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Performance Analytics


Analyzing data is nothing new — it's one of the most powerful tools any business can implement when planning for today and tomorrow. And while the traditional use of learning analytics has many benefits, what it can't provide might be the most important.

That's where Raytheon Professional Services (RPS) steps in. With our ability to apply powerful Performance Analytics, we let organizations view their data and their future in ways they had never before imagined.

Most learning and development (L&D) organizations want better ways to use analytics to improve their learning strategies and outcomes. Yet, a recent survey of over 400 organizations by RPS and Human Capital Media found that most L&D organizations still rely solely on learning tools for their data. By focusing on learning data, these organizations are focusing on the past — lagging indicators — instead of analyzing data to address the performance and business challenges that they face today, or gaining the information needed to predict future outcomes.

Performance Analytics is the engine that uncovers insights and reveals hidden value, to define new, targeted learning interventions. The result is learning spend helps the business achieve key objectives.

Raytheon Professional Services' Performance Analytics uses business data and leading indicators to improve performance through learning solutions. By combining performance data (e.g., tasks, business key performance indicators) and workforce data (e.g., hiring, retention) with learning data, RPS ensures a strong link between learning and business outcomes.


RPS' Performance Analytics shifts the analysis focus away from learning and toward a more comprehensive analysis of performance issues and opportunities. By bridging the gap between current workforce capabilities and strategic goals, Performance Analytics:

  • Combines performance, workforce and learning data to enable a comprehensive data-driven analysis of key business and performance challenges;
  • Analyzes gaps between current and future states, identifies root causes for low performance and provides learning solutions to address present and future performance gaps; and
  • Uncovers insights and reveals hidden value, helping to define new, targeted learning interventions.


RPS' expertise in the field of data analytics combines proven descriptive, predictive and inferential analyses to deliver valuable insights. After identifying patterns, performance issues, strategic needs, workforce challenges and outliers in customers' data, we provide a tailored plan detailing specific initiatives that can drive learning strategy and tactics for the near and long term.


Achieving a return on learning investment requires a systematic approach with a robust set of analysis and process tools. RPS is at the forefront of the learning industry in using performance, workflow and learning data to design and deploy learning solutions that deliver measurable impact. Our real-world customer case studies — with demonstrated performance improvements — show:

  • Learning focus is better aligned with business critical imperatives;
  • An accelerated time to proficiency;
  • An improved ability to troubleshoot and repair products properly the first time; and
  • Improved customer service satisfaction.



Today, business cycles have accelerated and leaders must make decisions more quickly than ever. The ability to harness business analytics and make high-quality decisions is a core competency. Companies that use data in real time to make business decisions gain competitive advantage. Leadership teams must have these skills before strategic decisions points are encountered; once the crisis occurs, there isn’t time to obtain them.

RPS looks at various statistical techniques central to the issue of turning data into information. Then we turn that information into key outcomes such as increased customer satisfaction and profits.

Predictive Analytics helps your organization predict future events with confidence so you can make smarter decisions and improve business results. Several key skills can help chart the road ahead:

  • Detect issues — Look at the data to find trends, shifts, outliers or any other issues that may reflect on future performance.
  • Look for correlations — Identify trends and relationships between metrics. Look for early-warning metrics signaling later issues and opportunities to take advantage of changes over time.
  • Data Clustering — Sift through large numbers of variables simultaneously to categorize or target. Look for opportunities to prioritize resources in areas of highest impact.
  • Forecast modeling — Define the likely future, showing the possible limits of uncertainty. Define risks and opportunities.



Descriptive Business Analytics for ROI

Descriptive Analytics takes a high-resolution look at the business using data needed to describe the current state of the business situation. It show us trends, shifts and other patterns through reports, dashboards and management information systems, among others. Descriptive models quantify relationships in data in a way that is often used to classify items into groups, helping to rank data based on past history. These models can be used, for example, to categorize customers by their product preferences and life stage, or identify defect trends. They can help you understand who your customers are, how markets have shifted and changed, and what subtle but important nuances have occurred in a product life cycle.

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