Implementing Data Governance at Transportation Agencies: Volume 1: Implementation Guide (2024)
Chapter: 6 Tackling Common Challenges
6. Tackling Common Challenges
Overview
This chapter provides guidance on how to tackle some of the most common challenges that transportation agencies face in implementing data governance. These challenges are:
- Executive Support and Resourcing. Getting executive support and resourcing for data governance.
- Engagement. Getting engagement from governance group members and stewards.
- Change. Effecting meaningful changes in behaviors that are needed to improve data consistency, quality, usability, and protection.
- IT Coordination. Coordinating data and IT governance.
- Organizational Alignment. Aligning agency data silos.
- Staff Capacity. Making progress with limited staff capacity (time and skills).
- Sustaining Data Governance. Ensuring that established data governance structures and practices continue through staff transitions.
Note that many of these challenges are interrelated. Limited staff time and agency data silos are key reasons why effecting change is difficult. Getting executive support and getting governance group member engagement are both related to the difficulty of communicating what data governance is and why it is important to pay attention to. Lack of resourcing makes it difficult to tackle all of the other challenges.
Executive Support and Resourcing
The Challenge
There are pockets of interest in data governance at your agency, but the executive leadership team (Director and Deputy level) are not on board. They may lack a basic understanding of what data governance is and why it is important. They may be familiar with and supportive of data governance as a concept but do not have a clear picture of how it would help to address the agency’s priorities. They may feel that data governance is something within the IT group’s purview and therefore there is not a pressing need to set up anything new.
Even if the executives were bought in to data governance, they could face real constraints on adding new senior positions and committing to continuing resourcing of overhead-type activities. This might require legislative support or involve de-funding
other activities or re-purposing existing positions that are determined to be lower priority.
Ideas for Tackling this Challenge
Understand executive perspectives. Find out why there is a lack of executive support for data governance. Determine whether the lack of support is due to incomplete understanding of data governance, or whether it is more about connecting data governance to agency priorities. Identify other topics of current concern and seek ways of reflecting these in the data governance effort.
Make the case. Create a persuasive case for why investing in data governance should be prioritized. Make a connection to the agency’s strategic objectives. Include specific examples of current problems that would be alleviated through data governance and current initiatives that require data governance to succeed. Talk about the need to avoid inconsistent answers to questions by creating a single source of truth. Present the agency’s vision for making consistent, authoritative data available to meet internal needs and external reporting requirements – and how data governance is integral to this vision. Highlight decisions that could benefit from better data, and risks that could be mitigated. Point to the concept of data as an asset that requires deliberate management analogous to infrastructure assets. Provide examples from other states or organizations with mature programs that have demonstrated benefits.
See Chapter 6 of NCHRP Web-Only Document 419: Implementing Data Governance at Transportation Agencies, Volume 2: Communications Guide for further discussion of key points to make about data governance to executive audiences
Communicate effectively. Tailor your message to each executive to address what motivates them. Speak directly and clearly, avoid technical jargon, and keep your message simple. Do not expect them to have a deep understanding of the topic.
Communicate regularly about what you want them to do. Keeping the attention of executives can be challenging. They may respond positively to an initial discussion but then shift focus to other competing needs. Find opportunities to regularly remind them of why data governance is important and ask them to support it in specific ways, which may include things like expressing their endorsement, signing off on new policies, approving staffing and organizational changes, and helping to overcome pockets of resistance.
Conduct and share a data governance assessment. Assess your agency’s data governance maturity (see Chapter 3, Step 5) and share the results with the leadership team. Where possible, compare your agency’s maturity to peer agencies to highlight areas where you are behind others and the implications of this for broader agency performance.
Peer conversations. If one member of the executive team is on board with data governance, ask them to meet with the other members of the team and explain why they support it. Look for opportunities to set up conversations between your agency’s executives and those of other agencies that have established data governance.
Provide a concrete plan. Lay out a concrete plan for a first impactful but achievable data governance initiative including clear goals, anticipated products and results, timing, roles, and resourcing.
Seek interim resourcing solutions. If, even with executive support, it is not feasible to establish a senior level data governance lead, look for opportunities to add staff or dedicate an existing position at a lower level of the organization – at least on an interim basis. Consider jump starting an effort using consultant resources. Look for opportunities to use federal funding by focusing an initial data governance effort on data required for federal reporting or data linked to a federally funded planning or analysis activity.
Build grass roots support. Build a coalition of people (agency staff and staff from partner agencies) who are supportive of data governance and begin meeting to discuss common problem areas. Identify and pursue some practical initiatives that can be accomplished with existing resources. Document successes and prepare a presentation describing what was done and how a broader-based approach could scale up the benefits.
Engagement
The Challenge
You have designated members of governance bodies and identified data stewards but are having difficulty getting them to engage in data governance meetings and initiatives. Signs of a lack of engagement may include spotty attendance at data governance meetings, lack of participation at the meetings, and lack of responses to email requests.
Ideas for Tackling this Challenge
Formalize Expectations. Clearly define what governance body members and data stewards are expected to do. Create a RACI chart that identifies who is Responsible, Accountable, Consulted and Informed for decision making processes that involve data governance roles. Provide model duty statement language that can be used for data stewardship roles.
Example Messages to Data Stewards
Data stewardship is integral to your job – the agency is just improving how we support these activities.
We recognize that there are different maturity levels for data management across the agency. We are trying to even things up and make sure people have what they need to strengthen their practices.
Communicate. Create effective communication materials that focus on the “why” of data governance. Include stories that allow participants to understand the problems that you are trying to solve and see the activities you are pursuing will help. These materials should be tailored to the needs and programs of hesitant or distracted members.
Conduct early pilots. It may be difficult to create and sustain enthusiasm for background activities that are necessary to establish data governance but do not add immediate value. Identify a small pilot effort that can be used to demonstrate results. For example, create a data quality improvement plan for a dataset, or compile a list of useful data resources for distribution to the agency’s analysts.
Onboard your data stewards. Provide an onboarding session for each designated data steward. This can be done individually or in small groups. Use the session to communicate why data stewardship is important to the agency, and the responsibilities and expectations for a data steward. Provide specific examples of activities that they will
be asked to participate in within the next 3-6 months. Tell them about any resources that are available to help them. Allow time to talk about any questions or concerns that they may have.
See NCHRP Web-Only Document 419: Implementing Data Governance at Transportation Agencies, Volume 2: Communications Guide for further discussion of key messages to use in communicating with data governance participants
Meet with data governance body members. Meet with each member of your data governance body(ies) individually or in groups of two or three. Talk about why the agency is pursuing data governance, highlighting the perspectives of executive sponsors. Review any external mandates for your data governance initiatives. Clearly state why their engagement is needed to make the effort successful. Ask them to talk about how their part of the organization currently uses data. Use this information to probe about what kinds of improvements to data quality, consistency, and access would benefit them. Ask for their commitment to attend meetings or send an alternate. Ask them to provide feedback on how to make the meetings (and other activities) more productive and useful.
Recognize contributions. Provide positive feedback in response to contributions of data stewards and governing body members. This can take the form of public thanks at meetings or emails to managers expressing appreciation for the efforts of their staff.
See the discussion of Maximizing the Effectiveness of Data Governance Bodies in Chapter 4.
Consider changing group membership. If you have tried and failed to get a particular member engaged, it may be that they do not have sufficient time or interest to participate. Seek alternative members who can represent their functional areas.
Change
The Challenge
You have created one or more data governance directives or resources (e.g., policies, guidelines, processes, templates, standards). However, there is little evidence that they are being followed or used unless the data governance team is directly involved.
Change Management Stages
Many organizations follow the Prosci ADKAR® change management model which has the following stages:
- Awareness of the need to change
- Desire to change
- Knowledge of how to change
- Ability to change
- Reinforcement of the change
Ideas for Tackling this Challenge
Create change management plans. Consider creating and executing specific change management plans for each major data governance initiative that requires behavior changes across the organization. For best results, engage someone who has training and experience in organizational change management. A change management plan will identify the target population affected by the change, select, and engage individuals to serve as change agents, and develop appropriate communication, training, and support activities. An effective plan will help the target population understand what they are expected to do and why they are expected to do it and will directly address reasons why they may not have the desire or ability to change.
Allocate time for communication. Communicate widely and frequently. Find new and innovative ways to communicate about the data governance program to keep it in the minds of staff and leaders. Look to use new ways to communicate via short form videos, simple introductory training, coming to all staff meetings, and so on. Actively pursue
opportunities to get in front of groups to explain what, why, how, “what’s in it for me,” and then follow up.
Use your network. Engage your data governance body members and data stewards in rolling out each new directive or resource. Brief them, provide them with background information, and ask them to pass the information along to their colleagues. Most importantly, ask them to be on the lookout for situations where these new directives or resources can or should be applied and offer their advice or assistance to people who are able to implement them. Ask them to report any feedback to the data governance team that can be used to address barriers to effective implementation of the directives or resources.
See Chapter 2 of NCHRP Web-Only Document 419: Implementing Data Governance at Transportation Agencies, Volume 2: Communications Guide for further discussion of change management for data governance.
Track compliance. As part of change management planning, consider how compliance with new policies and procedures will be monitored. Recognize that when the agency sets new expectations for people, it is important to have a way to track that they are being met. Consider establishing an auditing process to check on compliance levels. This process can focus on identifying and addressing barriers to non-compliance, as opposed to penalizing people.
Embed data governance within existing processes. Wherever possible, embed data governance activities within already existing processes. For example, there may already be data intake processes for GIS or open data portals and data warehouses. These provide good checkpoints to require provision of metadata in standard formats and verify that adopted data quality management guidance has been followed. IT governance processes can be adjusted to include checks for potential data duplication and ensure adherence to established data element standards. Procurement approval processes can be tapped to provide review of data purchases or licenses using criteria established through data governance.
Provide support, training, and tools. Some changes may be difficult for staff to implement because they lack the necessary time, tools, or expertise. In the short term, you can tackle this issue by offering support, either from internal experts or external consultant resources. At the same time, work to build staff capabilities to adjust to new requirements through training, refinement of position descriptions, and implementation of tools that support and automate time consuming manual activities.
Simplify. In some situations, it may be necessary to revisit and refine the directive or resource to make it easier to implement. Ideally, each new directive or resource would be piloted prior to being finalized. Pilots provide an opportunity to understand the time and skills required for implementation, test assumptions that were made, and make any needed revisions.
IT Coordination
The Challenge
Your data governance team recognizes the importance of working in partnership with IT and IT representatives participate in data governance groups. However, you are
encountering problems getting strong coordination with IT because (1) you have different chains of command – and perhaps your IT function is centralized at the state level, (2) data governance and IT have different priorities – and limited staff resources, (3) IT managers feel that data governance is encroaching on what has historically been their turf, and/or (4) IT governance processes are difficult to change (to align with data governance needs) because they are tied to state requirements.
Data and IT Governance Points of Coordination
Strategic planning
IT project lifecycle milestones (initiation, requirements, design, development, production)
Data warehouse planning, design, and development
Purchase and deployment of data modeling, metadata management or data quality solution
Creation of Enterprise Architecture (EA) artifacts such as business capability models, enterprise process maps, reference models, standards and investment roadmaps.
Purchase or licensing new data products
Execution of data sharing agreements
This challenge arises because data and IT are intertwined. In most DOTs, IT has responsibility for creating, acquiring, and managing the systems that house the agency’s data. They also typically manage technologies and processes for making agency data available for reporting and analytics – and for supporting metadata and data quality management. Because of this, some agencies choose to locate data governance within the IT function. Others choose to separate data governance from IT to encourage close alignment with business units and establish a discipline of managing data as an asset - independent of information systems. In these situations, new system-independent activities led by the data governance team need to be brought into alignment with similar or related activities led by IT as part of system development and management.
Ideas for Tackling this Challenge
Build relationships. Include IT representatives on all data governance bodies. Maintain open lines of communication and build close working relationships between the two groups – at management and staff levels. This will help both groups to stay informed about each other’s activities and opportunities for productive collaboration.
Clarify roles and responsibilities. Recognize that existing IT roles and responsibilities will need to be adjusted or at a minimum clarified when data governance is introduced into the agency. Clarify responsibilities by creating a RACI chart (or similar tool). Refine this chart over time as new situations arise that create tensions or confusion about roles.
Emphasize maximizing staff resources. Discuss how IT and data governance can work together to maximize the collective staff capabilities of the agency. Clarify how to empower business side data analysts to create and maintain data assets (such as dashboards) while minimizing risks by ensuring adherence to established documentation, licensing, and data storage protocols.
Synchronize processes. Work with IT partners to create or revise process flow diagrams that indicate touch points between data and IT governance for key processes. See the sidebar for examples.
Involve executives. Ask the executive sponsor(s) for data governance to facilitate coordination between data governance and IT and resolve specific turf issues that may arise. This is particularly important when data governance and IT report up to different members of the executive team.
Coordinate on strategic planning and budgeting. Be proactive about aligning data governance and IT activities by coordinating on strategic planning, budgeting, and work planning. Use the IT strategic planning process to engage in a discussion of key points of
collaboration and coordination, and make sure data governance is covered within the plan. Similarly, engage IT leaders in data governance strategy and planning activities to discuss areas where collaboration will occur.
Organizational Alignment
The Challenge
Various data-centric programs in the DOT – such as GIS, performance reporting, traffic monitoring, crash records and highway inventory/HPMS have some data governance processes in place, but they are not consistent. It would be beneficial to standardize data intake, metadata, and data quality processes, tools, templates, and related training materials across these programs. However, representatives of these programs are satisfied with their existing procedures and feel this would be disruptive – or low priority at best.
Ideas for Tackling this Challenge
Clarify roles and responsibilities. The agency data governance team can make it clear that their purpose is not to usurp existing responsibilities for making decisions about how individual data programs operate. However, they do need to get engaged when decisions have cross-business unit impacts. It can be helpful to create a RACI chart (like the approach noted above for IT coordination) that calls out situations where the data program lead should be consulting with or providing information to the data governance team – and vice-versa. As part of this activity, clearly communicate (and adjust as needed) what data is in scope of the data governance program.
See Chapter 7 for a sample RACI chart.
Modify business processes. It may be necessary to establish new or modified business processes to ensure alignment. Specific candidate business processes to review include:
- IT project intake processes
- Data-related procurement processes (products and services) – including consulting and research project contracts that will involve data collection or production
- Data publication processes
- Data change processes
- Employee onboarding and offboarding processes
- Database application development processes
Collaborate on planning and budgeting efforts. Identify opportunities for collaboration on strategic planning and annual budgeting exercises to build relationships, identify common goals and meet common needs. One example of this is coordinating GIS and IT investment needs identification.
Engage data program representatives. Involve representatives of key data programs (e.g., crash data, traffic data, asset management) within your data governance bodies early on and keep lines of communication open. Begin by understanding what they are doing and listening to their ideas for areas where more consistency across agency data
silos would be helpful. Find opportunities to pursue initiatives that will benefit their individual programs and other parts of the agency as well. For example, introducing new data profiling tools and offering training could provide a welcome opportunity to improve the efficiency of existing data validation procedures across multiple units.
Take advantage of existing resources. Review existing processes and resources that current data programs have created (for example, metadata repositories, data intake forms, checklists, etc.) and look for opportunities to adapt and adopt them for agency-wide use.
Pick your battles. Keep in mind that your goal is to manage risk and add business value – not necessarily to achieve full agency-wide consistency. Focus on helping to fill the major gaps such as datasets lacking any stewardship or documentation or multiple inconsistent sources for the same key reporting data element. These will have greater payoff than efforts to achieve compliance with standards for data programs that are already being well-managed.
Staff Capacity
The Challenge
Staff capacity limitations are holding back progress in building greater maturity in managing, governing, and using data. Many of the designated data stewards do not have the time or skills needed to perform data documentation, classification, or data quality management tasks. Data users lack the basic data literacy skills needed to understand how to find and access data and understand its suitability or relevance. It is difficult to find analysts with the skills needed to manipulate, critically assess, and draw valid conclusions from data.
Knowledge, Skills and Abilities for a Data Steward
In-depth knowledge of one or more data systems
Knowledge of data standards
Understanding of database design principles
Understanding of private and senstive data classification and protection
Understanding of data interoperability challenges and solutions
Ability to create and maintain metadata
Ability to create and maintain business rules
Ability to recognize and diagnose data quality issues
Ability to develop data retention schedules
Ability to identify and advocate for data quality and usability improvements
Ability to effectively communicate technical information
Ability to engage with data users to understand their needs
Ideas for Tackling this Challenge
Spell out data steward skills and responsibilities. Create standard language defining the skills and responsibilities expected of individuals serving as data stewards. If feasible, include this language in position descriptions or duty statements.
Secure time commitments. Meet with key business area managers who are the largest data producers in the agency, and other supervisors of data stewards. Discuss the goals of data governance and set expectations for how much time will be needed on a regular basis as well as for upcoming major initiatives. Explain the importance of data stewardship activities and how they will benefit the steward’s organizational unit. Make the case for busy staff to allocate more of their time to fulfill data stewardship responsibilities. Take any specific concerns back to your governing bodies to discuss ways to address time constraints. If this activity will be conducted by multiple individuals (e.g. coordinating data stewards), the data governance team can create some standard talking points to be used for these conversations.
Maximize efficiency. Seek ways to automate or centralize data governance tasks to reduce staff burdens and make the best use of available staff capacity:
- Provide tools and templates for metadata creation, business rule management and data quality management.
- Investigate use of rapidly maturing artificial intelligence tools to automate data documentation, mapping, lineage tracing and audit functions.
- Offer services of a trained agency staff or consultant resource to perform tasks requiring specialized skills.
Provide support resources. Engage external consultants or student interns to support data stewardship and management activities. Consider creating a data Center of Excellence (CoE) on a temporary or permanent basis to serve as a central resource for expertise and support. The CoE could consist of a group of agency staff with data related expertise who devote part of their time, as well as new hires and (as needed), external consultants.
Training. Define the skills needed for different data roles or personas (steward, analyst, user, manager) and offer training to meet these skills. Training can help people understand the different data governance practices and why they matter. Because it takes significant effort to develop custom training, take advantage of available commercial and academic institution courses as well as courses that have been created by peer agencies. Focus internally developed training to help employees understand the basics of data governance at your agency – what is it, why it is important, how it is being implemented and what resources are available.
Sustaining Data Governance
The Challenge
Increasing frequency of staff transitions (retirements, transfers, job changes) makes it difficult to sustain data governance activities. Departure of a data governance lead can lead to stalled efforts for long periods of time. Departure of others within the data governance team can disrupt planned activities that no longer have the staff support needed to carry them out. Turnover of data stewards and members of data governance bodies creates the need for continual orientation and education activities. Changes in agency leadership can also be disruptive – jeopardizing support for data governance or necessitating changes in direction.
Ideas for Tackling this Challenge
Anticipate turnover. Make a deliberate plan for staff turnover; do not be surprised when it occurs. Consider what can be done to smooth transitions when they occur and minimize having a single point of failure for the data governance program. Most importantly, have a succession plan for the data governance lead; actively engage the number two person in the lead’s activities to take over if needed (at least on an interim basis). While it is not always possible in a government setting to implement anticipatory hiring in advance of the departure of key personnel, strategic cross-training and
succession planning can reduce the negative impact when those in critical positions leave.
Contents of Shared Data Governance Team Files
Most recent strategic plans, roadmaps, and work plans Finalized policy, procedure, guidance and standards documents
Training materials
Reference list
Data governance body membership list
Contact lists
Contact logs
Issues logs
Chronology of data governance milestones
Presentations and other communications materials
Notes on lessons learned
Technical documentation for data governance tools or systems
Job aids for data governance team members
Working documents
Maintain complete and well-organized files. Make sure that the data governance team maintains a well-organized repository of documentation that a new person can use to get up to speed.
Implement data governance and management tools. Implement tools for maintaining data catalogs, metadata management, data quality management and managing workflows for governance processes such as data publication can help to institutionalize data governance practices so that they remain stable through staff transitions.
Establish priority documentation standards. Put requirements and processes in place for documenting data assets - with a tiered structure defining minimum standards as well as additional documentation to produce based on criteria such as publication method/location, level of complexity, and stability. Minimum documentation might include a description of the data asset suitable for inclusion in a data catalog; a process diagram showing how data are collected, processed, stored, and delivered; and/or a high-level data context diagram indicating major sources and uses for each system/data set. This would allow that new staff taking on data responsibilities to quickly familiarize themselves with the agency’s data assets. A tiered approach to documentation recognizes that producing documentation and keeping it up to date is time-consuming and not always feasible.
Communicate importance of knowledge transfer. Educate both managers and staff about the importance of knowledge transfer – through both documentation and ongoing collaboration activities. Make the point that if knowledge transfer is not done, the employees’ successors will face a long learning curve and may be unable to explain the source, derivation, and meaning of the data they have inherited to others.
Establish onboarding materials and processes. Create re-usable onboarding materials for data governance team members and data stewards. Train several different individuals on delivery of these materials. Establish regular schedules for onboarding – for example, quarterly webinars for new data stewards.
Other Challenges
Agencies may face a variety of other challenges – see Table 6 below for some examples and ideas for tackling them.
Table 6. Tackling Other Data Governance Challenges
| Challenge | How to Address this Challenge |
|---|---|
| There was a prior failed data governance effort and people are reluctant to try again. | Collect information on what went wrong by talking to several different people who were involved. Perhaps the timing was wrong. Create communications materials that address the prior failed effort head on. Articulate what was learned and what can be done differently to be successful. |
| Challenge | How to Address this Challenge |
|---|---|
| Our data governance lead is under our Planning Division. We are pursuing an agency-wide scope, but it is difficult to get engagement from employees in other divisions. They don’t see this as an enterprise effort. | Place the data governance program as high up in the organizational structure as possible. Have the data lead physically sit in the executive office area. Have the highest-level executives in the DOT make it clear that the program is enterprise in nature to staff. Market it as an enterprise effort. |
| We don’t have any dedicated staff for data governance. | Start a grass roots effort - identify volunteers to become champions. Pick a small improvement to work on together that can be used as a model and build support for dedicating staff resources for data governance. |
| It is difficult to get support in my agency for establishing any formal data governance policies or processes. | Be clear about the goals of a new policy or process. Consider ways to make progress without formalizing the policy – for example, by conducting training or outreach to educate staff on best practices. |
| We would like to collect a new type of data to help with our safety analysis but are unable to identify a business unit willing to take on management or stewardship of the data. | Establish a clear policy that the agency won’t fund new data collection, provide IT support for data hosting or managing server space, or include data in official reports unless there is a steward in place. Work through data governance bodies to identify training and recruitment strategies to build agency capacity for data stewardship. |
| Many business units are turning to off-the-shelf, hosted solutions where the data aren’t housed within the DOT. It seems impossible or impractical to establish new standards across these different areas. | Work through your data governance groups to identify a list of non-negotiable items for new systems. Develop standard language reflecting these items within Requests for Proposals (RFPs) and vendor agreements. These may include adherence to agency data standards, pulling input data from authoritative sources, provision of metadata, ability to integrate all or a portion of the data within the agency’s data warehouse, and use of standard data query and reporting services. For off-the-shelf systems with inflexible data structures, explore creating materialized views that present data in a manner that is consistent with other agency data. Create an exception process to handle situations where vendors are not able to comply and there are no alternatives to their product. |
Using Peer Experience to Gain Support for Data Governance
One DOT had tried to implement grass roots data governance efforts on four occasions but had failed each time to gain the support of upper management. Each effort died as soon as the data governance task became resource intensive because it was never a part of anyone’s job description or assigned responsibilities.
The agency executives wanted data governance, but at zero net cost. They needed to be convinced that the savings at least covered the proposed increases in staff time and effort.
Without a way to prove the value of data governance, each attempt was doomed for lack of resource allocation no matter how much the stafflevel personnel believed it would work.
A solution based on peer agencies’ experiences assured the agency’s leadership that they could plan for both the expense of data governance and the savings that would come from better data and more effective decisions.
| Challenge | How to Address this Challenge |
|---|---|
| It is difficult to get an understanding of the business uses and value of our existing data | Enlist the help of your data stewards to provide information on how the data within their areas of responsibility are used. Record this information in your data catalog. Create business process models for key processes and extend these by indicating what data are produced and consumed. Track data usage patterns using logging and auditing features of database management systems, cloud platforms, and data catalog tools. |
Summary
Common challenges that agencies face when Introducing data governance are getting support and engagement from leaders, managers, and staff; aligning priorities and processes with IT and other data-related teams; achieving meaningful changes in behavior; and sustaining efforts through turnover in staff. These challenges can be tackled through a combination of being clear about objectives (the “why” of data governance), effective and frequent communication; use of change management methods; adaptability; collaboration; creativity; and persistence.
