Master the Power of Your Data

Performance management – being able to measure and optimize performance-based on a clearly articulated and communicated organizational strategy is critical to successful business. A study conducted by the American Management Association interviewed 203 companies (ranging in size from $27 million to $50 billion) and those that are "measurement managed" rank in the top third of their industry.

Performance management helps companies reach that "top third" status by enabling them to clearly articulate their business strategy, align their business to that strategy, identify their Key Performance Indicators (KPIs) and track progress, and deliver the information to the decision-makers. Just how do organizations monitor and manage this process?

Like anything else, a data analysis scorecard is an effective technology for measuring and monitoring product, process, and system performance. It enables the alignment of KPIs, and provides the ability to track and optimize performance based on those indicators. KPIs are measured based on a set of metrics that consider multiple interdependent perspectives, and they help organizations balance their focus on more than just the "bottom line." This approach ensures design, manufacturing, quality (six sigma), and customer service are weighted appropriately which results in well-rounded successful companies. Until recently, however, a data analysis scorecard was limited in reference to the level of information it provided and the degree to which it enabled drill down of presented information for the purpose of heavy analysis. Data warehouse is helping to eliminate those limitations.

The data analysis scorecard and data warehousing are a perfect combination to achieve the greatest, most efficient, and accurate performance analysis and management yet. The combined technologies enable organizations to balance their resources and manage their business functions according to process and key performance indicators. Data warehouse is the effective infrastructure that supports the performance management process and it provides a means for collecting and storing the data. The data analysis scorecard and data warehousing technology collaboration provides decision-makers with the ability to drill down on the data delivered by the data analysis scorecard.
The data warehouse provides companies with the ability to compare and analyze identified KPIs against actual data, allowing for benchmarking and performance improvement tracking. This is a critical piece of performance management – knowing where you have been, where you are now, and where you are heading. Unlike the annual performance appraisal, the data warehouse-supported data analysis scorecard utility enables organizations to monitor their product, process, and system progress continuously.

There are a few critical components in an effective data analysis scorecard utility:

1. Getting last month's results 30 days late doesn't cut it in today's rapidly changing world. Some measures should be tracked to the day or shift; some are acceptable weekly, while others are acceptable at month end. Determining what is needed when and why should be driven by product volume.

2. Presenting the measures of manufacturing test data is one element of the data analysis scorecard utility, but determining and correcting the problematic areas in the product, process, and/or system is a terrific communications tool that supports the upward and downward feedback at management level and across business functions will turn the scorecard into a true management cockpit.

3. A good data analysis scorecard utility should contain the finest level of detail in order to craft the complete picture of all the parametric measures. For instance, it should contain measures (i.e. variable or attribute parametric test data), design measures (i.e. when developing specifications prior to and after performing a Monte Carlo) and sub-tier data (i.e. supplier test data, etc.).

There is considerable analysis involved in implementing a performance management solution. Businesses must be carefully examined, and the metrics must be broken down by:
• Time dimensions
• Data availability
• Data access requirements
• Completeness and requirements
• Frequency of use

That information translates into the architectural components that deliver the warehouse and, ultimately, the data analysis scorecard utility. Therefore, the initial commitment to defining the appropriate strategies and measures at every level of the business is crucial.

KPIs are the primary means of communicating performance across the organization. KPIs should be balanced and not just focus on the traditional failure mode measures used to monitor performance. The combination of data warehousing and data analysis scorecard technology maintain KPIs when and where they are needed most, helping companies better satisfy customers, monitor progress, benchmark process and activities, drive change, show signposts of improvement, create balance and provide relevant information.

The Data warehouse and data analysis scorecards are where strategy, corporate performance management and business intelligence come together. When implemented properly, they communicate how executing strategy should become manifest. They display results and progress. The metrics should translate an organization’s strategy into observable outcomes and allow performance to be confronted with goals. This is where the strategy rubber meets the road.

By incorporating a data analysis scorecard into manufacturing (and design), and not just financial and operational indicators, but including complete measures on all the manufacturing test data, data analysis scorecards amplify the voice of the customer within the corporation. Companies are only as good as the compounded decisions its people make. Data analysis scorecards not only supplies a set of software tools, but also enables better decision processes to allow management to act on product, process, or system data. When implemented well, data analysis scorecards and proper data warehousing help steer the business.

Data analysis scorecard solutions promote performance visibility of the product, process, and system. By providing insight, they allow for optimization and alignment of corporate resource planning, improved product reliability, and better control of their processes, product, and system. R&D will benefit from the use of the data analysis scorecard as well – it will allow them to deliver manufacturing a robust product since the data would be characterized prior to production release. Otherwise, manufacturing may have pre-production/production issues that become increasingly difficult to solve and sometimes a detriment to product release.

In light of these realities, senior management must get a grip on this large chunk of discretionary corporate spending. The fact that results are known to be structurally variable and hard to predict makes the quest for valid measurement even more critical. On top of that, companies don’t just operate to make a profit today; they must be constantly focused at ensuring sustainable profits in the future as well.

The idea behind data analysis scorecards is that noteworthy fluctuations in performance become instantly visible. When change occurs, the underlying root cause needs to be made visible, too! By drilling down or through, explanations for change are surfaced. By disaggregating the numbers in the scorecard along critical dimensions, new insights emerge as well. This is where the data analysis scorecard really adds value.

Otherwise, any blip on the radar might send managers on a search frenzy, looking for an (underlying) explanation what caused this change. Conversely, lack of such drill down functionality with a scorecard (and fruitless searches in the past), will lead managers to ‘learn to ignore’ some failures. This may lead to poor product performance once fielded.

The whole idea of business metrics is that they should drive the business forward, and provide the best possible implementation of corporate strategy. However, translating strategy into action is never ‘done’ and one must look at the KPIs drivers on a regular basis to ensure they remain important.

About the Companies

TestSoft, Inc. and HELM Analytics have teamed up to provide manufacturers with comprehensive manufacturing quality control, production process, and supply chain management tools.

HELM Analytics system integration and data capture capabilities coupled with TestSoft’s Explicore™ software provide powerful solutions to increase manufacturing efficiency and identify cost cutting measures. Explicore ™ software, a lean Six Sigma based tool, is a Data Analysis Scorecard Utility that provides professionals with a powerful, reliable, and easy-to-use utility to fully analyze data and manage large and complex projects. Customers use a data parser as part of Explicore™ to capture data more efficiently and effectively. Explicore™ automatically characterizes successful and failed test data providing a solid evaluation of the manufacturing process. TestSoft’s patented process enables users to quickly capture, characterize, analyze, assess and measure product parameters. This enables users to determine the reliability of their processes and products avoiding costly design and testing mistakes and production downtime.

Leveraging these solutions creates cost savings, increases efficiency and ensures product quality is supported throughout the manufacturing process. Design flaws and testing issues can be identified early in the process and adjustments can be made quickly limiting cost overrun and production downtime. Developing cost saving initiatives is critical. HELM solutions help manufacturers track customer orders, production information and historical use to provide an overview of the total customer relationship and create opportunities for additional sales or product placement. Integrating disparate systems and providing a single access point for comprehensive business information creates opportunities and positions manufacturers to capture both operational and supply chain actionable data to help drive their business forward.

HELM Analytics and TestSoft, Inc. solution help cut internal costs and maximize production efficiency.

HELM Analytics™, a division of CCS Global Tech delivers Comprehensive Enterprise Applications powered by Business Intelligence solutions. The company automates business processes and workflows within complex supply chain relationships. Our solutions include compliance, predictive analytics, data security, regulatory automation, reporting, and enterprise-wide business analytic capabilities for companies of all sizes. For more information, visit www.helm360.com

TestSoft delivers problem-solving technologies through software, training, and comprehensive services. The company also provides automated data capture and characterization to the customer when and where they need it most. TestSoft delivers world-class service and customized support solutions designed to reduce costs and uncertainties associated with managing, manufacturing products and components. Our services are designed to help solve specific problems encountered during the manufacturing process. For more information, visit www.testsoftinc.com.