Bert Markgraf is a freelance writer with a strong science and engineering background. He started writing technical papers while working as an engineer in the 1980s. More recently, after starting his own business in IT, he helped organize an online community for which he wrote and edited articles as managing editor, business and economics. He holds a Bachelor of Science degree from McGill University.
Carolyn Gray started writing in 2009. Her work history includes line and staff management in the Finance and Controller's Department of New York Telephone and NYNEX. Gray has a Bachelor of Arts in government from Clark University and a Master of Business Administration from New York University's Stern School of Business in Management and Organization Behavior.
While we often think about compassion as an individual quality, the organizations where we spend our time—such as workplaces, schools, places of worship, and community centers—can actually impact whether and how we respond to someone in distress.
This quiz measures the level of compassion in an organization. It is based on more than 10 years of research on compassion and organizations by the research collaborative CompassionLab and the Center for Positive Organizational Scholarship at the University of Michigan Ross School of Business. CompassionLab has partnered with the Greater Good Science Center to develop this quiz especially for our website.
To take the quiz, think of one organization to which you belong, and keep that organization in mind as you answer the questions. The first 16 items assess how you and others feel, think, and act when you’re in that organization. There are no right or wrong answers, so please respond as honestly as possible. The final 7 questions will help our research team see how people’s experiences of compassion in organizations relate to factors like gender, age, and the size of the organization.
When you're done, you'll get your organization’s compassion score, along with ideas for cultivating compassion in the organization.
Any responses submitted here will never be shared with any organization outside the Greater Good Science Center under any circumstances, ever. All responses are anonymized and only used in aggregate for evaluation purposes.
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Poor quality in manufacturing and service can cost companies as much as 20 percent of revenue in rework, scrap, brand switching, and loss of goodwill. Organizations have begun to understand that prevention saves more time and money than the discovery of flaws after the fact.
The school’s management-oriented certificate program focuses on quality as a priority. Developed in cooperation with industry, the courses can help students develop a total quality management environment to combine the theory and practice of statistical quality control with leadership, teamwork, and problem-solving concepts and skills.
The certificate in quality management teaches the nuts and bolts of a quality organization, prepares students to introduce quality concepts to their organization, and teaches how to put quality principles to work. The certificate can prepare students to work as quality trainers, facilitators, team leaders, or managers at various levels of an organization.
This program is no longer accepting new student applications.
Summary: At one end of a continuum are organizations where the quality program is perceived as no more than a set of slogans. At the other end, each and every employee from entry level to the seat of the chief executive embraces the company’s quality vision, values and goals as a way of life. Companies displaying world-class quality can demonstrate that their leadership unwaveringly and visibly supports quality objectives. They are also passionate in their drive to continually identify and address customer needs.
To illuminate the issue of a culture of quality, Forbes Insights partnered with ASQ (American Society for Quality) to conduct a global survey of 2,291 senior executives and quality professionals in April 2014. In-depth interviews with more than 20 senior executives and consultants add context to the data.
Click here to use our interactive benchmarking tool to see how your culture of quality stacks up.
To get a pdf of the study, please fill out the following information. If you experience any trouble, please send an email to: insights@forbes.com.
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Metadata comes from multiple sources and can be stored in different places, systems, and networks. It’s hard to track it down. When files are updated, new versions are created. So how do you know if you’ve got the latest version? How do you know if the quality is good enough?
The easiest way is to use a clinical metadata repository! And, by creating organizational standards that adhere to industry standards, data will be reliable and consistent. You’ll also have greater transparency.
What’s a clinical metadata repository?
A cloud-based clinical metadata repository is essentially a database that maintains metadata definitions such as forms, datasets, codelists, and variables, throughout the various stages in a clinical trial.
Metadata plays an essential role in allowing different people involved in a clinical trial to access, monitor, track, and log data. All your teams can access information in a readable format, easily and quickly. And, allows for effective planning, communication, and teamwork.
It gives total transparency to all users and ensures that data is of a high standard. Both current and historical metadata should be accurate and easily accessible.
A clinical metadata repository is key to effectively managing organizational standards. It lets you:
- Create, maintain, govern, and use standards consistently.
- Reuse your existing assets.
- Realize the impact of changes.
- Create accurate mappings.
- Be fully compliant.
- Create high-quality submissions.
There are various features that contribute to data quality.
Governance
You can create your own organizational lifecycle for studies and standards to transition through according to your company’s governance process.
Aside from improving data quality, governance lets you control and fully understand the workflow and develop robust organizational standards. This means you can get your product to market safely, and faster.
If metadata isn’t properly managed, it can become out of date and invalid. Good governance means your metadata is accurate and compliant.
Reuse
Organizational standards are stored ‘all in 1 place’ and can be reused. For example, forms, mappings, annotations, controlled terminology, and datasets. A standard can then be updated to suit study-specific requirements. Outputs can also be automated. And, because standards have already been approved, tested, and validated, it means data quality is improved and remains consistent.
Impact analysis
One of the key objectives is to analyze the impact of change. All associated standards and assets will be analyzed to let you know exactly what downstream or upstream metadata will be affected. Impact analysis should also show all assets that are indirectly affected. You can also see how your assets interrelate in the metadata repository. The diagram below shows how the CRF can be affected by a change in the ADaM dataset.
You can also see how your assets interrelate in the metadata repository.
Impact analysis lets you make informed decisions before you make changes. You know the scope of the updates. And, once you have this information, you can decide whether it’s worth making a particular change or not.
Change control
Team members can set up change requests to change existing standard objects. For example, updating a form. The change control process is a pre-defined workflow that defines the approval process as well as the tracking and handling of change requests. All changes are tracked from inception to completion.
Example of an approval process:
Versioning
A good clinical metadata repository allows multiple versions of the same standard that has been updated, improved, or customized.
You can easily identify which version of a standard is being used. And, users can be confident they’re working on the correct version of an asset or standard.
Traceability
Traceability is of key importance in the world of clinical trials, due to the ever-changing regulatory environment.
Traceability must be built into a clinical metadata repository so that all assets can be fully tracked through their lifecycle. With traceability in place, you can see who has accessed the clinical metadata repository. Who made changes to what studies, standards, and assets, and when. And, you can check the differences between them. For example, the differences between versions of the same standard. You can see the full and detailed history of a standard.
Full traceability throughout the lifecycle process ensures audit compliance and increases the chances of a successful submission to the FDA.
Conclusion
The real measure of data quality comes at submission time. Are many questions raised? And, how long does it take to resolve them? If the answer is “not many” and “not long”, then you know without a doubt that the quality of your data is high.
Can Formedix help?
Our clinical metadata repository and study automation platform has been built especially for clinical metadata. It’s off the shelf which means you can get started straight away! It covers all the data quality aspects discussed in this blog.
And, we’re constantly developing it in line with what’s happening in the industry and with the latest standards and regulations.
The Formedix platform is used by many pharma companies, biotechs, and CROs. Each organization has its own objectives and processes, and we work with customers to meet their individual needs. Common goals include:
- Developing internal standards that can be reused.
- Having a central place (MDR) to store forms, datasets, standards, and other study data/metadata.
- eCRF design (in Rave, InForm, or another EDC).
- EDC specification.
- EDC build.
- Quickly creating define.xml from SDTM datasets (automate SDTM conversions).
- Getting ADaM datasets into define.xml.
- SDTM validation.
- Creating Analysis Result Metadata in define.xml.
- Automating end to end studies from eCRF through to submission.
- Seeing data much faster.
- Easier clinical metadata management.
Any of these sound familiar?
You can request a no-obligation demo to see how our automation platform could help you. Or arrange a call so we can talk through your situation and go from there.
Enhance your data strategy with effective data quality and data governance practices. Learn their differences and how to integrate the strategies successfully.
Data quality and data governance describe different parts of enterprise data management strategies but are not mutually exclusive. Together, they can help your business Improve its bottom line by providing better visibility into enterprise assets, all while driving efficiency and operational improvements that lead to greater business agility. This comparison defines both terms, explains their differences and covers how data quality and data governance best practices can be used in tandem.
Jump to:
What is data governance?
Data governance is the process of establishing, aligning and securing data within an organization. It aims to ensure that data is collected, stored, processed and disposed of consistently.
Data governance covers the strategies and processes needed to manage enterprise data effectively to leverage it for business decision-making. It also provides a framework for managing the risk associated with businesses in an uncertain regulatory environment.
In short, data governance is about managing all organizational information assets — not just data but also documents, applications, networks, configurations and metadata.
SEE: For more information, check out our in-depth data governance overview.
There are various data governance software that give you control over data availability, usability, integrity and security. We reviewed the top data governance tools, their features, strengths and weaknesses and pricing so that you can select the best option for you.
Why is data governance important?
Data governance is important for various reasons:
- Compliance: It ensures companies are adhering to laws and regulations, such as GDPR, which can help them avoid hefty fines and penalties.
- Consistency: It provides a consistent approach to handling data across an organization.
- Trust: It builds trust in data as stakeholders can be confident the data is properly managed, up to date and accurate.
- Increased efficiency: It boosts operational efficiency by eliminating unnecessary duplication of data and streamlining data-related processes.
- Better decision-making: High-quality, reliable data makes for better strategic planning, decision-making and overall performance metrics across every sector of a business.
What is data quality?
Data quality is the measure of how complete, accurate, relevant, timely, consistent and trustworthy data is. If data has all these qualities, then it is considered high quality. Businesses with high-quality data can make better decisions about which direction they want to take their company, what strategies they want to implement and what data they have at their disposal for success.
SEE: Learn how to measure data quality.
To ensure data quality, it is necessary to use the best data quality software because any flaws in data quality can lead to poor decision-making. The higher the quality of your data, the more valuable it becomes.
Why is data quality important?
Ensuring data quality is not just a nice thing to have but a crucial aspect of any data-driven approach or business. Managing data quality can lead to:
- Accurate decision-making: High-quality data leads to better decision processes as it often involves tracking performance, predicting future outcomes and identifying potential issues.
- Resource optimization: By ensuring data quality, companies can avoid the waste of resources on incorrect data and help leverage resources efficiently.
- Customer experience: Accurate and up-to-date data helps companies understand customers and their preferences.
- Cost reduction: Poor data quality can lead to costly mistakes and rework, so by investing in data quality, organizations can minimize errors and associated expenses.
Data quality is not just a short-term concern; it impacts an organization’s long-term success and growth. Organizations can ensure they are well-prepared for future challenges and opportunities by maintaining high data quality standards.
What are the main differences between data governance and data quality?
Data governance focuses on overarching data management activities for people, processes and technology. Its applications include designing a sound approach to storing information, managing its life cycle, identifying information that needs to be corrected or deleted, appointing someone as the accountable data steward and investing in technology to help maintain data governance.
On the other hand, data quality focuses on addressing information accuracy issues more granularly by identifying data problems or inconsistencies within individual pieces of information, such as names or addresses. It also covers the design and execution of specific processes to ensure data is accurate, consistent, relevant and complete.
| Data approach | Data governance | Data quality |
|---|---|---|
| Focus | Policies, processes and procedures for managing data assets | Assessing and ensuring the accuracy, consistency and reliability of data |
| Objective | Ensure data is appropriately used, protected and compliant with regulations | Ensure data meets predefined standards and requirements |
| Scope | Broad in scope; organization-wide | Narrower in scope; primarily focuses on datasets or specific projects |
| Responsibilities |
|
|
| Activities | Policy development, defining data ownership and accountability, data classification, data access controls, data retention policies and regulatory compliance | Data profiling, data cleansing, data validation, data standardization, data monitoring and establishing data quality metrics and benchmarks |
How data governance and data quality overlap
Data quality is an important component of data governance but should not be considered a substitute for governance. The relationship between data quality and governance is symbiotic; they are necessary to achieve sound enterprise data management.
SEE: Explore the top data management strategies for small businesses.
Without good data quality practices, organizations will struggle to maintain complete, accurate information that can be trusted to provide input for other corporate processes. Poorly managed metadata will also undermine business intelligence initiatives by introducing inaccuracies in reporting tools. Furthermore, poor data quality makes extracting insights from raw data difficult.
As such, companies must find an appropriate balance between these two important components of data management. It is not enough to have one without the other; organizations must have strong governance practices while implementing robust data quality strategies.
How to integrate data quality and data governance for your organization
Data quality and governance goals are achieved through strategic decisions, operational efforts, ongoing oversight and a willingness to innovate. Implementing data quality and data governance strategies often involves the following:
- Take inventory of your organization’s data to understand what you have, where it resides, how it gets there, who uses it in which business process, how often they use it and why they need it.
- Use this information to determine the most critical datasets to work on first.
- Improve the most critical datasets by defining key performance indicators that will measure improvement.
- Identify opportunities for automation or efficiency by creating an action plan based on those KPIs.
- Determine if governance policies are enforced and if they should be updated or created.
If data governance is ineffective, it may not be possible to reach a high level of data quality. Conversely, organizations cannot achieve effective data governance if data quality is low or non-existent. Both need to be in place to get your desired results.
As a co-founder and CEO of a healthcare financial technology organization that partners with health systems and patients in our community, I am thankful for the many organizations that have already stepped up to support our healthcare providers. Some hotels have opened their doors for free to healthcare workers. Auto manufacturers are producing ventilators, and clothing manufacturers are shifting their operations to sew face masks. But after several weeks of stay-at-home orders nationwide, I am learning of needs beyond masks, ventilators and personal protective equipment (PPE).
To demonstrate ways you can help, view this as an opportunity to contribute to the community. If you or your organization does not fall into the above categories such as hotels or manufacturing, there are still opportunities to make a difference. Additionally, health experts have warned Americans to prepare for a second outbreak of COVID-19 later this year, which could once again strain the healthcare industry.
Operationalize emergency medical facilities.
Nontraditional facilities such as convention centers and hotels have been converted into emergency medical facilities to treat COVID-19 patients. Other emergency medical facilities have been built on football fields, in parks and even in parking garages. Operationalizing these facilities takes a lot of work and logistics coordination within a short period of time.
Even the first step of narrowing down the geographic location or building choice requires thoughtful planning. The American Institute of Architects formed a special task force to share best practices for how to assess building inventory and identify places that could be adapted to help during the crisis.
Encourage your organization to think outside the box. Hold virtual “innovation meetings” where all ideas are welcomed, and expand them beyond your engineers and operational teams. For example, once a location is determined, emergency medical facilities still need to be staffed and stocked. Some facilities also need basic utilities such as water, electricity and internet connectivity. Ask your teams how you can address those needs in the event of a future outbreak later this year.
Help hospitals by supporting their supply chain.
The companies that are supplying ventilators, protective masks and other medical equipment to hospitals still need coordination and connectivity. One ventilator is made of 175 individual parts. Any hurdle within the supply chain — from finding materials for parts to transporting parts for assembly — can delay how quickly hospitals receive these resources.
If your organization is in a position to help companies that are producing ventilators or other necessary equipment, look for ways you can support this. For example, one company, Smith & Richardson, is a supplier for the defense and commercial aerospace industry, but they’ve offered to supply ventilator parts for General Motors. Coordinate with your team to see what’s possible. Similarly, research ways to address the shortage of PPE. Securing the PPE supply chain doesn’t just help hospitals treat existing and future COVID-19 patients, it also helps them safely resume in-person care and planned surgeries that had been previously postponed.
Help healthcare providers access funding.
Between limiting or cancelling elective procedures and spending more to procure PPE and other supplies, many hospitals and health systems are facing cash liquidity issues. This is an area where fintech companies can help, as the sector is dedicated to making it easier for businesses to obtain loans. If you’re a fintech company that operates in the lending space, mobilize your team to help match providers with sources of funding. For instance, independent physician’s offices may need help quickly securing additional funding until they start seeing patients again.
Also, many patients have seen impacts to their income, which has driven people to make difficult decisions as to where they allocate their dollars while considering other necessities like rent and food — which may impact their long-term health. We need to remove barriers, especially financial barriers, to care so patients stay healthy and hospitals stay funded. Whether it’s sourcing funds for patients who need help paying medical expenses or giving patients more flexible payment options, fintech companies can make a difference.
Health IT companies are uniquely positioned to help.
If your company provides IT support to healthcare organizations, consider which tools or services can be quickly implemented, or which offerings can be provided for free. Budgets and executive-level decision-making resources are all focused on COVID-19, and “selling” to hospitals will not be well received.
Healthcare providers are striving to keep their patients informed, and some messages are more time-sensitive than others. Perhaps you can find ways to allow providers to engage with their patients digitally instead of via channels that rely on a physical workforce, such as mail or a call center.
Similarly, can your technology foster engagement between team members working for the hospital, even if they’re remote? Some hospitals have nonclinical teams working from home. Keeping these teams productive and engaged is critical to the operational health of the hospital. Work with your team to brainstorm ways for promoting open lines of communication among remote users.
Here’s how you can help in the future.
In the near future, hospitals will face new challenges, and there may be ways you can help. For example, since hospitals have advised patients to postpone nonurgent care to make room for COVID-19 patients, there will likely be an influx of rescheduled procedures after the pandemic. Manually calling patients to reschedule will not be feasible. Is there a way your technology can make this process more efficient?
While the current situation is something no one planned for, there is no shortage of opportunities to help others, especially hospitals. Find ways to help that leverage your skill set. As a leader, I’m mobilizing my team and our partnerships to make a difference. In my home state of Georgia, we’re working with an initiative to acquire critical resources for the state’s hospitals and raise awareness of staying at home. You can leverage your strengths to make an impact, too. By helping providers respond to new challenges proactively, the economy can recover faster. Together, we can come out of this stronger.
