Grants Demographic and Geographic Data Project Report
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- 2023 Commerce Reports Grants Demo Report Final 0Be78Fbc 192E 40Df B584 A39A
Summary
The Grants Demographic and Geographic Data Project Report, dated June 2023, prepared by Kinetic West LLC for the Washington State Department of Commerce. The project was funded in Sect. 128(216) of Chapter 297, Laws of 2022, to report on how Commerce will collect demographic and geographic information from organizations receiving its grants, with cost and time estimates. The report finds Commerce data practices decentralized, with a single data manager position, while the agency disburses more than $2 billion per year through more than 100 programs. It recommends standardized collection on grantees and beneficiaries, centralized data governance and use of the Contract Management System, at about $2.3 million in one-time costs and $2.1 million per year ongoing. Appendix tables estimate staff hours and costs, including $450,521 for headquarters and IT and $1,187,500 for program staff.
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Kinetic West
Grants Demographic
and Geographic Data
Project Report
June 2023
1
Acknowledgments
Washington State Department of Commerce
Anna Batie Kuka, IT Data Management Coordinator – Project team member
Kyle Gitchell, Managing Director of Equity and Belonging – Project team member
Elizabeth Saylor, Interim Chief Information Officer – Project team member
Martin McMurry, Former Chief Operations Officer (no longer at Commerce) – Executive sponsor
Marissa Joy VanHoozer, Chief Equity and Operations Officer – Executive sponsor
1011 Plum St. SE
P.O. Box 42525
Olympia, WA 98504-2525
www.commerce.wa.gov
For people with disabilities, this report is available on request in other formats. To submit a request, please call
360-725-4000 (TTY 360-586-0772)
Kinetic West LLC
Marc Casale, CEO and founder – Project advisor
Merilee Teylan, Senior Consultant – Project team member
Casey White, Consulting Manager – Project team member
2
Executive summary ...........................................................................................................................................................................4
Introduction ......................................................................................................................................................................................6
Findings .............................................................................................................................................................................................9
Recommendations .......................................................................................................................................................................... 15
Appendices ...................................................................................................................................................................................... 21
3
Executive summary
The Grants Demographic and Geographic Data Project was By standardizing demographic and
funded by the Washington State Legislature in Sect. 128(216) of geographic data collection among
Chapter 297, Laws of 2022 (the 2022 supplemental operating programs, Commerce will be able to:
budget). The project’s primary goal is to report on how the • Report on impact at the agency-level
Department of Commerce will collect demographic and • Analyze data to identify opportunities
geographic information from organizations that receive direct or • Direct investments equitably
indirect grants from the agency, including estimation of cost and • Collaborate more effectively with other
time to implement changes to allow for complete, aligned data Washington agencies
tracking. In late 2022, Commerce contracted with Kinetic West
to undertake this work. The project team consisted of Kinetic West consulting staff and key members of Commerce’s
Equity and Operations Division. The project was sponsored by Commerce’s Chief Equity and Operations Officer.
Commerce strengthens communities in Washington through the disbursement of more than $2 billion per year in
grants, contracts, and loans via more than 100 programs in areas such as climate, public facilities, housing, and public
safety. The agency has grown rapidly in recent years, from about 300 employees in 2018 to more than 550 in 2023,1 and
in 2022 more than doubled the total number of grants distributed compared to 2015 (Figure 2). While Commerce
programming has expanded significantly, capacity for data governance has been limited to a single position attempting
to meet the needs of an entire agency, and as a result, data practices (e.g., decisions about what data to collect, how to
collect data, where and when to report data) are decentralized with little agency-wide coordination.
We recommend funding Commerce to standardize and improve demographic and geographic data collection to build
a more comprehensive understanding of how Commerce resources are driving greater equity throughout
Washington. Implementation will require about $2.3 million in one-time costs and $2.1 million per year on an ongoing
basis. This investment will provide Commerce and its stakeholders with data of critical importance. Commerce will be
able to report on impact at the agency level, analyze data to identify opportunities and direct investments equitably, and
collaborate more effectively with other Washington agencies. This effort aligns with Commerce’s long-term vision to
lead as a champion of best practices for demographic and geographic data collection to achieve equitable outcomes for
all people in Washington and is part of a growing movement in Washington to use data to advance equity.
Key findings of this project Recommendations for a path forward
Within Commerce, current data practices are decentralized
and fragmented. At the same time, the value and impact of
Commerce should move forward with enhancing
standardized data collection practices is widely
demographic and geographic data collection through
understood.
strategies that are possible today, which are rooted in an
While there is no standard practice for demographic data
understanding of the current systems and processes at
collection among Washington agencies that we
Commerce.
interviewed, there are common (but imperfect) practices
to build on.
To truly be able to tell the story of who is benefiting from All programs should collect standardized demographic and
Commerce funding, programs should not be allowed to opt geographic data on grantees. Programs that provide
out of data collection. grants, contracts, or loans and provide direct services to
1 See Office of Financial Management Washington Workforce Metrics Dashboard
4
beneficiaries should be required to collect standardized
demographic and geographic data on beneficiaries.
Investment in both internal and external change
management to ensure successful implementation.
Commerce should collaborate with its grantees and
program beneficiaries to solidify implementation plans.
Commerce staff and grantees/subgrantees will need a
Engaging directly with communities on this data collection
range of supports to implement new data practices.
effort can help Commerce incorporate community
perspectives, get buy-in that will lead to higher quality
data, and ensure the effort benefits (and does not harm)
communities.
Invest in capacity for centralized data governance,
More centralized capacity is needed within Commerce to including capacity to clean, analyze, and visualize data for
support a robust data culture. use by Commerce, legislative, and community
stakeholders.
Modify Commerce’s Contract Management System (CMS)
Commerce needs a single repository to collect and store
to serve as a repository for this data effort. Nearly all
standardized demographic and geographic data.
Commerce programs are already using the system.
Recommendations
Commerce's demographic and geographic data collection should be enhanced and standardized to build a more
comprehensive understanding of how Commerce resources are driving greater equity throughout Washington. To
achieve this, we recommend:
• Adopting a project roll out approach that includes three stages: 1) planning, 2) development, and 3)
implementation. Key activities within these stages are depicted below.
Planning Development Implementation
Internal and external stakeholder engagement
Change management
Technology modifications
Staff training and implementation
Grantee training and implementation
Additionally, we recommend launching implementation with a learning-oriented pilot by infusing new data
requirements into all new grants going forward, as well as revising a subset of existing grant agreements. Lessons
learned from this pilot can inform implementation at scale.
• Allocating about $2.3 million in one-time costs and $2.1 million per year on an ongoing basis to plan, develop, and
implement collection and analysis of standardized demographic and geographic data. Investment in enhancing
technology comprises the largest share of one-time costs, and staff capacity (both IT and program) to implement
new practices comprises the largest share of ongoing costs.
5
Introduction
Purpose
The project’s primary goal is to report on how the Department of Commerce
will collect demographic and geographic information from organizations who • Community Services
receive direct or indirect grants from the agency, including estimation of cost • Housing
and time to implement changes. This effort is an exciting and valuable step for • Energy
Commerce programming, as it brings the agency closer to a nuanced • Local Government
understanding of its own work and who benefits, or does not, from its • Office of Economic
programs. Development and
Competitiveness
With access to detailed demographic and geographic data, collected in a
uniform manner across the agency, Commerce can better tailor its resources,
Figure 1. Department of
programs, and grants to ensure it is truly reaching all people who live in
Commerce’s programmatic
Washington, particularly those in highest need. Higher quality, more
divisions
accessible demographic and geographic data will also help Commerce
communicate and partner with communities, as well as effectively collaborate with the Legislature and other state
agencies using data driven analysis. Commerce will be able to better track the impact of its spending, and work with the
Legislature to ensure that the legislative intent of specific programs is met. Commerce will be able to work more easily
cross-departmentally with shared data and outcomes, and with other state agencies tracking similar information.
Further, as Commerce’s data collection and tracking practices become unified with those of other agencies, it will be
possible to draw a more accurate picture of the state’s overall impact on the lives of Washington residents. Finally,
greater demographic and geographic data collection allows for greater transparency on taxpayer spending, increasing
confidence in the work of the agency and the work of the state government, and can drive more equitable distribution
of resources.
Commerce history and context
Commerce strengthens communities in Washington through
5000 the disbursement of more than $2 billion per year in grants,
Total Grants
New Grants contracts, and loans. The agency is comprised of five
4000
programmatic divisions (Figure 1), which house
approximately 120 programs (as of 2023) in areas such as
3000
climate, public facilities, housing, and public safety. The
2000 agency has grown rapidly in recent years, from about 300
employees in 2018 to more than 550 in 2023.2 In 2022, the
1000 agency more than doubled the total number of grants
distributed compared to 2015 (Figure 2). There was
0 moderate, steady growth in the number of grants from
2015 2016 2017 2018 2019 2020 2021 2022
2015 to 2018, and in more recent years, that growth has
accelerated, partially due to the role Commerce played in
Figure 2. Grants per fiscal year
2 See Office of Financial Management Washington Workforce Metrics Dashboard
6
distributing vital funds during the early years of the COVID-19 pandemic.
In addition to the wide breadth of its programs, Commerce has historically been responsive to the needs of the state,
often overseeing the distribution of funds through programs that do not fall neatly within other state agencies’ purview.
As Commerce has risen to meet the needs of the state, it has not had the resources necessary to implement
standardized demographic and geographic data collection practices across its programs, limiting the ability to measure
and report on impact. Currently, Commerce has one data manager to support the agency’s extremely diverse data
footprint, and data stewardship has not been operationalized beyond the data manager role. Commerce has not
resourced central services like information technology (IT), communications, or data analytics in the same way as it has
resourced programs with the expansion. As a result, data governance practices are at the program level, not the agency
level, and data practices vary widely across programs and divisions.
Project approach
The scope of this project is centered
on understanding demographic and Phase 1 Listening sessions with key internal
geographic data collection within Establishing fact base and and external stakeholders
Commerce and finding alignment identifying key data elements
with both One Washington and the Best practice research
Washington State Office of Equity.
Knowing that Commerce is not alone Phase 2 Project kick-off meetings with
in exploring demographic and Information gathering with Commerce managing directors and
Commerce programs program staff
geographic data standardization, our
approach was to explore efforts
Surveying Commerce Program staff
across the state, federal efforts, and
efforts in philanthropy to inform our Phase 3 Interviews with identified Commerce
recommendations broadly. Cost-structure planning and program and key staff
analysis
Phase 1: Establishing fact base and
identifying key demographics Figure 3. Phased project approach allowed for broad and deep learnings from
Listening sessions with key internal stakeholders
and external stakeholders
The goal of the listening sessions with internal stakeholders was to establish an understanding of the history, current
state, and future goals of demographic and geographic data collection within the agency. For external stakeholders, we
aimed to learn what demographic and geographic data standards exist in other state agencies (including the Office of
Financial Management, Department of Enterprise Services, and the Department of Health), and if there are existing or
planned efforts to modernize and/or standardize demographic and geographic data collection within or across state
agencies. A total of 12 listening sessions were conducted, including engaging with One Washington and the Office of
Equity. See Table A1 for a full list of the listening session participants and the specific goals for each engagement.
Best practice research
With the goal of data collection standardization within the agency and alignment with other state agencies, we looked at
how demographic data on workforce is currently reported by other agencies, including the Executive Branch Workforce
Demographics, Executive Branch Minority Contracting Spending, and Office of Financial Management’s Human Resource
Management System (HRMS) data dashboard.
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Knowing that some Commerce programs leverage federal funds, we reviewed federal reporting standards for
demographic data elements. We paid particular attention to the review and revision of standards for maintaining,
collecting, and presenting data on race and ethnicity led by the U.S. Office of Management and Budget (OMB). OMB’s
initial proposal was released in late January 2023, which was well-timed with this project.
We also examined demographic and geographic data reporting as a means of measuring accountability and impact of
dollars spent among philanthropic organizations. When reviewing these practices, we explored a wide range of practices
in private philanthropy and differences between the public and philanthropic sectors. Organizations that we explored
included the Hewlett Foundation, the Packard Foundation, and the MacArthur Foundation.
Phase 2: Understanding the current data landscape at Commerce
Project kick-off meetings with Commerce managing directors and program staff
Successful implementation will require buy-in across the agency. Staff at all levels must understand and support the
goals behind changing data collection methods and see how better demographic and geographic data collection can
benefit their programs and their work. To build that buy-in, Commerce’s managing directors and program staff were
invited to attend a project kick-off meeting to hear directly from the combined project team of Commerce and Kinetic
West about the purpose and goals of the project, and how Commerce staff would be engaged in the process. The
meeting was repeated on three separate dates during a week in January 2023 to maximize attendance during the busy
legislative session. The meeting was also recorded and made available those who could not join in real time. More than
70 people attended across the three meetings, including a solid cross-sample of staff. Each meeting included robust
question and answer session and discussion with the attendees.
Survey Commerce program staff
Informed by the Phase 1 and what we heard directly from staff at the kick-off meetings, a survey was distributed to
Commerce managing directors and program staff. The survey aimed to give us a detailed understanding of the current
state of demographic and geographic data collection across Commerce programs, what influences current practices, and
what resources and capacity would it take to establish and operationalize standard practices across the agency.
When asking about current demographic and geographic data collection, we wanted to understand if programs collect
data at three distinct levels of who receives and/or benefits from Commerce funding. These levels are:
1. Grantees/Subgrantees: Those who receive direct funds from Commerce; some refer to this group as contractors or
subcontractors.
2. Workforce: Those who are paid to execute the work funded by Commerce.
3. Beneficiaries: Those who benefit from the work done and funded by Commerce.
Phase 3: Estimating what it will take to update data practices at Commerce
Interviews with identified Commerce programs and key staff
The survey in Phase 2 provided a foundation for the development of an activity-based cost model to estimate the
resources needed to align data collection practices across the agency. To build on insights from the survey, interviews
were conducted with key Commerce staff to help inform the design of the cost analysis and recommendations. See
Table A2 for the list of interviewees and the goals of each engagement.
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Findings
Within Commerce, current data practices are decentralized and fragmented. At the same time, the value
and impact of standardized data collection practices is widely
understood. Among Commerce
Commerce has a long-term vision to be a leader in championing best practices for programs that provide
demographic and geographic data collection to achieve equitable outcomes for grants, contracts, or loans:
people living in Washington. The current decentralization of data storage and
reporting makes it difficult to answering questions such as: “Who is being funded
70% of demographic
collect some type
by Commerce?” and “Who is benefiting from Commerce funding?” Among those
we spoke with, there is widespread understanding and support for standardized data
data collection to tell the story of how Commerce is impacting the state.
94%
collect some type
During our listening sessions with Commerce stakeholders, we heard that some of geographic data
programs are already collecting some types of demographic and/or geographic
data, and the reason for capturing this data is often reporting required by federal or
86%
are influenced by
state funding sources. This was confirmed by our survey of Commerce’s program state or federal
staff. Survey responses represented 111 programs at Commerce. One-hundred and funder reporting
five of the 111 programs that provide grants, contracts, or loans reported that they requirements
collect demographic or geographic data. Of programs that provide grants,
contracts, or loans, 70% collect some demographic data. Most demographic data was collected on beneficiaries,
followed by grantees/subgrantees. Very few programs collected demographic data on workforce. Gender and race or
ethnicity were the demographic categories most frequently captured by programs across all levels. Sexual orientation
and gender identity beyond male or female (e.g. transgender, non-binary, gender non-conforming, etc.) were the least
collected demographic categories across all levels. Eighty-six percent of programs collecting demographic data had data
practices driven by funding reporting requirements, specifically state and federal funding sources. Ninety-four percent
of responding programs collect some geographic data, most often on the physical location of grantees/subgrantees.
County was the most common level of geographic data collected for grantees/subgrantees and for beneficiaries.
While there is no standard practice for demographic data collection among Washington agencies that we
interviewed, there are common (but imperfect) practices.
The Office of Equity is another key stakeholder identified for this work. One of the Office of Equity’s charges is to provide
standards for the collection, analysis, and reporting of population-specific data to track population level outcomes for
communities. Working closely with the Office of Equity is integral to successful implementation of any data
standardization at Commerce. Initial conversation with the Office of Equity elicited connections to other state agencies,
including the Department of Enterprise Services, Department of Health, State Human Resources via the Office of
Financial Management, and the ethnic commissions. Through these conversations and research on demographic data
reported by a sample of state agencies, we aimed to draw an understanding of what is considered standard practice
across the enterprise.
At the grantee or contractor level, Commerce and other state agencies have relied on state certifications to identify
businesses by demographic disaggregation, such as:
• Minority Business Enterprise (MBE) – owned by minorities
• Women’s Business Enterprise (WBE) – owned by women
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• Minority Women Business Enterprise (MWBE) – owned by minority women
• Combination Business Enterprise (CBE) – owned by women and minorities
• Socially and Economically Disadvantaged Business Enterprise (SEDB) – owned by non-minority men who are found
to be socially and economically disadvantaged on a case-by-case basis.
• Veteran-Owned Business (VOB)
At the individual level, such as workforce or beneficiaries, there is some consensus on demographic data elements when
reporting on disability status, veteran status, and identification as a member of the lesbian, gay, bisexual, transgender,
queer or questioning, and more (LGBTQ+) community; however, this is true because these demographics are often
collected and reported dichotomously (such as with/without a disability, veteran/not a veteran, etc.). In some cases,
dichotomous data is completely sufficient. However, in some cases, dichotomous data loses subtle but important
differences when thinking about the diversity of communities, both in identity markers and in their needs to thrive.
Gender identity and race/ethnicity have more variability in how data is reported, which is not surprising since the ways
in which we speak about these demographic categories have changed rapidly. These findings hold true when examining
data collection and reporting practices among philanthropic organizations.
Combined with what we learned from internal stakeholders at Commerce, there are two forces that should be
considered and balanced when thinking about standardized demographic data collection and the key data elements that
should be captured. The first is moving beyond the binary and outdated demographic categories, which we heard clearly
from the Office of Equity. The other is understanding the broader context that Commerce programs and the grantees
work within, and the existing reporting requirements that are tied to state and federal funding. Table A3 shows
examples of what demographic data collection can look like if anchored by both ends of this spectrum. This is made
even more complex when considering future changes that may be in place, such as the revisions proposed to capture
race and ethnicity by the U.S. Office of Management and Budget.
Key finding Recommendation for a path forward
Commerce should enhance demographic and
geographic data collection through strategies that are
possible today and are rooted in an understanding of
Within Commerce, current data practices are the current systems and processes at Commerce. This
decentralized and fragmented. At the same time, the is a recognition of the fundamental role that
value and impact of standardized data collection Commerce plays in strengthening communities, as
practices is widely understood. well as the importance of building a more
comprehensive understanding of how Commerce
resources are driving greater equity throughout the
state.
To truly tell the story of who is benefiting from Commerce funding, programs should not be allowed to
opt-out of data collection.
However, there should be parameters that clearly identify if a program is exempt from any or all data collection, or if
there are other data sources that could supplement data collection efforts in order to reduce burden. Figure 5 illustrates
a decision tree that could clarify if a program is exempt from collecting data from grantees regarding program
beneficiaries.
10
Additionally, we recommend that Commerce consider collection of standardized demographic and geographic data on the
grantee workforce (those paid to execute the work funded by Commerce) in a later phase of the implementation. Fewer
than one in five programs currently collect demographic data on workforce, and no programs reported collecting
geographic data. We believe that this data will be valuable to Commerce in understanding equitable flow of resources,
but more conversation with grantees is needed to understand the promises and the challenges of this approach.
Figure 5. Mapping exemptions to beneficiary data collection
Start
Does your program Program
No
Exempt provide grants, collects data
contracts, or loans? on grantees
Yes
Can beneficiaries be Does your program
No No
extrapolated from the provide direct services to
regions served? beneficiaries?
Diagram Key
Yes Yes
Decision
Primary data collection by grantee Beneficiary data Grantee collects data on
extrapolated based on beneficiaries and reports
Primary data collection by Commerce
region served to Program
Key finding Recommendation for a path forward
Programs that provide grants, contracts, or loans and
provide direct services to beneficiaries should be
To truly be able to tell the story of who is benefiting required to collect standardized demographic and
from Commerce funding, programs should not be geographic data on beneficiaries. Without this
allowed to opt out of data collection. requirement, Commerce will not be able to
understand its full reach and impact or identify
opportunities to invest equitably.
Commerce staff and grantees/subgrantees will need a range of supports to implement new data
practices.
Commerce staff will need training and support on new data practices and reporting requirements.
Staff were asked to provide their thoughts on what would be needed for their programs to successfully adopt new data
practices. Of the respondents representing programs who provide grants, contracts or loans, 72% indicated that some
training would be required. When asked to specify what kind of training, respondents indicated that training was
required across the gamut, including training on new policies and procedures, data collection practices, data quality
assurance, visualization, reporting, privacy, storage, security, sharing, and ethical data practices. Beyond the technical
aspects of adopting new data practices, there is a need for general training around diversity, equity, inclusion, and
cultural competency.
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In surveys and interviews, Commerce staff highlighted the importance of hearing directly from grantees and subgrantees
about their needs. Given Commerce’s more than 2,500 contracts per year, it is not surprising that grantees vary widely
in their capacity to implement new data collection and reporting practices. In our survey, we asked Commerce staff to
estimate the effort needed for their grantees/subgrantees to adopt new technology to update their data collection
practices. One in three said they are unable to estimate.
New data practices and reporting requirements will create additional work for grantees.
Commerce staff highlighted concerns about the burden added by standardized data collection, specifically for grantees
who receive funding from Commerce. Some of those grantees are small non-profit organizations or municipalities who
might already struggle to meet contracting requirements based on their capacity. In those instances, we heard that
additional contracting requirements should not result in grantees having to choose between using their staff to provide
services to the community or to meet Commerce’s contract agreement.
Generally, any staff hesitation or resistance that surfaced is anchored in concern for the communities that Commerce
hopes to support. Questions that we have heard from key program staff include:
• How do you balance reporting actual numbers while protecting vulnerable populations?
• How do you ensure that you are not inadvertently identifying vulnerable individuals in the data?
• How do we ensure this effort, which is intended to benefit the community, doesn’t burden or cause harm?
• How are community voices intentionally and authentically included in this process?
In our survey, we asked Commerce program staff about the training and supports grantees would need. 69% indicated
that grantees/subgrantees would need training to adopt new data practices; however, there was much more
uncertainty expressed about what specific types of training would be required. The biggest need cited is the people time
that grantees/subgrantees need to do the work required to implement these data collection and reporting practices,
and the monetary resources needed to pay for this additional effort. In conversation, program staff suggested that
grantee needs will vary widely – from orientation to the data elements Commerce is requiring to technical training on
the data reporting system that Commerce develops, and direct engagement is needed to understand the training,
capacity and resources needed for each grantee.
In recent years, the agency has averaged about 2,500 contracts annually. Even marginal administrative costs will result
in meaningful burden for Commerce’s grantees and subgrantees. For example, consider the hypothetical situation in
which it would take an average of an additional hour per invoice per contact to submit this information. As a whole,
grantees would need an additional 30,000 hours every year. This is the equivalent of between 14 and 16 full-time
employees.
A proactive change management approach is needed to support Commerce staff, grantees, and the communities that
the agency serves.
The need for effective change management was a theme we heard across the project, including an integral conversation
with a Commerce employee who has held roles within the agency as an organizational agility manager and as a manager
in Commerce’s Performance and Project Management Office. As we learned from the survey, Commerce programs
function independently, which has resulted in decentralized data practices. Many employees emphasized the need for a
thoughtful change management approach to successfully implement standardized data practices. When asked what
good change management looks like, highlights include:
• The agency should be able to rally around a collective “why” and connect objectives of this initiative to Commerce’s
objectives
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• A robust communication plan that includes proactive, agency-wide communication, where staff are engaged early
and often throughout the process
• Proper planning, and an expectation that there will be some resistance
There is an opportunity for Commerce to hire contractors to help guide the cultural change associated with
implementing an agency-wide transformation to its data practices, and for these contractors to influence and help build
this capacity within the agency. This is an approach that resonated with the project team at Commerce. Therefore, when
thinking about the resources needed to support this data standardization work, contractor resources were often linked
with building similar capacity at Commerce to ensure that the expertise did not leave when the contract ended.
In addition to the internal change management described above, Commerce should invest capacity in external change
management. We recommend that Commerce engage both its grantees and the beneficiaries or potential beneficiaries.
Engaging grantees can help Commerce build awareness of the new requirement and also better understand grantees’
needs and strategies for support. Engaging directly with communities can help Commerce incorporate community
perspectives and ensure the effort benefits (and does not harm) communities.
Community voices should be intentionally and authentically included in the planning and implementation process.
Personal identity is complex, and the collection of demographic data can be sensitive. For example, questionnaire design
has the potential to affirm some identities, while obscuring others.
Additionally, when reporting on data about individuals and groups, this reporting is subject to a “small number
standard” in which non-zero counts below a certain threshold (often 10 individuals) are suppressed and instead
reported as an asterisk or other symbol to indicate a number below the threshold. Commerce, like all state agencies, has
an ethical responsibility to protect individual privacy, especially when disaggregating demographic and geographic data
in its public reports. Commerce applies other agencies’ policies (such as the Department of Social and Health Services)
and federal policy when necessary. Additionally, Commerce is currently drafting its own “small numbers” policy to
protect individual privacy when other agency or federal policy are not applicable. Community perspectives gained from
collaboration can help Commerce navigate the balance of disaggregating data to make historically excluded populations
visible, while maintaining confidentiality and risk for beneficiaries.
Key finding Recommendation for a path forward
Increase capacity in both internal and external
change management to ensure successful
implementation. Without proactive change
management, new practices will not be widely or
Commerce staff and grantees/subgrantees will need a consistently adopted, which will negatively affect
range of supports to implement new data practices. the quality and completeness of the data. This will
limit Commerce’s ability to use the data to
understand impact, shape programs and investment
equitably.
Commerce needs more centralized capacity to support a robust data culture.
Currently, Commerce programs’ data collection is highly fragmented and individualized. In order to support broad,
standardized data availability and appropriate use of data, capacity is needed to develop standards, guidelines, and
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secure data. Commerce has one data manager to support the agency’s extremely diverse data footprint, and data
stewardship has not been operationalized beyond this data manager role.
Given the magnitude of the proposed changes, capacity will be needed to directly support Commerce program teams, as
well as to clean, validate, and analyze submitted data. This comprehensive, standardized data will allow for the creation
of robust reports to direct investments equitably. Such reports could include longitudinal or trend analyses, interactive
dashboards, and mapping and other novel visualizations. These reports will enable Commerce to identify areas of
opportunity for investments. Transparent data governance will also be critical to supporting communication and
building trust with the community.
Additionally, more centralized capacity for data governance will create more opportunities for coordination and
alignment with other stakeholders. For example, the state recently hired a Chief Data Officer, who can also provide
direction at the state level. We also envision coordinating proactively with other agencies and initiatives such as Office
of Minority and Women's Business Enterprises (OMWBE) and Washington Technology Solutions (WaTech), and
continued partnership with One Washington.
Key finding Recommendation for a path forward
Invest in capacity for centralized data governance,
including capacity to clean, analyze, and visualize
data for use by Commerce, legislative, and
More centralized capacity is needed within community stakeholders. This capacity is critical to
Commerce to support a robust data culture. supporting data availability, appropriate use of data,
and reporting that can answer key questions such
as: “Who is being funded by Commerce?” and “Who
is benefiting from Commerce funding?”
Commerce needs a single repository to collect and store standardized demographic and geographic data.
Early in our conversations with key stakeholders, two technology solutions were elevated as clear options to explore for
this data standardization effort: (1) Commerce’s Contract Management System (CMS), and (2) Workday via the One
Washington initiative. Additionally, hearing from Commerce program staff and conducting our own research, we also
analyzed Salesforce (customer relationship management software), REDCap (data capture and database creation
software), and Smartsheet (project and data management software).
One Washington (Workday) can be part of the solutions to meet Commerce’s data repository needs, but schedule
delays and scope limitations prevent Workday from being the sole solution.
Listening sessions were conducted with external stakeholders from other state agencies to understand how Commerce
can align with existing and future efforts. One agency of particular interest for this project was the Office of Financial
Management, and specifically the One Washington initiative. One Washington’s mission is to “lead the transformation of
state business processes and tools within finance, procurement, budget and HR/payroll functions” (website). Our
primary goal in our conversation with One Washington’s enterprise resource planning team was to explore whether the
demographic and geographic data elements that are of interest to Commerce are consistent with data elements in the
extended financials and procurement phase of their work. What we learned is that the One Washington initiative is
behind schedule. Additionally, One Washington cannot be the sole data collection tool or repository for Commerce’s
demographic and geographic data because its scope is restricted to replacing the core financial system and does not
14
include capturing data on the workforce or beneficiaries. As a result, other technological solutions should be seriously
considered by Commerce.
While Salesforce, REDCap, and Smartsheet have features that would be beneficial to data standardization, collection,
and reporting for Commerce, each fell short.
Salesforce is prohibitively expensive, and perhaps provides more functionality than necessary. REDCap, while excellent
for data collection and storage, does not have the technical support on the vendor’s side that would be needed to
support Commerce. And while Smartsheet is a software that a majority of Commerce programs have adopted, it
functions best for workgroup collaboration rather than sustaining an agency-wide effort, and is not approved for
collecting and storing confidential data.
CMS is the best solution, and is already used by a majority of Commerce programs.
Based on conversations with key CMS personnel at Commerce and our assessment of other technologies, CMS is the
best, near-term solution to support this data effort. Significant modifications are required to update the system, but
nearly all Commerce program staff are familiar with it. Most existing geographic data and some demographic data is
already housed within CMS, and as the contract management system it is a modest step to link the output and impact
data with the funding source. Building upon CMS eliminates the need for new software to pass security approvals for
use, and reduces the time and effort required for Commerce staff to be trained in new software and to integrate new
software into their workflow.
Key finding Recommendation for a path forward
Modify Commerce’s Contract Management System
(CMS) to serve as a repository for this data effort.
Commerce needs a single repository to collect and Nearly all Commerce programs are already using the
store standardized demographic and geographic system. Compared to the adoption of a new system,
data. enhancing Commerce’s current system-of-record
(CMS) will accelerate progress by reducing costs and
time needed for training staff and grantees.
Recommendations
Commerce's demographic and geographic data collection should be enhanced and standardized to build a more
comprehensive understanding of how Commerce resources are driving greater equity throughout Washington. To
achieve this, we recommend:
1. Adopting a project roll-out approach that includes three stages: 1) planning, 2) development, and 3)
implementation. We recommend launching implementation with a learning-oriented pilot by infusing new data
requirements into all new grants going forward, as well as revising a subset of existing grant agreements. Lessons
learned from this pilot can inform implementation at-scale.
2. Allocating about $2.3 million in one-time costs and $2.1 million per year on an ongoing basis to support
standardized data collection. Note that this estimate does not include the cost of increasing funding to grantees to
support their ability or capacity to act on new data practices. Additionally, if the recommendation is only partially
funded, we would expect the pace of change to slow and implementation at-scale to be pushed back.
15
1. Adopt a staged project roll-out
Figure 7: Project roll out
Planning Development Implementation
Internal and external stakeholder engagement
Change management
Technology modifications
Staff training and implementation
Grantee training and implementation
Figure 7 depicts the three stages of project roll-out: planning, development, and implementation. The project sequence
also highlights major activities that stem from our findings, particularly the need to:
• Modify Commerce’s Contract Management System (CMS) to serve as a repository for this data effort. Nearly all
Commerce program staff are already using the system. While collecting demographic and geographic data on
grantees/vendors is aligned with One Washington, capturing data on workforce and direct beneficiaries is currently
out of One Washington’s scope and the project itself will not be complete for several years.
• Invest capacity in both internal and external change management to ensure successful implementation. We
recommend that Commerce engage both its grantees and the beneficiaries or potential beneficiaries of its funding.
Engaging grantees can help Commerce build awareness of the new requirement, and better understand grantees’
needs and strategies for support. Engaging directly with communities on this data collection effort can help
Commerce incorporate community perspectives and ensure the effort benefits (and does not harm) communities.
• Implement strong data governance, including data privacy and security. Currently, Commerce programs’ data
collection is highly fragmented and individualized. To support broad, standardized data availability and appropriate
use of data, additional capacity is needed to develop standards and guidelines, and secure Commerce’s broad and
varied data footprint. Transparent data governance can also support communication and building trust with the
community. The resource recommendation includes the cost of development of this foundational capacity, as well
as capacity for data cleaning, anonymization, and aggregation.
When it comes to the implementation stage, we recommend revising all new grant agreements going forward, while
piloting a process to revise existing agreements with subset of grantees. With these learnings, Commerce will be well
positioned to implement the new data practices at-scale.
After hearing directly from Commerce program staff through the project kick-off meetings and the agency-wide survey,
a top-of-mind question was what it would take to revise grant agreements to formalize new data collection standards,
given that the agency has 2,500 annual grant agreements on average. In partnership with Commerce experts, we
envisioned the implications of three scenarios: (1) revise all existing and future grant agreements, (2) revise a subset of
existing and all future grant agreements, and (3) implement only for new grant agreements. Together, we evaluated
these options on the following criteria: (A) the person-time resources required to execute these changes across the
agency, (B) the expediency to get Commerce to be able to answer the questions “Who is being funded by Commerce?”
16
and “Who is benefiting from Commerce funding?”, and (C) through a lens of optimal change management. Table 1
displays a matrix of these options and criteria.
Table 1. Alternative approaches to revising Commerce grant agreements
A. Person-time B. Understanding C. Change
Options resources Commerce’s impact management
1. Implement in new grant Ability to understand
High (across all
agreements, revise all existing grant impact of funds already High effort
programs)
agreements distributed
2. Implement in new grant Partial understanding
Moderate (phased
agreements, revise a subset of existing of already distributed High/moderate effort
approach)
grant agreements funds
Understanding of
3. Implement only in new grant
Moderate impact of future Moderate effort
agreements
funding
We recommend option 2 – revising a subset of existing and all future grant agreements – as this approach balances the
pros and cons of the other two options. Through our engagements with program staff, there are some programs that
already have robust demographic and geographic data. A phased approach could include identifying a percentage of
programs (for example, 10% = 250 grant agreements) to revise existing grant agreements to collect standardized
demographic and geographic data. This would require a smaller infusion of resources to support staffing capacity and
could provide Commerce employees with lessons learned and early insights into how their work benefits people in
Washington.
While option 1 would expedite Commerce’s ability to understand the impact of their funding, the amount of work
required to revise all existing grant agreements would be costly. On average, the agency has 2,500 grant agreements
annually. Without the addition of significant staff resources, current staff would have to choose to either spend their
time on their daily duties or amending all grant agreements (such as contacting grantees, explaining changes to them,
getting amendments drafted and signed, etc.). A similar situation occurred during the COVID-19 pandemic. The influx of
pandemic relief funds required Commerce staff to balance a workload beyond their standard day-to-day duties, and day-
to-day duties were dropped to prioritize the immediate needs of people trying to navigate the pandemic. Imposing a
workload of this magnitude would have widespread negative impacts on Commerce’s operations and programming.
The third option – introducing new data collection and reporting requirements only for new grant agreements – would
require a moderate amount of person-time resources and change management effort. However, this approach would
have the longest timeline to have a full view into the impact of Commerce’s work and funding.
2. Allocate about $2.3 million in one-time costs and $2.1 million per year on an ongoing basis to support
standardized data collection.
This estimate of the resources needed to align data collection practices across the agency is based on a cost model that
connects time and resources to activities, and distinguishes between one-time and routine, ongoing costs. Table 2
provides a summary of line-item costs aligned to five major activity categories: 1) Stakeholder engagement and
socialization, 2) Launch planning and implementation, 3) Program staff training, 4) Technology, and 5) Additional staff
capacity.
17
A significant one-time investment is needed, primarily to support intensive launch planning and implementation ($1.42
million or about 60% of the one-time total cost) and investment in enhancing technology systems to serve as a
repository for the standardized demographic and geographic data ($867,000 or about 37% of the one-time total cost).
Note that the launch planning and implementation estimate includes capacity for internal change management to help
prepare and support Commerce staff and leadership, as well as capacity to build grantee awareness of new practices.
The estimate does not include capacity for engagement with community or more intensive dialogue with grantees,
which we recommend to maximize the benefit of collecting standardized data for Commerce and its stakeholders (the
Legislature and people who live in Washington).
Ongoing implementation is estimated to cost approximately $2.14 million per year. The largest driver of this cost is staff
capacity at about $1,640,000 per year, which includes IT staffing to support Commerce-wide data governance, security,
and appropriate data use ($450,000), as well as additional capacity needed by program teams ($1,190,000). Ongoing IT
support is estimated as a percentage of capacity from an additional eight staff members. For program staff, using the
median for additional hours needed reported in the survey, we estimate that the ongoing work of 1) data collection and
quality assurance, and 2) data analysis, reporting, and visualization will translate into a need of about 7.4 additional
FTEs. For more details, see the appendix. The second largest cost category is data purchasing at $250,000. This
investment will help Commerce identify and access new sources to extrapolate beneficiary data for grantees whose
work does not include direct service (see Figure 5 for a map of exemptions to beneficiary data collection).
18
Table 2: Time and Cost Estimate Summary
Line Item Details One-time Est. Cost Est. Cost
vs. Annual (one-time) (annual)
I. Stakeholder engagement and socialization
Launch stakeholder Listening sessions with grantees; Engagement with the Office of Equity, One One-time $62,000 --
engagement Washington, and other state agencies; includes preparation of materials,
outreach, and follow-up across all engagements; Contractor to oversee all
engagements
Ongoing stakeholder Reporting out findings and sharing process improvement changes with Ongoing -- $31,000
engagement grantees, Office of Equity, One Washington, and other state agencies; includes
preparation of materials, outreach, and follow-up across all engagements
Subtotal $62,000 $31,000
II. Launch planning and implementation
Commerce HQ and IT
Developing policies & Change management approach, creating data governance policies and data One-time $81,000 --
procedures collection procedures, updating to new grant agreements
Launch roll out to Development of materials, hosting meetings for program staff to share "What" One-time $99,000 --
staff is changing, "Why" it's changing, and "How" it impacts their programs
Launch roll out to Development of materials, hosting meetings for grantees to share "What" is One-time $15,000 --
grantees changing, "Why" it's changing, and "How" it impacts their programs
Revising a subset of Updating existing grant agreements (i.e., grant agreements in place before One-time $100,000 --
existing grant implementation of changes to data practices) for a subset within programs who
agreements have a high potential for early adoption to changes in data practices
Program Staff
Learning new policies Internalizing and operationalizing new processes and expectations around data One-time $375,000 --
and procedures collection
Developing program Implementing changes to existing program systems and structures to be able to One-time $750,000 --
specific procedures support changes in data collection
and structures
Subtotal $1,420,000 --
III. Program Staff Training
Data and equity Training like equitable decision making based on data collection, harm Ongoing -- $80,000
prevention when collecting data from vulnerable / marginalized communities
19
Line Item Details One-time Est. Cost Est. Cost
vs. Annual (one-time) (annual)
Data collection and Training including data standards and security Ongoing -- $80,000
quality assurance
CMS technology Training that highlights modifications to CMS to support effort and walks Ongoing -- $60,000
training through processes to enter data to remain compliant with new data practices
Subtotal -- $220,000
IV. Technology
CMS modifications External contractors to design, build, test, and launch changes to CMS over a 9- One-time $867,000 --
month timeline
Data purchasing Ongoing -- $250,000
Subtotal $867,000 $250,000
V. Additional Staff Capacity
Commerce HQ and IT
Data governance, Additional IT staffing needs to support this effort Ongoing -- $451,000
maintenance, and
support
Program Staff
Data collection, Additional program staffing needs Ongoing -- $625,000
quality assurance
Data analysis and Additional program staffing needs Ongoing -- $563,000
reporting
Subtotal -- $1,639,000
TOTAL $2,349,000 $ 2,140,000
20
Appendices
Legislative mandate
This report details the process, findings, and recommendations of a project that was conducted in response to the Sect.
128 (216) of Chapter 297, Laws of 2022 (the 2022 supplemental operating budget)):
(216) $300,000 of the general fund—state appropriation for fiscal year 2023 is provided solely for the department
to report how the department will collect demographic and geographic information from organizations who
receive direct or indirect grants from the department.
(a) The department may contract to complete the report. The department must collaborate with the one
Washington enterprise resource planning team to determine what demographic and geographic data
elements would be consistent with data elements in the extended financials and procurement phase of one
Washington.
(b) The report must also include accurate cost and time estimates needed to collect the demographic and
geographic information from department grantees and their subgrantees. The department must consult
with the office of equity to ensure that demographic tracking information can be used to help create an
accurate definition of "by and for organizations." The department must report to the legislature by June 30,
2023. The report must include, but is not limited to, the following information:
(i) The cost and time required for the department to revise current grant agreements to collect
demographic and geographic data;
(ii) The cost and time required for the department to incorporate the collection of demographic and
geographic data into future grant agreements;
(iii) The cost and time required for the department to align demographic and geographic data points to
the one Washington program to serve as a data collection system and repository of demographic and
geographic data on all department grant agreements;
(iv) In addition to the one Washington program, an analysis of other information technology systems
that can serve as a unified single data collection system and repository for demographic and geographic
data on all department grant agreements. This analysis should compare and contrast the efficiency and
effectiveness of each system with the capabilities, cost, and timeliness of using the one Washington
program for this purpose; and
(v) Recommendations on grants that should be excluded from the responsibility to collect demographic
and geographic data.
21
Table A1. Phase 1 listening session engagements
Organization Participant’s name Role Goals of engagement
Washington State Martin McMurry* Chief Operations Officer Hear their perspective on the goals of
Department of the project and what achieving data
Commerce Marissa Joy Chief Equity and Operations Officer equity could look like for Commerce,
VanHoozer and its impact on the communities
Commerce serves
Washington State Elizabeth Saylor Chief Information Officer Understand how the project and the
Department of recommendations that emerge can
Commerce Anna Batie Kuka IT Data Management Coordinator integrate with existing work and
infrastructure at Commerce
Washington State Randi DuPrey IT Business Analysts, Contract Learn of existing, centralized
Department of Management System (CMS) geographic and demographic data
Commerce Karl Lowood* collection at Commerce
Washington State Lilian Ferraz Management Analyst Get insight into ongoing work at
Department of Commerce to define by-and-for
Commerce organizations
Washington State Jason Henderson IT Business Analyst, Geographic Gain knowledge on the recent
Department of Information System (GIS) modernization of geographic data
Commerce collection at Commerce, and how
Commerce staff have adapted to the
changes
Washington State Megan Matthews Assistant Director of Shared Power Identify alignment between with the
Office of Equity Design Office of Equity’s standards for the
Caitlyn McNabb Statewide Spatial Equity Analyst & collection, analysis, and reporting of
Coordinator demographic data disaggregation
Kathy Williams Assistant Director of Innovation and
Performance
Washington State Community partners Governor’s Office of Indian Affairs To share our project goals and
Office of Equity Commission on Hispanic Affairs approach, to learn about efforts in
Commission on African American Washington and across the country to
Affairs improve demographic data collection
Commission on Asian Pacific American in service of equity
Affairs
Women’s Commission
LGBTQ Commission
Department of Veterans Affairs
Governor’s Committee on Disability &
Employment Issues
Washington State Robin Milne Primary Procurement Assistance Identify alignment between Commerce
Office of Financial Practitioner and the integration of Workday by One
Management – Michael Schaub One Washington Finance Lead Washington
One Washington
Washington State Sue Richards Workforce Research & Performance Understand demographic data
Office of Financial Manager collection on state employees and the
Management workforce
Washington State Alisha Ghanie Management Analyst Understand enterprise-level
Department of demographic data collection on
Enterprise vendors via Washington’s Electronic
Services Business Solutions (WEBS)
22
Washington State Cathy Wasserman State Epidemiologist Learn about their participation with
Department of the Office of Management and
Health Leah Wainman Equity & Health Assessment Manager Budget’s listening sessions on updating
the federal race/ethnicity categories
Harriet Tubman Korbett Mosesly Chief Strategy Officer Learn how they are engaging
Foundation for community to impact changes to
Safe Passage Commerce policies, procedures, and
practices
* Note: Participant is no longer in their role at Commerce.
Table A2. Phase 3 interviews
Interviewee’s name Role Goal of engagement
Talia Scott Homeless Management Information Understand complexities of additional data reporting for
System (HMIS) Manager; Housing programs that already collect and report demographic data for
Division state and federal funding sources
Beth Robinson Supervisor, Local Government Division Gain clarity about the lack of data collection at the workforce
level (i.e., those executing the work funded by Commerce) for
programs
Randi DuPrey IT Business Analyst, Contract Learn about the modifications needed to CMS to adapt to new
Management System (CMS) demographic and geographic data collection practices, and
resources required to support that effort
Rebecca Stillings Managing Director, Office of Equity Understand past efforts at Commerce with similar impact on
and Belonging programs, lessons learned, and resources needed to support a
robust change management strategy
Sarah Champion Chief Contracts Officer Learn process and resources required to update existing and
future grant agreements
Jill Eikenhorst Supervisor, Energy Division Understand criteria for programs that may be excluded from
demographic or geographic data collection
Elizabeth Saylor Chief Information Officer Gain clarity on additional resources required by IT to support
work around data collection, quality assurance, analysis, and
Anna Batie Kuka IT Data Management Coordinator reporting
23
Survey responses
Phase 2 Survey Respondents – Divisions, units and programs represented
Community Services
Community Economic Opportunities Unit
Office of Crime Victims Advocacy
Office of Firearm Safety and Prevention / Community Safety Unit
Washington State Developmental Disabilities Council
Energy
Clean Buildings
Energy Programs in Communities Unit
Housing
Data & Performance Unit
Homelessness Assistance Unit
Homeownership Unit
Multifamily Housing Unit
Office of Homeless Youth
Local Government
Boards
Community Capital Facilities
Community Capital Facilities - Early Learning Facilities
Community Development and Assistance
Growth Management Services
Research and Development Services Unit
State Broadband Office
Office of Economic Development and Competitiveness
Administrative
Economic Innovation Sector Leads
Sector Lead Program
Small Business Export Assistance
Small Business Training & Education / Business, Investment & Visitor Attraction
Non-programmatic divisions
Director’s Office
Government Affairs and Policy
Equity and Operations
Information Services
Equity and Belonging
24
Phase 2 Survey Respondents – Programs that do not provide grants by division
Do not provide grants, contracts, or loans (n=13)
* Denotes that another respondent reported that the program provides grants, contracts, or loans
Community Services Local Government
*Self-Advocates in Leadership Bond Cap Allocation Program
*Allies in Advocacy *Climate Program
*Advocacy Partnership Project State Surplus Property Program
*Informing Families Manufacturing Council
Home and Community-based Services Advisory Committee
Office of Equity
Director’s Office Engaged Employee Survey
Tribal Relations
Operations
Housing Service and support all programs
Foreclosure Fairness Program
Housing Contract Management System
Provides grants, contracts, or loans (unique program n=103, including duplicate n=111)
^ Denotes that multiple respondents submitted a survey on the program’s behalf; however, all respondents reported that the program provides grants, contracts, or
loans3
Community Services Low-income Home Energy Assistance Program
Advocacy Partnership Project Low-income Home Water Assistance Program
Allies in Advocacy Outreach to Historically Underserved Communities
Asian Pacific Islander Coalition Spokane Self-Advocates in Leadership
Asset Building Program State funded Community Services Block Grant
Byrne Justice Assistance Grant Victim Witness Assistance
Community Law Enforcement Partnership Victims of Crime Act
Dan Thompson Memorial Community Services Account Violence Against Women Act
DHSH Emergency Shelters WA Diaper Program
Domestic Violence Legal Advocacy WA Tax Credit Community Outreach Program
Family Resource Center Program Whidbey Island Homeless Coalition
Federal funded Community Services Block Grant
Financial Fraud and Identity Theft Energy
Hispanic Business Professional Association Clean Buildings
Informing Families Clean Energy Fund - Building Electrification
Kittitas County Health Network Clean Energy Fund - Direct
3
Note on Survey Methodology: Understanding that Commerce program staff can be responsible for multiple programs, survey respondents were
invited to submit a single survey when data practices are identical across their programs. If programs had different data collection practices,
respondents were asked to complete a survey for each program or set of programs with identical data practices.
Upon reviewing the survey results, we identified five programs who were both classified as “does not provide grants, contracts, or loans,” and
separately as a program who “provides grants, contracts, and loans.” Since this analysis is focused on those who do provide grants, contracts, or
loans, we held the assumption that these five programs fell into this category and included them in the analysis.
Additionally, among programs that were classified as “provides grants, contracts, and loans,” there were six programs that were represented twice
(i.e., two different respondents reported on the program), and one program that was represented in triplicate (i.e., three respondents reported on
the program). This totals to eight duplicates from 111 program entries (<10%). Knowing that a single program at Commerce may sometimes be
represented as separate programs when there are multiple funding sources, all repeat entries were included in the analysis. We believe that these
duplicated programs do not have a significant impact on the results of the analysis, and the results will provide directionally correct information on
Commerce’s current demographic and geographic data collection practices.
25
Clean Energy Fund - Electrification of Transportation System Young Adult Shelter
Clean Energy Fund - Grants to Non-profit Lenders ^Youth Adult Housing Program
Clean Energy Fund - Grid Modernization Youth Homeless Demonstration Program
Clean Energy Fund - Research, Development, and
Demonstration Local Government
Clean Energy Fund - Rural ^Behavioral Health Facilities
Clean Energy Fund - Wood Energy Conservation Brownfields Revolving Loan Fund
Energy Retrofits for Public Buildings - Solar ^Building Communities Fund
Low-income Community Solar Development ^Building for the Arts
Low-income Community Solar Grants Climate Program
Solar plus Storage for Resilient Communities Committed Private Partner
Weatherization Community Development Block Grant
Community Economic Revitalization Board
Office of Economic Development and Competitiveness Defense Community Compatibility Account
Go Global Dental Capacity Grants
Global WA Direct Capital Appropriations
Innovation Cluster Accelerator ^Early Learning Facilities
NW Disaster Grants Food Banks
State Trade Expansion Program (STEP) Growth Management Services
Infrastructure Projects
Housing ^Local Community Projects
Anchor Communities Initiative Planning and Predesign Capital Equity Program
Apple Health and Homes Port Infrastructure
Arlington Campus Project Prospective Development
Centralized Diversion Fund Public Works Board
Community Based Rental Assistance Research Services
Consolidated Homeless Grant Rural Broadband Planning
Eviction Rent Assistance Program 2.0 State Broadband Office
Forensic PATH Work, Education and Health Monitoring
Homeless Student Stability Program ^Youth Recreational Facilities
HOPE and Crisis Residential Centers
Housing Stability for Youth in Courts
Housing Trust Fund - HOME
Housing Trust Fund - Homeownership
Housing Trust Fund - National Housing Trust Fund
HUD Continuum of Care and Emergency Solutions
Independent Youth Housing Program
Manufactured / Mobile Home Relocation Assistance Program
Manufactured / Mobile Relocation Coordination Program
PATH
Peer Pathfinder
Rights of Way Initiative
Shelter Program Grant
Street Youth Services
System Demonstration Grant
System of Care
Tenant Based Rental Assistance
Transitional Living Program
Treasury Rent Assistance Program 1.0
Treasury Rent Assistance Program 2.0
Washington Youth and Families Fund Diversion
26
Table A3. Examples of race/ethnicity data collection
Forward-thinking demographic data collection Federal standards of demographic data collection
Example: U.S. Department of Housing and Urban
Example: State Office of Equity
Development: Homelessness Management System
I most closely identify with the following race(s): Race
We recognize that race and ethnicity are not • American Indian, Alaska Native, or Indigenous
quantifiable values. Rather, identity is a complex mix • Asian or Asian American
of one’s family and social environment, historical or • Black, African American, or African
socio-political constructs, personal experience, • Native Hawaiian or Pacific Islander
context, and many other immeasurable factors. • White
• Client doesn’t know
• American Indian or Alaska Native • Client refused
• Asian • Data not collected
• Black or African American
• Hispanic or Latin American Ethnicity
• Native Hawaiian or Other Pacific Islander • Non-Hispanic/Non-Latin(a)(o)(x)
• White
• Hispanic/Latin(a)(o)(x)
• Race identity not specified above, please specify
• Client doesn’t know
• Client refused
I am read and treated as the following race(s):
• Data not collected
Although there is no biological basis to race, we
acknowledge the real effects this socially constructed
categorization of people in the U.S. has on peoples’
lives. Because people are treated in accordance with
U.S. racial narratives, we are leading with racial
justice, and collecting race data that helps us
understand disparities in how people are treated by
race, and the effects those disparities have on
peoples’ opportunity to thrive.
• American Indian or Alaska Native
• Asian
• Black or African American
• Hispanic or Latin American
• Native Hawaiian or Other Pacific Islander
• White
• Race identity not specified above, please specify
My ethnicity is:
• I am Alaskan Native/American Indian. My identity
is:
• Tribal Citizen
• Urban Indian
• I am not Alaskan Native/American Indian
27
Current state of Commerce demographic and geographic data collection
Headlines
• 105 of the 111 programs that provide grants, contracts, or loans reported that they collect demographic or
geographic data.
Demographic Data
• Of programs that provide grants, contracts, or loans, 70% collect some demographic data. Most
demographic data was collected on beneficiaries, followed by grantees/subgrantees, and very few programs
collected demographic data on workforce.
• Gender and Race/Ethnicity were the demographic categories most frequently captured by programs across
all levels. Sexual orientation was the least collected demographic category across all levels.
• Programs’ data collection practices were often driven by funding reporting requirements, specifically state
and federal funding sources.
Geographic Data
• 94% of programs who responded to the survey collect some geographic data, most often on the physical
location of grantees/subgrantees. County was the most common level of geographic data collected for
grantees/subgrantees and for beneficiaries.
Demographic Data Collection Practices
Survey responses represented 111 programs at Commerce, 78 (70%) of which currently collect some type of
demographic data. For a full list of the divisions, units, and programs represented by the survey respondents, please
see Appendix. This was a surprising finding since these data are not stored centrally; and anecdotally, the perception
was that programs generally were not collecting demographic data. The survey went on to ask programs that collect
demographic data whether they collected data on specific demographic categories (See Figure 3). Gender and
race/ethnicity were the most common demographics collected.
The survey captured data collection across three levels:
• Grantees/Subgrantees: Those who receive direct funds from Commerce; some refer to this group as
contractors or subcontractors.
• Workforce: Those who are paid to execute the work funded by Commerce.
• Beneficiaries: Those who benefit from the work done and was funded by Commerce.
Examining demographic data collection at each of these, data was most often collected for program beneficiaries,
followed by grantees/subgrantees, and was least collected for workforce (See Figure 4).
Among those collecting demographic data, more than half reported that federal or state reporting requirements
influenced their data collection. Despite those reporting requirements, responses to the survey clearly indicate that
demographic data collection practices widely vary among Commerce’s current programs.
28
Figure A1. Percentage of programs collecting demographic data by demographic category
80%
70%
67%
61%
60%
53%
50%
40% 35%
20%
0%
Any demographic Gender LGBTQ+ Disability Status Veteran Status Race / Ethnicity
data
Figure A2. Percentage of programs collecting demographic data by demographic category and level
(grantee/subgrantee, workforce, beneficiary)
Race / Beneficiary 52%
Workforce 16%
ethnicity Grantee / subgrantee 40%
Beneficiary 35%
Veteran
Workforce 8%
Status Grantee / subgrantee 27%
Disability Beneficiary 44%
Workforce 10%
Status Grantee / subgrantee 21%
Beneficiary 27%
LGBTQ+
Workforce 2%
Grantee / subgrantee 8%
Beneficiary 45%
Gender Workforce 8%
Grantee / subgrantee 33%
0% 10% 20% 30% 40% 50% 60%
29
Geographic Data Collection Practices
Similar to demographic data, we asked Commerce program staff to report on their current data collection practices for
geographic data at the grantee/subgrantee, workforce, and beneficiary levels. Of the 111 programs who provide grants,
contracts, or loans, 104 (94%) currently collect geographic data at one or more of those levels. Most programs collected
geographic data for grantees/subgrantees and beneficiaries, and no programs collect geographic data for workforce (See
Figure 5). County was the most comment level of geographic data collected for grantee/subgrantees and beneficiaries.
Figure A3. Percentage of programs collecting geographic data by geographical unit and level (grantee/subgrantee,
workforce, beneficiary)
Beneficiary 2%
Census
Workforce 0%
block
Grantee / subgrantee 2%
Beneficiary 5%
Census
Workforce 0%
track
Grantee / subgrantee 11%
Beneficiary 21%
City Workforce 0%
Grantee / subgrantee 70%
Beneficiary 44%
County Workforce 0%
Grantee / subgrantee 74%
Legislative
Beneficiary 9%
Workforce 0%
district Grantee / subgrantee 36%
Any Beneficiary 52%
geographic Workforce 0%
data Grantee / subgrantee 86%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90%
Regarding geographic data collection, the agency is further along in standardizing their data practices, and still, there
are still opportunities for improvement. Contract location is captured in the Contract Management System (CMS), and
in some cases, the region served by the contract can be deduced. For example, if the contract is for work on a water
treatment plant, the region served by the contract is the region served by the water treatment plant. Furthermore,
there has been an effort over the past few years to collect more detailed information on areas impacted in CMS,
including legislative districts, city, and county; however, this geographic data is typically available for contracts for
infrastructure or capital projects, and less so for projects that provide direct client-based services, which is just a
portion of what Commerce funds.
30
Additional Staff Capacity Details
Table A4. Commerce Headquarters and IT
Estimated Estimated Estimated Estimated
hours for IT hours for hours for hours for
Hours Cost FTE Data IT Journey IT IT Project
Task Estimate Estimate Equivalent Stewards Level Supervisor Manager
Data governance,
maintenance and
5,750 $450,521 299% 4000 1000 250 500
ongoing training and
support
TOTAL 5,750 $450,521 299%
Table A5. Commerce Program Staff
Median
hours
estimated
by Program
Hours Cost FTE Staff per Number of
Task Estimate Estimate Equivalent Program Programs
Data collection and
7,500 $625,000 391% 50 150
quality assurance
Data analysis,
6,750 $562,500 352% 45 150
reporting, and visuals
TOTAL 14,250 $1,187,500 742%
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File and source
- File
- 2023_commerce-reports-grants-demo-report-final-0be78fbc-192e-40df-b584-a39a.pdf
- Size
- 694,090 bytes
- SHA-256
- 81c7587dc949d173c4572332a2dbdcd8b3b3608584e3e0d838244589ddc75757
- Original
- app.leg.wa.gov