Key Decisions Require Vision

17 Sep Key Decisions Require Vision

Next-Generation Business Intelligence through Interactive Visual Analysis

In business, the best information wins. But today’s enterprises are struggling to make use of the volumes and complexity of available data. Next-generation, visual technologies can eliminate the pains associated with reporting and information analysis, helping organizations make the right decisions faster and with more confidence.

The Best Information Wins

Thomas Davenport wrote in his groundbreaking 2005 Harvard Business Review article, Competing on Analytics, how market-leading organizations including Walmart, Dell, Harrahs and Capital One have adopted the use of analytics as a strategic competitive differentiator. In every industry, organizations are realizing that to win in their markets, they need to learn from the data they collect in their enterprise systems in order to create competitive process improvements.

Data has never been more plentiful and available. Transactional applications such as ERP, SCM, CRM, and enterprise project management have matured and now gather large volumes of information about both internal and external business processes.

Unstructured data has also increased in volume from the widespread usage of web sites, email, knowledge management, XML and enterprise data storage systems. All of this data is now consolidated into data warehouses for use in analytical applications.

 

Today’s Business Intelligence Tools were Designed for a Simpler World

Unfortunately, having access to data is not the same as effectively using it. Users with the opportunity to analyze more data are often overwhelmed and frustrated by the amount of effort required to make sense of it all. Most organizations today use tools that were developed when networks and processors were slow, disk space was expensive, and databases were slow to handle complex queries. These applications fail to present information clearly to business users when there are multiple dimensions of data to integrate into a decision.

Data in high-level summaries, such as in simple dashboards, is presented in a rigid fashion and does not provide explanations of “why” results are as they appear. The drill-downs to detail reports and associated search tools generate simple row and column views that have become long (or longer) lists with text or numbers displayed out of context. More often than not, knowledge workers are unable to find answers to their questions through these systems alone. Because business people do not have a way to access and explore their data themselves, they usually end up attempting one of three dysfunctional strategies:

• Dysfunctional Strategy #1:

  Request custom reports for every new issue. Since business users must rely upon analytical programmers to create custom reports, each new reporting request becomes a new project for IT. Organizations are finding that up to 80% of their resources are allocated to custom reporting requests. Lack of IT resources and/or bandwidth limits the number of custom reports that can be created, leaving many key questions unanswered.

• Dysfunctional Strategy #2:

  Work around the IT infrastructure.Using spreadsheets and ad-hoc desktop databases, business users create their own reports by cutting and pasting information from multiple reports and data sources. This manual, repetitive and highly inefficient process transforms expensive knowledge workers into overpaid administrators. The resulting reporting is error prone, easily bottlenecked, not standardized across departments, does not update automatically and is often done redundantly with varying results.

• Dysfunctional Strategy #3:

  Operate without the information. If the information cannot be made available in time for a decision, then business users will work without the information entirely or ignore problems and opportunities that cannot be analyzed. This approach adds strategic and operating risks.

The traditional means of generating reports and dashboards need to be extended to help knowledge users answer the complex questions that affect corporate performance. New solutions are required to keep pace with growing business complexity.

 

Interactive Visual Analysis

“Interactive Visual Analysis” is a game changer in how data is being used in business. Through intuitive and interactive visual interfaces, subject matter experts can become data analysts, applying their experience to quickly understand the meaning and importance of data in making better decisions.
These interactive visual analysis applications—often referred to as visualizations or Active dashboards—are helping to identify opportunities and threats faster, to optimize resource allocation, and to increase the rate of innovation to bring new capabilities to market. Knowledge workers use these interactive metaphors to identify and solve business problems that require sophisticated analysis of multidimensional data. With this technique, organizations reduce reporting costs, make better decisions and increase the overall competitiveness of the company.

How is Interactive Visual Analysis Different?

It is not easy to create a self-service interface in which business users can intuitively explore and understand high volumes of data. Traditionally, business intelligence tools have attempted to accomplish this through end-user dashboards that link static reports and expose development tools. But simple dashboard gauges fail to capture complex business dynamics. At the same time, the number of columns and rows in static reports has grown well beyond end users’ ability to quickly get meaning from the data. And, both dashboards and static reports fail to consider more than a few dimensions of data—thus failing to provide a true representation of today’s more sophisticated business environments.

Applications with an intuitive, visual workspace can represent business information in more meaningful ways. By presenting information as interactive pictures, visualizations can combine data from thousands of static reports into easily digestible formats. Users can select data elements, filters, highlighting, and display options to change data perspectives—from high-level overviews down to the lowest levels of detail. Leveraging the human ability to recognize patterns, Interactive Visual Analysis uses time-based GANTT charts, bubble charts, heat maps and other visual metaphors to aid users in understanding information.

By providing a fluid interaction model to drill down for explanation, zoom out for context, and overlay dimensions as if the data were a map with points of interest from street level to citywide views, Interactive Visual Analysis enables the user to quickly and easily create meaningful data perspectives without calling on IT staff.

 

Data Discovery and Business Alignment

Interactive Visual Analysis is being applied today to solve a number of challenges in business related to data discovery and business alignment. Data discovery has become a significant challenge because business users need to be able to explore multidimensional data environments without programming ability or high-end analytics applications. Reporting systems today are helpful for getting answers to known questions; but, sometimes the question to be asked is unknown.

Interactive Visual Analysis solves the data discovery challenge by allowing novices to find patterns, distributions, correlations and/or anomalies across multiple attributes using visual cues to explore and understand the data. Data elements are highlighted by size and color while multiple filters can be applied by the user to determine which data is presented. Useful metaphors, including heat maps, bubble charts, and clusters, put information into context. In analyzing large data sets, the user can fluidly navigate between high-level summaries to more detailed views to find root causes and to identify the source of patterns. The resulting effect makes it easier to resolve the proverbial challenges of seeing “the forest from the trees” and “finding the needle(s) in a haystack.”

Business alignment challenges arise because teams need to make use of multiple domains of information to optimize productivity between team members. Small slices of information and out of context information make it difficult to align teams, projects, processes, resources and results; therefore, most teams work to pull information and compare it manually—an extremely time-consuming, error-prone effort.

With Interactive Visual Analysis, teams can more easily create status, metrics, and time-based reporting, while automatically being alerted when thresholds are exceeded or deadlines could be missed. With dynamic controls and views, users can test hypotheses and model scenarios based on historical data and planned timelines.

Through functionality for project/portfolio management, risk management, resource allocation, scenario modeling and portfolio optimization, teams can share plans, ideas, thoughts, opinions and views of the current state of business operations.

Users then gain a better understanding of how issues and opportunities identified in their processes will affect other areas of the business. Interactive Visual Analysis helps individuals and groups identify and understand relationships that would be otherwise difficult to see with large volumes of data.

 

Increasing Data Availability Fuels Demand

Reporting/output has in the past often been treated as an afterthought. In implementing enterprise systems, the focus was usually placed on the data or business process being captured. As a result, visualization of the data and the business’s performance became a secondary challenge to be addressed in a later phase.

The shift to more analysis of information has coincided with the consolidation and organization of data outside of business applications. A data warehouse or data mart is a database that consolidates and organizes information from across multiple applications into a data structure optimized for analytical applications. During the past five years, data warehouse adoption has steadily increased. New technologies, including XML integration tools and service-oriented architectures, have helped to drive adoption of warehouse strategies, where size has often grown to beyond two or three terabytes. These structured repositories provide highly available content primed for analysis.

While early database technologies couldn’t handle these high volumes of data, today’s higher-processor power scales to perform effectively against even complex requests such as predictive analysis models and large aggregate queries. The combination of data availability and rapid response times creates a new opportunity to drive efficiency from compiled warehouse data. For IT departments—who need to secure budget for ongoing maintenance and future expansion—new reporting/output capabilities will further extend the value of data warehouse projects.

 

Powered by Web 2.0 Technologies

New technologies often referred to as “Web 2.0” have also become available to power more interactive front-ends to data. Today’s Web environments include rich client experiences based on technologies such as Adobe Flash and AJAX scripting.

Interfaces previously available only on a programmer’s desktop can now be deployed to any user with a Web browser. Faster networks and more powerful desktop PCs increase the amount of data that can be processed on the desktop of the user. XML interfaces allow data to be presented from heterogeneous data sources in a secure fashion. Semantic web technology, like RDF, make information more meaningful to users by integrating ontologies—dictionaries about the meaning of data—to organize how content is presented to create context and save search time. These richer client environments open the door to a more visual approach to data analysis.

The combination of data availability and new technologies is creating an opportunity to change how data is analyzed. Companies that recognize the opportunity sooner will be the first to use it as a strategic differentiator—saving costs developing custom reports, lowering risks from spreadsheet-based reporting, and providing applications to business users that give them the visibility they need to make better decisions.

While the opportunity to improve reporting through Interactive Visual Analysis is driving early adoption of specific applications, it is still a new concept at many organizations. Most deployments to date are custom systems using web application programming tools including .NET, Java, and Flash or extensions of existing business intelligence dashboard projects. These custom projects are proving challenging and will not scale in the long term to meet the needs of large organizations due to gaps in expertise, gaps in capabilities and overall cost.

The Design Gap

Effective design of an interactive reporting environment is not a core skill for IT teams and software developers. Visualization can address a number of business requirements by applying design patterns that are not apparent to a team not experienced with the concepts so having experts who have delivered applications in the past greatly reduces failure rates and increases the total return on investment on projects. Making a useful workspace takes experience in the three disciplines of visual interaction design, business process analysis and reporting software development. The combination of these three skill sets are rarely found in a single individual or even within a functional team. With a limited community of expertise to translate business reporting requirements into a blueprint for a user interface it is important for companies to seek outside expertise.

 

Packaged Technology

The total cost of ownership of custom designed analytics systems is too high for sustainable development and maintenance. Today’s major business intelligence platforms lack the depth of features and architecture to support real-world visual analysis applications because the functionality required goes far beyond the capabilities of the core business intelligence reporting architecture. The solution is to license a product platform that is designed to satisfy the needs for visual analysis and integrate the visual analysis platform with existing data repositories and BI applications to leverage prior investments. The platform should be able to support both data exploration and business alignment and include a library of modular components sufficient to assemble a meaningful business application.

 

Summary

The complexity of business has out-paced today’s decision-making tools. As a result, organizations are struggling to make use of the volumes of information available to them through the myriad enterprise applications and corporate data warehousing initiatives. Knowledge workers spend too much time creating reports manually, and the growing list of custom reporting requests is overwhelming IT staff. Interactive Visual Analysis solutions extend an organization’s reporting and decision-making capabilities. By combining data into elegant, interactive pictures that equate to hundreds of static reports, Interactive Visual Analysis enables users to make more-informed, more-confident decisions faster. Organizations that embrace these new paradigms for data output will create significant competitive advantage in their markets, as users will become more efficient and fewer questions will go unanswered.