BUSINESS INTELLIGENCE SUPPORT

Multiple data sources and technologies make it hard for state and local governments to get the complete information required for better decisions leading to more efficient operations. Similarly, the continued transparency demand of constituents requires integrated management information that support clear performance metrics provided within easy-to-use dashboards.

IIS helps federal and commercial clients transform vast, disparate data into a single view of information. We combine deep federal and commercial expertise, business intelligence (BI) know-how and market-leading solutions to deliver built-for-government data metrics, reports, visualizations, dashboards, and scorecards, with mobile access.

We also help clients consolidate data from all sources – databases, data warehouses, legacy and modern systems – to provide actionable insights through state-of-the-art reporting and analytics.

IIS leverages industry-leading BI tools and best practices to integrate data from disparate sources into a unified information system that supports departmental and enterprise needs. With business intelligence and analysis tools drawing from all databases, legacy systems and new applications across the enterprise, governments increase transparency, productivity and performance measurement while also reducing operating costs.

Business Case for Business Intelligence

One of the largest hurdles an enterprise faces is ensuring operational performance and direction meet strategic vision to efficiently and accurately measure and analyze corporate performance at the strategic and tactical levels. A successful enterprise tends to collect large amounts of data during the course of daily operations. Often, this data is even captured for later use in a data store. However, the frequent lack of definition of proper performance metrics and deficient reporting and analysis capabilities result in difficult translation of data into usable and actionable information.

Organizations struggle with securing, from daily operations, the key metrics that provide predictive capabilities to the management team. The underlying premise of Business Intelligence (BI) is that organizations should expand the types of information used to monitor their business operation while more narrowly focusing on a limited subset of that information to direct management focus. Investments in financial reporting systems have led to an overemphasis of monitoring that financial information as a predictive indicator. Generally, financial systems are the system of record for historical financial transactions. Only when this information is combined with measures of ongoing business operations can it be used to predict future business results.

The challenges in identifying the information required to efficiently and effectively manage an organization can be minimized through the use of methods and frameworks that can accelerate the process and provide focused guidance. Organizations must identify the applicable measures for their business and define an organizational framework for how the measures are represented across the enterprise.

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IIS’ provides a holistic approach to Business Intelligence to address the issues of information that is obscured, widely distributed and inaccessible to an enterprise’s end users. To maintain consistency with the overarching strategic objectives of the enterprise, corporate key performance indicators and the resulting information requirements drive the supporting Business Intelligence initiatives.

The initial component in ensuring strategic alignment for the Business Intelligence initiatives is the establishment of key performance indicators (KPIs) that need to be measured on a corporate or functional basis. Each of these metrics measures some aspect of operational or strategic performance of the organization.

To ensure alignment with key business objectives, KPI identification is founded on a top-down approach that begins with the organizational objectives, identifying the relevant initiatives and functions and their critical success factors (CSFs) while defining the appropriate metrics for measurement. This process is relevant at an enterprise level as well as at a business function level.

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The subsequent phases of the approach extend the effort to determine the most optimal methods for integrating the enterprise’s supporting data, validating it and applying the necessary components of the IIS’ Business Intelligence Framework to it.

IIS’ BI Framework provides a logical representation of the necessary components to deliver the range of potential BI solutions that may be leveraged. Using the framework, IIS designs and delivers solutions that address the strategic and operational BI requirements of an organization. Each layer in the framework is an abstracted view that represents a grouping of tools, technologies, and processes that cohesively provide a subset of functionality.

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Data flows from the bottom of the framework upward. This path enables a transformation of the data whereby it becomes actionable information and ultimately is refined into its core enterprise intelligence subsets:

  • Data Sources – Structured data sources, including operational systems (systems of record), data warehouses/data marts, third-party data feeds, flat files and others
  • Integration – Data level and message-oriented integration to facilitate virtualized data views and near-time data access
  • Analytics – Formulaic processing of data, including data mining, to produce output meaningful in a functional or strategic context
  • Reporting – Automated or ad hoc mechanism for queries and formatting of data and analytic output meaningful to knowledge workers
  • Business Rules – Application of business semantics to data and analytic output capable of making rule-driven assessments and triggering further actions
  • Workflow – Coordination of multiple triggered processes, potentially including manual and application-level
  • Alerts – Triggering of specific notification events from visual notation in the user interface to messaging and workflow
  • Scorecard – Application of KPI metrics to intelligence for measurement of functional or corporate performance, including process-oriented mechanisms such as Balance Scorecard and technology-oriented mechanisms such as digital dashboards