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Governance: It's good for your data

07.12.19

Read this if you are an Institutional Research (IR) Director, a Registrar, or are in the C-Suite.

In my last blog, I defined the what and the why of data governance, and outlined the value of data governance in higher education environments. I also asserted data isn’t the problem―the real culprit is our handling of the data (or rather, our deferral of data responsibility to others).

While I remain convinced that data isn’t the problem, recent experiences in the field have confirmed the fact that data governance is problematic. So much, in fact, that I believe data governance defies a “solid,” point-in-time solution. Discouraged? Don’t be. Just recalibrate your expectations, and pursue an adaptive strategy.

This starts with developing data governance guiding principles, with three initial points to consider: 

  1. Key stakeholders should develop your institution’s guiding principles. The team should include representatives from areas such as the office of the Registrar, Human Resources, Institutional Research, and other significant producers and consumers of institutional data. 
  2. The focus of your guiding principles must be on the strategic outcomes your institution is trying to achieve, and the information needed for data-driven decision-making.
  3. Specific guiding principles will vary from institution to institution; effective data governance requires both structure and flexibility.

Here are some baseline principles your institution may want to adopt and modify to suit your particular needs.

  • Data governance entails iterative processes, attention to measures and metrics, and ongoing effort. The institution’s governance framework should be transparent, practical, and agile. This ensures that governance is seen as beneficial to data management and not an impediment.
  • Governance is an enabler. The institution’s work should help accomplish objectives and solve problems aligned with strategic priorities.
  • Work with the big picture in mind. Start from the vantage point that data is an institutional asset. Without an institutional asset mentality it’s difficult to break down the silos that make data valuable to the organization.
  • The institution should identify data trustees and stewards that will lead the data governance efforts at your institution
    • Data trustees should have responsibility over data, and have the highest level of responsibility for custodianship of data.
    • Data stewards should act on behalf of data trustees, and be accountable for managing and maintaining data.
  • Data quality needs to be baked into the governance process. The institution should build data quality into every step of capture and entry. This will increase user confidence that there is data integrity. The institution should develop working agreements for sharing and accessing data across organizational lines. The institution should strive for processes and documentation that is consistent, manageable, and effective. This helps projects run smoothly, with consistent results every time.
  • The institution should pay attention to building security into the data usage cycle. An institution’s security measures and practices need to be inherent in the day-to-day management of data, and balanced with the working agreements mentioned above. This keeps data secure and protected for the entire organization.
  •  Agreed upon rules and guidelines should be developed to support a data governance structure and decision-making. The institution should define and use pragmatic approaches and practical plans that reward sustainability and collaboration, building a successful roadmap for the future. 

Next Steps

Are you curious about additional guiding principles? Contact me. In the meantime, keep your eyes peeled for a future blog that digs deeper into the roles of data trustees and stewards.
 

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This spring, I published a blog about the importance of data governance in higher education institutions. In the summer, a second blog covered implementing baseline principles for data governance. With fall upon us, it is time to transition to discussing three critical steps to create a data governance culture. 

1.    Understand the people side of change.

The culture of any organization begins and ends with its people. As you know, people are notoriously finicky when it comes to change (especially change like data governance initiatives that may alter the way we have to understand or interact with institutional data). I recommend that any higher education institution apply a change management methodology (e.g., Prosci®, Lewin’s Change Management Model) in order to gauge the awareness of, the desire for, and the practical realities of this change. If you apply your chosen methodology in an effective and consistent manner, change management will help you increase buy-in and break down resistance. 

2.    Identify and empower the right people for the right roles.

Higher education institutions often focus on data governance processes and technologies. While this is necessary, you can’t overlook the people part of data governance. In fact, you can argue it is the most important part, because without people, there will be no one to follow the processes you create or use the technologies you implement. 

To find the right people, you need to identify and establish three specific roles for your institution: data trustees, data stewards, and data managers. Once you have organized these roles and responsibilities, data governance becomes easier to manage. Some definitions:

Data trustees (the sponsors) – senior leadership (or designees) who oversee data policy, planning, and management. Their responsibilities include: 

  • Promoting data governance 
  • Approving and updating data policies​​
  • Assigning and overseeing data stewards
  • Being responsible for data governance

Data stewards (the owners) – directors, managers, associate deans, or associate vice presidents who manage one or more data types. Their responsibilities include:

  • Applying and overseeing data governance policies in their functional areas
  • Following legal requirements pertaining to data in their functional areas
  • Classifying data and identifying data safeguards
  • Being accountable for data governance

Data managers (the caretakers) – data system managers, senior data analysts, or functional users (registrar, financial aid, human resources, etc.) who perform day-to-day data collection and management operations. Their responsibilities include:

  • Implementing data governance policies in their functional areas
  • Resolving data issues in their functional areas 
  • Provide training and appropriate documentation to data users
  • Being informed and consulted about data governance

3.    Be consistent and hold people accountable.

Ultimately, your data governance team needs accountability in order to thrive. Therefore, it is up to data trustees, data stewards, and data managers to hold regular meetings, take and distribute meeting notes, and identify and follow up on meeting action items. Without this follow through, data governance initiatives will likely stall or stop altogether. 

More information on data governance 

Are you still curious about additional guiding principles of data governance in higher education? Please contact the team
 

Article
People Power: Enacting Sustainable Data Governance

“The world is one big data problem,” says MIT scientist and visionary Andrew McAfee.

That’s a daunting (though hardly surprising) quote for many in data-rich sectors, including higher education. Yet blaming data is like blaming air for a malfunctioning wind turbine. Data is a valuable asset that can make your institution move.

To many of us, however, data remains a four-letter word. The real culprit behind the perceived data problem is our handling and perception of data and the role it can play in our success—that is, the relegating of data to a select, responsible few, who are usually separated into hardened silos. For example, a common assumption in higher education is that the IT team can handle it. Not so. Data needs to be viewed as an institutional asset, consumed by many and used by the institution for the strategic purposes of student success, scholarship, and more.

The first step in addressing your “big” data problem? Data governance.

What is data governance?

There are various definitions, but the one we use with our clients is “the ongoing and evolutionary process driven by leaders to establish principles, policies, business rules, and metrics for data sharing.”

Please note that the phrase “IT” does not appear anywhere in this definition.

Why is data governance necessary? For many reasons, including:

  1. Data governance enables analytics. Without data governance, it’s difficult to gain value from analytics initiatives which will produce inconsistent results. A critical first step in any data analytics initiative is to make sure that definitions are widely accepted and standards have been established. This step allows decision makers to have confidence in the data being analyzed to describe, predict, and improve operations.
     
  2. Data governance strengthens privacy, security, and compliance. Compliance requirements for both public and private institutions constantly evolve. The more data-reliant your world becomes, the more protected your data needs to be. If an organization does not implement security practices as part of its data governance framework, it becomes easier to fall out of compliance. 
     
  3. Data governance supports agility. How many times have reports for basic information (part-time faculty or student FTEs per semester, for example) been requested, reviewed, and returned for further clarification or correction? And that’s just within your department! Now add multiple requests from the perspective of different departments, and you’re surely going through multiple iterations to create that report. That takes time and effort. By strengthening your data governance framework, you can streamline reporting processes by increasing the level of trust you have in the information you are seeking. Understanding the value of data governance is the easy part/ The real trick is implementing a sustainable data governance framework that recognizes that data is an institutional asset and not just a four-letter word.

Stay tuned for part two of this blog series: The how of data governance in higher education. In the meantime, reach out to me if you would like to discuss additional data governance benefits for your institution.

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Data is a four-letter word. Governance is not.

As a new year is upon us, many people think about “out with the old and in with the new”. For those of us who think about technology, and in particular, blockchain technology, the new year brings with it the realization that blockchain is here to stay (at least in some form). Therefore, higher education leaders need to familiarize themselves with some of the technology’s possible uses, even if they don’t need to grasp the day-to-day operational requirements. Here’s a high-level perspective of blockchain to help you answer some basic questions.

Are blockchain and bitcoin interchangeable terms?

No they aren’t. Bitcoin is an electronic currency that uses blockchain technology, (first developed circa 2008 to record bitcoin transactions). Since 2008, many companies and organizations utilize blockchain technology for a multitude of purposes.

What is a blockchain?

In its simplest terms, a blockchain is a decentralized, digital list (“chain”) of timestamped records (“blocks”) that are connected, secured by cryptography, and updated by participant consensus.

What is cryptography?

Cryptography refers to converting unencrypted information into encrypted information—and vice versa—to both protect data and authenticate users.

What are the pros of using blockchain?

Because blockchain technology is inherently decentralized, you can reduce the need for “middleman” entities (e.g., financial institutions or student clearinghouses). This, in turn, can lower transactional costs and other expenses, and cybersecurity risks—as hackers often like to target large, info-rich, centralized databases.

Decentralization removes central points of failure. In addition, blockchain transactions are generally more secure than other types of transactions, irreversible, and verifiable by the participants. These transaction qualities help prevent fraud, malware attacks, and other risks and issues prevalent today.

What are the cons of using blockchain technology?

Each blockchain transaction requires signature verification and processing, which can be resource-intensive. Furthermore, blockchain technology currently faces strong opposition from certain financial institutions for a variety of reasons. Finally, although blockchains offer a secure platform, they are not impervious to cyberattacks. Blockchain does not guarantee a hacker-proof environment.

How can blockchain benefit higher education institutions?

Blockchain technology can provide higher education institutions with a more secure way of making and recording financial transactions. You can use blockchains to verify and transfer academic credits and certifications, protect student personal identifiable information (PII) while simultaneously allowing students to access and transport their PII, decentralize academic content, and customize learning experiences. At its core, blockchain provides a fresh alternative to traditional methods of identity verification, an ongoing challenge for higher education administration.

As blockchain becomes less of a buzzword and begins to expand beyond the realm of digital currency, colleges and universities need to consider it for common challenges such as identity management, application processing, and student credentialing. If you’d like to discuss the potential benefits blockchain technology provides, please contact me.

Article
Higher education and blockchain 101: It's not just for bitcoin anymore

The late science fiction writer (and college professor) Isaac Asimov once said: “I do not fear computers. I fear the lack of them.” Had Asimov worked in higher ed IT management, he might have added: “but above all else, I fear the lack of computer staff.”

Indeed, it can be a challenge for higher education institutions to recruit and retain IT professionals. Private companies often pay more in a good economy, and in certain areas of the nation, open IT positions at colleges and universities outnumber available, qualified IT workers. According to one study from 2016, almost half of higher education IT workers are at risk of leaving the institutions they serve, largely for better opportunities and more supportive workplaces. Understandably, IT leadership fears an uncertain future of vacant roles—yet there are simple tactics that can help you improve the chances of filling open positions.

Emphasize the whole package

You need to leverage your institution’s strengths when recruiting IT talent. A focus on innovation, project leadership, and responsibility for supporting the mission of the institution are important attributes to promote when recruiting. Your institution should sell quality of life, which can be much more attractive than corporate culture. Many candidates are attracted to the energy and activity of college campuses, in addition to the numerous social and recreational outlets colleges provide.

Benefit packages are another strong asset for recruiting top talent. Schools need to ensure potential candidates know the amount of paid leave, retirement, and educational assistance for employees and employee family members. These added perks will pique the interest of many candidates who might otherwise have only looked at salary during the process.

Use the right job title

Some current school vacancies have very specific job titles, such as “Portal Administrator” or “Learning Multimedia Developer.” However, this specificity can limit visibility on popular job posting sites, reducing the number of qualified applicants. Job titles, such as “Web Developer” and “Java Developer,” can yield better search results. Furthermore, some current vacancies include a number or level after the job title (e.g., “System Administrator 2”), which also limits visibility on these sites. By removing these indicators, you can significantly increase the applicant pool.

Focus on service, not just technology

Each year, institutions deploy an increasing number of Software as a Service (SaaS) and hosted applications. As higher education institutions invest more in these applications, they need fewer personnel for day-to-day technology maintenance support. In turn, this allows IT organizations to focus limited resources on services that identify and analyze technology solutions, provide guidance to optimize technology investments, and manage vendor relationships. IT staff with soft skills will become even more valuable to your institution as they engage in more people- and process-centric efforts.

Fill in the future

It may seem like science fiction, but by revising your recruiting and retention tactics, your higher education institution can improve its chances of filling IT positions in a competitive job market. In a future blog, I’ll provide ideas for cultivating staff from your institution via student workers and upcoming graduates. If you’d like to discuss additional staffing tactics, send me an email.

Article
No science fiction: Tactics for recruiting and retaining higher education IT positions

We humans have a complex attitude toward change. In one sense, we like finding it. For instance: “Now I can buy something from the vending machine!” In reality, we try to avoid change as much as possible. Why? Because it’s frightening. Consider this quote from Mary Shelley’s Frankenstein: “Nothing is so painful to the human mind as a great and sudden change.”

The key word in that quote is “sudden.” Because the more we prepare for change, the less painful it becomes. One crucial way to prepare for change is to assess how ready we are for something new.

Which brings us to you. The fact you are reading a blog post with the words “Readiness for Enterprise Systems” in its title suggests that you have considered, or are considering, changing your institution’s Enterprise Resource Planning (ERP) system or other enterprise software, such as LMS, SIS, CRM, etc. This change is no minor adjustment.

Enterprise systems are complex, impacting institutional activities at many levels, from managing student records, finances, and human resources, to enabling student enrollment and registration. Is your institution prepared for transformation across the organization? To find out, assess your institution’s readiness for change. To help illustrate what an assessment might entail, I’ll outline BerryDunn’s method.

Step #1: Understanding Key Indicators for Readiness
When assisting a client to determine readiness, BerryDunn begins engaging stakeholders from across the institution (e.g., staff, faculty, and students) to understand the current environment. This allows us to address seven key indicators for change readiness:

  1. Stakeholder Buy-In. The key to success in changing an ERP platform is for users to understand the value that the change will bring. “Do stakeholders know how the new system will benefit them? Or, from their perspective, ‘What’s in it for me (aka, WIIFM)?’”
  2. Executive Sponsorship. In order to obtain stakeholder buy-in, leaders have to communicate effectively with various parties about change. They will be required to display strong and consistent leadership when stakeholders are faced with challenges with vendors, timing, scope creep, or other issues. “Are leaders prepared to lead the charge? Are they committed to change?”
     
  3. Vendor Ability. Each institution has specific operational needs and programmatic objectives. ERP vendors will highlight their strengths and may de-emphasize weaknesses that may exist in their products. “Are vendors actually able to meet the institution’s functional needs and align their software with strategic objectives?”
     
  4. Business Process Redesign. As mentioned above, it can be a struggle to align operational needs and programmatic objectives with vendor software. It’s even harder to achieve this while ensuring that, in implementing a new ERP system, an institution won’t lose valuable functionality that had been provided by the previous ERP. “Does the client fully understand the impact of a new ERP system on their processes?”
     
  5. Project Management. Proactive project management is critical when changing an ERP system. Project managers need to engage institutional stakeholders, project sponsors, and vendors to keep them apprised of progress. “Are project managers empowered to maintain strong communication with all stakeholders?”
     
  6. Data Governance. Another key indicator of ERP readiness is how well-defined data management is before implementation. ERP replacement projects are jeopardized when institutions don’t understand their data assets, or don’t know what level of data migration is necessary. “Is the institution prepared for data migration?”
     
  7. Software Change Management. As ERP vendors move their products to the cloud, the software they sell will become less customizable, but more configurable. In other words, customers won’t necessarily be able to modify the base software code, but they will have more options in regards to defined fields, workflow, and user interface. Although this sounds limiting, it is actually an opportunity to streamline operations, add discipline to software update timelines, and require organizations to consider how to best complete their administrative functions. It is critical that an institution adapt its software change management practices to meet this reality. “Do the institution’s software change management practices reflect how software is delivered by vendors today?”

Step #2: Establish Agreed-Upon Metrics
Based on our analysis from Step #1, we then score these indicators of readiness based on a maturity scale from 0 – 5, using the following parameters:

0  Non-existent
1  Aware, but not ready to change
2  Aware and open to change, but lack understanding of path forward
3  Accept that change is needed, but clear action plan is not in place
4  Accept that change is imminent and is being planned for
5  Readiness for change has broad understanding, is accepted, and is being executed 

Step #3: Score the Readiness of Your Organization
When you work with a consulting firm to assess your institution’s readiness for change, you should expect tangible takeaways that will inform stakeholders and provide a baseline metric. For example, we prepare a brief report that outlines a score for each of the seven maturity indicators of ERP readiness and provides supporting information for the basis of each score.

Here is an example of a Software Change Management section from a hypothetical ERP Readiness Report:

READINESS INDICATORS

BASIS FOR SCORE

SCORE (0 – 5)

Software Change Management

The University does have an effective software change management methodology, and a standard process for prioritizing requests to its current ERP system. This model may change significantly if a cloud system is chosen, and will require a new approach to configuration and asset management.

3


Finally, based on the weighted aggregate score of the report, BerryDunn determines the institution’s readiness for change, and provides recommendations on how to remediate low scores, and sustain higher scores.

Now for the good news. By setting a baseline early in your readiness planning, the scoring can be revisited over time to measure progress and provide project leadership with a simple, but effective, approach to tracking change management within the organization.

Next Steps
As you can see, implementing a new ERP doesn’t have to be a monstrous experience. You simply need to determine your ERP readiness, and follow a common-sense plan for change management. If you’d like to talk more about this process, send me an email: dhoule@berrydunn.com. I look forward to learning about the great changes your institution has planned.

Article
Assessing organizational readiness for enterprise systems

Read this if you use, manage, or procure public safety and corrections technology.

Recently we discussed the benefits of developing a strong, succinct Request for Proposal (RFP) that attracts Offender Management Systems (OMS) vendors through a competitive solicitation. Conversely, we explored the advantages and disadvantages of leading a non-competitive solicitation. Industry standards and best practices serve as the common thread between competitive and non-competitive solicitations for standard implementations. So, how does an agency prepare to navigate the nuances and avoid the “gotchas” of a non-standard implementation in the corrections realm?

Functional areas in the corrections industry exist in an ever-evolving state. The ongoing functional area refinements serve to overcome potential gaps between standardizing organizations (e.g., CTA, APPA) and your agency’s operations. For example, CTA does not distinguish incidents from disciplines as distinct functional areas. While merging workflows for incidents and disciplines may align with one agency’s practice, your agency may not always correlate the two functions (e.g., disciplinary action might not always result from an incident). Moreover, your agency may not have a need for every functional area, such as community corrections, depending on the scale of your operation.

Your agency should view the industry standards as a guide rather than the source of truth, which helps you cultivate a less parochial approach driven solely by standards and follow instead a more pragmatic plan, comprised of your unique operations and best practices. CTA and APPA specifications alone will result in comprehensive solicitation. For that reason, agencies can enhance an OMS modernization initiative by enhancing solicitation requirements to include jurisdictional specifications resulting from interviews with end-users and policy research. 

Upcoming OMS webinar

On Thursday, November 5, our consulting team will host a webinar on navigating a solicitation for a new OMS. During the webinar, our team will revisit the benefits of an independent third-party on your solicitation and review industry standards, and will discuss:

  1. Crafting requirements that address common OMS functions, as well as jurisdiction-specific functions (i.e., those that address the unique statutes of the state). Crafting requirements helps your agency to ensure a replacement system addresses core business functions, provides a modern technical infrastructure, and complies with local, state, and federal regulations.
  2. Thriving with a collaborative approach when acquiring and implementing an OMS system, helping to ensure all stakeholders not only participate in the project but also buy into the critical success factors.

If you have questions about your specific situation with OMS implementations, or would like to receive more information about the webinar, please contact one of our public safety consultants.
 

Article
Managing non-standard Offender Management System (OMS) implementations

Read this if you are a state Medicaid agency, state managed care office, or managed care organization (MCO). 

The COVID-19 pandemic and resulting economic downturn has led to increased Medicaid member enrollment and has placed a strain on state budgets to support Medicaid and other health and human services programs. It has also impacted traditional Medicaid utilization patterns and has challenged provider reimbursement models, forcing managed care programs and supporting MCOs to:

  • rethink the control of program costs, 
  • seek MCO program flexibilities to expand coverage such as telehealth, and 
  • make operational changes to support their growing member populations.

Managed care opportunities

While COVID-19 has created many challenges, at the same time it has given managed care programs the opportunity to restructure their delivery of services not only during the public health emergency, but for the longer term. Flexibilities sought this year from the Centers of Medicare & Medicaid Services (CMS) put in place through waivers and state plan amendments have helped expand services in areas such as the delivery of COVID-19 testing, medical supplies, and behavioral health services via telehealth. 

These flexibilities have relieved the administrative burden on Medicaid programs, such as performance and reporting requirements outlined under federal law and 42 CFR §438. Although these flexibilities have helped managed care programs expand services during the pandemic, the benefits are temporary and will require MCOs to make programmatic changes to meet the demands of its population during and after the public health emergency.

A recent study by Families USA cited 38 states reporting 7% growth in member enrollment since February. As the Medicaid population continues to grow in 2020 and beyond, managed care programs have numerous opportunities to consider: 

Managing care coordination and establishing efficiencies with home- and community-based services (HCBS)

The increased risk of adverse health outcomes from COVID-19 due to older age and chronic illness, and the demands on providers and medical supplies, has forced Medicaid programs to seek waiver flexibilities to expand HCBS. As part of HCBS delivery, MCOs may focus on the sickest and most costly of their member populations to control costs and preserve quality. 

MCOs will most likely monitor cost drivers such as chronic conditions, catastrophic health events, and frequent visits to primary care providers and hospitals. MCOs have the opportunity to establish efficiencies and improve transitions across different providers and multiple conditions to better manage the over-utilization of services for members in skilled nursing facilities, and for those who receive HCBS and outpatient services.

Adjusting and monitoring Value-Based Payment (VBP) models

With the continued transition to VBP models, Medicaid programs face the challenge of added costs and adapting plan operations and services to address pandemic-related needs, chronic conditions, and comorbidities. 

Building on the latest guidance to state Medicaid directors from CMS on value-based care, Medicaid programs can look at COVID-19 impacts on provider reimbursement prior to the rollout of VBP models. Medicaid programs can continue establishing payment models that improve health outcomes, quality, and member experience. States can adjust contracts and adherence to local and state public health priorities and national quality measures to advance their VBP strategy. Managed care programs may need to consider a phased rollout of their VBP models to build buy-in from providers transitioning from traditional fee-for-services payment models, and to allow for refinements to current VBP models.

Continued stratification and the assessment of risk

By analyzing COVID-19’s impact on the quality of care and member experience, improved outcomes, and member and program costs, managed care programs can improve their population stratification methodologies factoring as population demographic analysis, social determinants of health, and health status. Adjustments to risk stratification during and after the COVID-19 pandemic will inform the development of provider networks, provider payment models, and services. Taking into account new patterns of utilization across its member population, managed care programs may need to refine their risk adjustment models to determine the sickest and most costly of their populations to project costs and improve the delivery of services and coordination of care for Medicaid members.

Telehealth

As providers transition back to their traditional structures, MCOs can continue to expand telehealth to improve service delivery and to control costs. Part of this expansion will require MCOs to balance the mentioned benefits of the telehealth model with the risk of over-utilization of telehealth services that can lead to inefficiencies and increased managed care program costs. In addition, because of the loosening of federal restrictions on telehealth, managed care programs will most likely want to update program integrity safeguards to reduce the risk of fraud, waste, and abuse in areas such as provider credentialing, personal identifiable information (PII), privacy and security protocols, member consent, patient examinations, and remote prescriptions. 

Continued focus on data improvement and encounter data quality

Encounter data quality and data improvement initiatives will be critical to successfully administer a managed care program. As encounter data drives capitation rates for MCOs, a continued focus on encounter data quality will likely enable Medicaid programs to better leverage actuarial services to establish sound and adequate managed care program rates, better aligning financial incentives and payments to their MCOs. 

States have pursued a number of flexibilities to establish a short-term framework to support their managed care programs during the COVID-19 pandemic. However, the current expansion of services and the need for MCOs to rapidly identify additional areas for operational improvements during the pandemic have allowed Medicaid programs to further analyze longer-term needs of the populations they serve. These developments have also helped programs increase their range of services, to expand and manage their provider networks, and to mature their provider payment models. 

If you would like more information or have questions about opportunities for adjustments to your managed care program, please contact MedicaidConsulting@BerryDunn.com. We’re here to help.
 

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COVID-19 and opportunities to reboot managed care