Author Archives: Nicole Radziwill

About Nicole Radziwill

Nicole Radziwill is a quality manager and data scientist with more than 20 years leadership experience in software, telecommunications, research infrastructure, and higher education. Prior to joining Intelex, she was an associate professor of data science and production systems at James Madison University, Assistant Director for End to End Operations at the National Radio Astronomy Observatory (NRAO), managed software product development for the Green Bank Observatory (GBO), and managed client engagements for Nortel Networks and Clarify (CRM). She is an ASQ-certified manager of operational excellence (CMQ/OE), an ASQ-certified Six Sigma Black Belt (CSSBB), and contributed to the development of ISO 26000—“Guidance on Social Responsibility.”

Voice of the Customer Part 5: Creating Meaningful Customer Experiences

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In this final look at the Voice of the Customer, we’ll look at what you can do for your customer after you collect and organize all the information about their stated, implied, and silent needs.  

While VoC can be useful for uncovering customer preferences regarding pricing or product features, the goal of a truly insightful VoC process is to discover what constitutes a meaningful customer experience. Customer experience is built on the premise that while customers are often rational decision makers, they are also emotional and value experiences that are pleasurable, beneficial, and educational. Furthermore, they value experiences that allow them to co-create those values through their interaction with brands and companies. (Hwang and Seo, 2016)  

Total Customer Experience (TCE) describes the end-to-end process that encompasses the social, physical, and emotional realities of the customer as they move from the initial stages of awareness to the post-transactional “nurture” stage. (Hwang and Seo, 2016) With the democratization of technology contributing … Read more...

GDPR Consent: Legally Managing Data about EU Citizens

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If you collect data in the European Union, you’re well aware of GDPR and potential for steep fines if you are not compliant. Find out which consent rules are key.

It’s been well over a year since the European Union’s (EU) General Data Protection Regulation (GDPR) went into effect. Proposed in 2012, the regulations were approved in 2016 to provide consistency between data privacy and protection regulations across EU member nations.

The cornerstone of GDPR is consent: information about a person belongs to that person. If your organization is collecting data thatin any way relates to a citizen of the EU, that person should be informed about how you plan to use that information and kept informed as your organization’s data management strategy evolves. It doesn’t matter where the individual is located — universities who have even one student who is a citizen of the EU must also comply.… Read more...

World Quality Day 2019: Leading Quality for 100 Years

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World Quality Day – November 14 – provides a forum to reflect on how we can implement more effective processes and systems that positively impact KPIs and business results.

Each year, the second Thursday of November is set aside to reflect on the way quality management can contribute to our work and our lives. Led by the Chartered Quality Institute (CQI) in the United Kingdom, World Quality Day provides a forum to reflect on how we can implement more effective processes and systems that positively impact KPIs and business results — and celebrate outcomes and new insights.

This year’s theme marks the centennial of the CQI’s efforts to grow and expand attention to quality across the United Kingdom and in Europe.

We usually think of quality as an operations function. The quality system (whether we have quality management software implemented or not) helps us keep track of the health and … Read more...

Shining Light on Dark Data

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What is dark data? It could be your organization’s greatest asset, if you know where to find it. We’ll tell you where.

There are insights about your business and EHSQ processes hiding in plain sight… if you know where to look.

Data that is collected — but never shared, mined, or leveraged to gain business insights — is called dark data. Every organization has dark data, which translates to missed opportunities for learning, insights, and performance improvement. Although it’s mostly discussed in the context of expanding the use of Internet of Things (IoT) devices in industrial contexts, there is another

Since storage has become relatively inexpensive (particularly cloud storage), the challenge presented by dark data is growing. While much of dark data resides in enterprise data warehouses, and databases that support Customer Relationship Management (CRM) and Enterprise Resource Planning (ERP) systems, there’s another source that is even more compelling: … Read more...

A Digital Transformation for Voice of the Customer (VoC)

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Fuji Xerox launched a digital transformation project to modernize voice of the customer and raised their Net Promoter Score from -4 to +35.

In the late 2000’s, Fuji Xerox changed its strategy from “Make & Sell” to “Sense & Respond.” The company wanted to be more agile and responsive to changing customer needs, instead of relying on long product development lifecycles and the hope that a market would be in place when a product was released. They decided to overhaul their Voice of the Customer (VoC) program for Industry 4.0. (Sachamanorom & Senoo, 2016) In the process, Fuji identified customer needs according to the three levels and provided labels (VoC 1.0, 2.0 and 3.0) to describe the increase in maturity as new varieties of data were added:

  • Stated needs = knowledge from customer (VoC 1.0)
  • Implied needs = knowledge about customer (VoC 2.0)
  • Hidden needs = knowledge discovered through interactions
… Read more...

Define Systems of Record to Boost Performance

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Quality depends on data because effective decision making depends on data. As a result, successful business and process outcomes will depend on building a culture of quality around data. This includes creating and following management processes to make data accessible, available, and accurate.

One strategy for improving process quality through data is to identify master data and decide which system of record will hold each type of master data. This is similar to knowing who the experts are in your company, knowing how to find them when you need them, and getting assurance that they will provide you with accurate, up-to-date information. For example, your Environment, Health, Safety & Quality (EHSQ) system may be your system of record for emissions, incidents, exposure data, and quality events, providing a single source of truth for these processes.

Master Data

Master data is some of the most important data your organization has – … Read more...

Next Generation Quality: It’s All About the Data

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As early as 2015, McKinsey’s “Digital America” report projected that adoption of Industry 4.0 technologies in manufacturing alone was expected to increase domestic GDP by over $2 Trillion by 2025. This estimate, developed from expectations surrounding productivity enhancements, waste reduction using methods from lean manufacturing, and new business models enabled by technologies like 3D printing and practices such as remanufacturing, is on track to not only be met — but exceeded.

Manufacturing is Being Revitalized

All of these sea changes are happening because of data – and the software used to collect, manipulate, and understand it. While traditional manufacturing jobs have relied on physical and mechanical skills, new manufacturing jobs require additional cognitive skills. As a result, manufacturers are scrambling to identify and roll out technology training for workers that will best support these emerging needs. At the same time, organizations recognize that institutional memory remains critical. Job shadowing … Read more...

Nonconformance vs. CAPA: Three Key Questions

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Communicating the differences between nonconformances (NCRs) and corrective/preventive actions (CAPAs) to staff can be challenging. It’s extremely important, too, that everyone fully grasps the distinctions — because consistency in using your organization’s quality management system will directly contribute to the accuracy of your metrics. Furthermore, this will impact the quality of the insights that can be generated by studying them.

In ISO 9001:2015, there is a defined progression between nonconformity, correction, and corrective action:

  • A nonconformity occurs when a requirement is not fulfilled. The result of a nonconformity, according to Hoyle (2017), is a failure to meet product requirements, carry out a task as required, or meet customer or stakeholder requirements.
  • A correction is the step taken to remedy that single nonconformity. Removing the nonconformity does not prevent the issue from happening again. The result of a correct is to prevent the nonconformity from advancing further in the process.
  • A
… Read more...

Close the Loop on CAPAs with Verification of Effectiveness

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In addition to meeting compliance requirements for many ISO defined management systems, corrective and preventive actions (CAPAs) serve another critical role: to be the backbone for your organization’s continuous improvement efforts. CAPAs help you keep track of problems that are observed, problem solving processes used to investigate them, and resolutions. Additionally, the CAPA process provides a way to trace exactly how a quality management system evolves and matures through business processes.

In ISO 9001:2015, the emphasis has shifted exclusively to corrective actions (CARs), since a risk-based approach (which includes continuous risk assessment, and regular dispatch of actions to mitigate or otherwise manage risks) should theoretically accomplish the same goals as preventive actions did in the past.

Despite the value that can be driven by a robust CAPA process, it can also quickly become overwhelming and unmanageable. Not every quality event has to be immortalized in a CAPA — some don’t … Read more...

Root Cause Analysis and the Tools You Need to Drive Continuous Improvement

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Root Cause Analysis is part of an ecosystem of tools and techniques you can implement to help your organization harness the value from their EHSQ integrated management systems. Improving your organization’s processes requires identifying a methodology and approach that can spur innovation through evidence-based analysis.  

Root Cause Analysis (RCA) is one of several methodologies in your toolkit – including Failure Mode Effects Analysis (FMEA), Control Plans and Corrective Actions (CAR or CAPA) – that can be used to uncover the reasons for safety incidents or near misses, occupational health issues, environmental issues like repeated violations and quality events like recalls and nonconformances. Implementing a framework that incorporates multiple analysis tools to achieve a desired outcome can result in measurable results.  

Top Five Tools for Continuous Improvement

These tools can be extremely valuable for performance when used proactively — and in conjunction with one another. Here’s how they might be used together:   

  1. Identify potential failure modes through a Process Failure Mode Effects
… Read more...