The IT Manager’s Strategy for Data-Driven Government

Chaz Mateer By: Chaz Mateer

With the increased abundance and availability of data, we often find ourselves looking for innovative ways to leverage these data and to derive insights that will further the mission of our enterprise. Data-driven strategy and IT management principles are often employed in private industry to get ahead and deliver business value quicker and to beat out competition.  However, more and more we are seeing data driven practices enter the local, state, and federal government spheres where agencies are utilizing innovative data management practices and open data portals to improve operations and deliver valuable insights to internal stakeholders and members of the public. This shift is further backed by initiatives such as the Federal Data Strategy which aims to bootstrap government agencies to leverage data as a strategic asset. Furthermore, if nothing else, our current state in the COVID-19 pandemic crisis highlighted the critical importance of quick, trustworthy, and actionable data delivery.


The Problem
One of the main issues we see our clients run into when trying to adopt a more modern data strategy is not knowing where to start. How to wade through the plethora of technology and vendor options when looking at data warehouse/lake options, reporting tools, dashboard/business intelligence (BI) platforms. 
“What are the right tools for me?” 
“Do I even need a data warehouse?” 
“What even is a data warehouse?”
“I need HOW MANY named user licenses for this solution?!”
“What sort of people and skills do I need to pull this off?”
“Do I have enough funding for this?”
Beyond technology, and even more important, “does my agency have a data-centric culture” to support a data strategy and are IT and the business units closely aligned to deliver the most impactful insights? Data initiatives often start out with great vigor and support from those involved but once the reality of the effort required sets in things can sometimes fizzle out.

  • Existing data can be poor quality – leads to poor quality analysis/limited insights
  • Legacy systems may be seemingly too dated/costly for upgrade
  • ETL processes may be complex and/or poorly orchestrated – difficult to figure out what is going on and if you can trust the data
  • Unable to join data from disparate internal and external sources (including tabular and geospatial) in a reliable and consistent way
  • “That’s the way I’ve always done it”
  • “I don’t know what the business units want”
  • “This is going to cost too much”
  • “We can’t manage the data we currently have, how are we going to scale this?


How to Solve It
Do you want to harness real-time information to make dynamic data driven decisions? To have dashboards at your business users’ fingers tips enabling them to answer their own questions and freeing up technology staff for other projects? Want the ability to trust your data and to make forecasting models so the organization can stop being reactive and instead get ahead of the data curve? You can get there through:



How to tie it all together?
Create a Data Strategy Roadmap. A roadmap helps to outline and understand current state, the desired goals of a data initiative, and a plan to get there. Furthermore, it operates at a strategic level without getting too in the weeds on technical details. A roadmap should certainly outline and assess technology choices at a high-level but can exclude implementation details (which can be covered in more tech-focused plans) in favor of higher-level cultural discussions. This allows for greater buy-in from business units and executives and will help with funding such an initiative.

Roadmap Steps
Here are some of the key initiatives to undergo during a data road map project.

Identify Current State
Assess where the organization currently stand in terms of staff, data governance policy, and technology options. Furthermore, how do those technology options serve internal and external stakeholders? Are stakeholders empowered to access enterprise data via open data portals? Making their own web maps using authoritative agency GIS data? Inputting information into centralized systems and deriving near instant feedback/insights? Or are they being forced to request data and analysis through a single channel bottle neck, overwhelming IT staff with frequent requests.


When assessing current state, consider the following:

  • Create a data inventory
    • What are your current data themes?
    • Where are data stored (database/spreadsheet/cloud SaaS)
    • Data access (are the data easy to get to and if so, are they structured or unstructured?  Does their schema change each year?)
    • What is the update frequency for a piece of data
    • Is the data external to my agency?
  • What are the key business units and what are their reporting needs?
  • Develop key performance indicators (KPIs)/measures and determine how well the data from the inventory aligns with those KPIs
  • What is the current data culture and governance like?
  • Where do you fall on the data maturity scale?



Where would you like to be?

  • Near real-time analytics
  • Automated data integration and quality checks
  • Self-service dashboards
  • Data savvy business users who feel empowered by the systems you create


What are you lacking?
Conduct a gap analysis. Are you missing data, systems, or policies that will help drive a data-driven culture?

  • Personnel – Do you need additional staff? Need to train existing staff?
  • Technology – Do you need to license, procure, or build additional software to help deliver value?
  • Assess if business units have buy-in and trust IT to help
  • Is there funding? Are their avenues to pursue new funding?
  • Do we have quality data? If not, how can we fix that.


Make a Plan
It is going to take time to achieve the goals you lay out via this analysis. As you write out the roadmap seek to highlight outcome-based deliverables along the way to keep business units and executives interested. Try to identify the highest business value areas first, particularly those that have an external impact such as informing or providing data services to the public.

Keep the following in mind when developing the plan:

  • Executive level support of data culture amplifies the success of a data strategy
  • Keep a clear vision of the ultimate goals for the project so that the business value of the initiative can be clearly reiterated if you hit challenges along the way and need to boost morale
  • Data teams excel with diverse skillsets – Keep your team trained and engaged, look for data champions (on the IT and/or business side) that will help push the project forward


How Timmons Group can help
Timmons Group has years of experience conducting GIS and enterprise data road maps and has assisted many government clients with helping to shape a data strategy. At the end of the day it will the agency itself and the people working there who uphold a data-driven culture.  However, Timmons Group can assist along the way and identify where we can best plug in to help you succeed. We have a wealth of data scientists/engineers, technology experts, and consultants on staff and a proven track record with long lasting relationships with our clients.  We excel at helping our clients deliver forward progress within any budget and have a proven approach to develop data competencies over time to transform organizations. Our teams are passionate and knowledgeable about data and we would love the opportunity to work with you!

Also, if this post has piqued your interest, you may also be interested in one of our posts from last year on Data Governance.

For more information about Timmons Group's technology services, visit us on the web or contact Lowell Ballard with any questions.


About the author: Chaz Mateer is a highly motivated GIS professional with considerable experience conducting spatial analysis, data modeling/automation, and creating web GIS solutions. He is a technologist with an environmental science and geographic information systems background with skillsets in programming and web application development. Chaz has experience with the management and administration of enterprise GIS environments (web servers, GIS servers, server-side GIS software, scripting environment, and GIS web applications). He has worked with State, Federal, and private entities to coordinate requirements gathering and analysis for geospatial workflows. In his 7 years of experience, he has planned and documented enterprise architecture and information technology standard operating procedures for previous clients. He has developed custom geospatial solutions for supporting agency-wide situational awareness during exercises and emergencies to include automated mapping, scripted geoprocessing tools, and web mapping applications.