution that could help them understand customer behavior patterns and make strategic business decisions.

Before the implementation of Tableau, OptumHealth was struggling with managing and making sense of data from various sources. The company had different silos of reporting teams, data sources, and separate spreadsheets. This made it difficult to get a holistic view of operations and address customer issues promptly. The company was also facing challenges in tracking its various distribution partners and independent brokers. The spreadsheets used for this purpose were unmanageable and not very useful, providing little value to the sales team.

The Epidemiology Department at the Louisiana State University Health Sciences Center- School of Public Health collaborates with hospitals and other providers around the state to meet the requirements of a grant from the Centers for Disease Control and Prevention. The grant funds the school’s Louisiana Breast and Cervical Health Program (LBCHP) to fulfill its mission to ensure that uninsured and underinsured Louisiana women have access to and receive high-quality screening and diagnostic services for the early detection of cancer. The challenge was to identify outliers for quality control and to improve program performance.

The Danish Olympic Committee was struggling with data accessibility and analysis. They had a lot of reporting and 'gatekeepers', but the data was not easily accessible to athletic consultants. These consultants work with about 61 different federations for various sports, and the federations needed to work with the committee. The committee had 26 Tableau Desktop users, but they were facing problems with spreading their data. They were also working on cube data, which presented its own set of challenges. The committee started with a small group of around eight people working on and testing Tableau, and now it's being used by many federations. They have 70 staff members, so 26 is actually a lot. The main goal from the beginning has been to sustain the work between the consultants and the federations.

The University of California, Irvine Medical Center was struggling with the challenge of understanding and presenting their vast amounts of data to the community. They had spreadsheets, Access databases, and were on the path to a data warehouse, but they lacked a tool that could effectively visualize this data. They needed a solution that could work within their current environment and also in the future. The IT department did not want to be the report writers and wanted a self-service model where the people who knew the data could develop their own visualizations and reports.

Norbridge, a management consulting firm, competes against larger firms for the same client opportunities. They rely on fact-based analysis and deep domain expertise to set them apart. However, while their analysts are comfortable with raw pivot table output from Microsoft Excel, most of their clients are not. Their projects often require weeks or even months of data collection, cleaning, and analysis, interspersed with client workshops for joint evaluation and interpretation of the findings. They were looking for a way to respond to analytical opportunities that could rapidly and convincingly connect clients to the key insights in their data. The primary criteria in evaluating analysis applications were: it had to run efficiently on stand-alone laptops, it had to be intuitive so that new analysts could learn the basics quickly, and it had to effectively output visual images to Microsoft PowerPoint.

Irish Life, a market leader in Ireland for life, pension, and investment plans, was facing the challenge of managing its business amidst a worldwide economic recession. The company needed a way to gain fast insight into the business to help business owners understand patterns and trends. They needed a solution that could provide visualizations and trend lines across finance, HR, sales, and customer service. The company was also looking for a way to distribute information to regional sales managers and across the company.

Predicta, an online marketing intelligence services company, was facing a challenge with its product development and customer service. The company's developers were spending a significant amount of time creating filters, drill-downs, graphs, and other capabilities into the company’s product interfaces. This was diverting a large share of developmental resources from creating new features. Additionally, Predicta’s current analytical capabilities required technical knowledge, causing customer questions to be directed to IT instead of the analysts, further impacting IT’s productivity. Predicta recognized that it needed to improve reporting capabilities to enhance the customer experience and make the best use of resources.