A data strategy defines how your organization will use data to accelerate success. Asking the right questions is a key part of the process.
Over the course of eight years, our dataset went from a single Excel spreadsheet to a data warehouse. It drove our programmatic strategy and helped us achieve our goals.
We used data to deliver impact – to influence policy changes, to create price transparency, to lower the cost of broadband – and to solve the classroom connectivity problem.
When analyzing large amounts of data, you need to evaluate the best tools and systems that will scale as you do.
Learn how even with a small data set, you can influence stakeholders for impact.
We used our annual report to celebrate, compel, and engage with our audience. Small changes can have a big impact.
When leadership prioritizes data-informed strategy, it permeates the whole organization.
Data was our secret weapon. Learn about the phases of our data journey and how it helped us achieve our mission.
Using data to drive results was a force multiplier at EducationSuperHighway and can be for all mission-driven organizations. At EducationSuperHighway, data helped us succeed in three areas:
We started with one question that became the basis of our data strategy: “How much Internet access does every public school in America have?” We knew that answering this question was the key to convincing federal and state policymakers to focus on solving this issue and to developing an effective programmatic strategy to actually upgrade schools. To answer this question, we asked schools around the country to take Internet speed tests. 800,000 tests later we had a dataset that showed that 90% of students had insufficient Internet access – a number that compelled President Obama to launch a national initiative to upgrade America’s K-12 schools.
As critical as it is to develop a question that defines the basis of your data strategy, it’s equally – if not more important – to ask the right question.
If we had asked “How many schools in America have Internet access?” the answer would have been a very high percentage. When we started our work, 98% of schools had minimal Internet access – primarily for casual browsing in their computer labs, or to support teachers’ email systems. By asking instead if schools had enough Internet bandwidth for digital learning, we found the true scale of the K-12 broadband problem.
Demonstrating that 90% of students in the U.S. needed an Internet upgrade catalyzed policymakers to act and helped us understand who needed to be upgraded. However, it did not give us the insights we needed to understand how to make these upgrades happen quickly, cost-effectively, and at scale. We now had to ask a new question: “Who is buying what, from whom and at what price?”
The answers to our second question revealed that affordability was the key problem we needed to solve to upgrade America’s K-12 broadband. Schools were paying $22 per Megabit per second (Mbps) for their Internet access while businesses were paying $3 per Mbps. At these prices, schools could not afford to buy the bandwidth they needed. Fortunately, our second question also pointed the way to a programmatic solution – showing that there was tremendous variability in the price schools were paying for broadband, not just across the nation, but within counties too. We found example after example of neighboring school districts paying dramatically different prices for Internet from the same service provider – sometimes as much as eight times the price!
Armed with this insight, we developed our theory of change – a hypothesis about what actions would result in schools upgrading. Our theory of change was that transparency into school Internet costs could drive the median price down from $22 per Mbps to $3 per Mbps and enable school districts to afford the broadband they needed for digital learning. Based on this, we focused our data strategy on creating price transparency so school districts could negotiate better deals and Internet service providers could find school districts where they could offer more bandwidth for the school district’s budget. We created a website where every school district could see the details of what every other school district was buying and five years later the cost of K-12 internet access had fallen over 90% to less than $3 per Mbps!
Start with one question that, if you knew the answer, would help you accelerate your progress. When you can answer your first question, define additional questions that help dimension the problem. Be sure to ask the right questions and always follow up answers with the question “Why?” If you’ve asked the right questions, the answers will lead you to your theory of change. How you use data to accomplish your theory of change is your data strategy.
At EducationSuperHighway we dealt with many of the same challenges that all nonprofits face in getting started with their data journey, including a lack of available data to answer the questions we cared about. Over the course of eight years, we saw our dataset evolve from manually collected information in a single Excel spreadsheet to a cloud-hosted data warehouse automatically refreshed multiple times a day. The increased depth, breadth, and quality of our data over time enabled us to scale our work across all 50 states (without significantly growing our team) and convince key state and national stakeholders to partner with us to close the classroom connectivity gap.
When we started trying to understand the state of Internet connectivity in K-12 schools, most of the information available was in the form of stories and anecdotes. We learned that in many schools across America, something as simple as loading a video from the web took way too long to be practical. But we had no hard numbers to take to policymakers or set tangible goals with.
We started by looking for publicly available datasets or reports that helped us frame the problem and found “The Broadband Imperative,” published by the State Educational Technology Directors Association (SETDA) in 2013. This report did not have the data we needed, but it did help us define what success looked like for our mission and led us to our first key question: what percentage of students have access to sufficient bandwidth? We adopted SETDA’s recommendation of “at least 100 Mbps per 1,000 students/staff” as a minimum bandwidth target for school districts and set out to determine how many districts were currently meeting that benchmark.
Because there was no existing data source to help us answer the question, we decided to collect the data ourselves. We built an Internet speed test linked to a database of schools and asked schools to test their broadband. This proved difficult to scale at first, but by forming partnerships with state departments of education, we were able to get 800,000 people in 36,000 schools to run the speed test – giving us our first dataset on the state of broadband in America’s K-12 schools. This data helped us convince key policymakers (including President Obama) that we needed to solve the K-12 broadband problem, but it didn’t have the depth of information we needed to actually help us drive those upgrades.
To get the data we needed to help schools upgrade, we undertook another early manual data collection effort, asking school districts using funds from the Federal Communications Commission’s (FCC) E-rate program to send us their application forms. These forms detailed the Internet services school districts were procuring – including the speed of their connections, the cost of each connection, and the vendors they were buying from. While this provided a much richer dataset than the speed tests, our collection process was still entirely manual. Schools sent us their data in PDFs, at times with handwritten notes, which we had to transcribe into a spreadsheet cell by cell. As tedious as it was to collect, this early dataset produced findings that played a key role in convincing the FCC to modernize E-rate and make all E-rate application forms publicly available going forward. This meant that we now had access to annually updated data covering the Internet purchases of virtually every school district in the country. It was a game-changer.
As pivotal as this milestone was for lifting barriers to our data collection, we soon had another great challenge on our hands: the data wasn’t completely accurate (as is often the case with self-reported data). While we now had access to data of the right scope and depth, that didn’t mean very much if it wasn’t trustworthy. Our focus shifted to data cleaning and curation. This meant coming up with rules by which to interpret the data, determining its accuracy, and creating a framework for fixing it if necessary. Over the next four years, we invested heavily in new approaches to clean our data – starting with outreach to school districts and ultimately leveraging machine learning. As a result, we went from just over 50% clean data in 2015 to nearly 100% in 2019.
If we had settled for the data that was available in our first couple of years of work, we would have never been able to understand the barriers driving the classroom connectivity gap in a meaningful way. Likewise, had we not acknowledged and addressed the poor quality of the data immediately after E-rate modernization, we would have struggled to gain credibility with key stakeholders for our data-driven self-service upgrade tools that ultimately allowed us to achieve scale in our mission. Our success in using data to drive action was largely due to consistently looking for new ways to improve our dataset.
Until the end, we continued to refine our understanding of the problems we were trying to solve. This was an iterative process that required a significant investment in resources – both personnel and technology. We dedicated 40% of our budget to data because as the quality and scale of our dataset improved, it allowed for better understanding of the problems, better solutions, and greater adoption of those solutions.
The ultimate goal of your data journey is to drive action towards accomplishing your mission. Here are a couple important principles to guide you through your own data journey:
Many nonprofits use data to measure their impact, often for fundraising purposes. At EducationSuperHighway, we used data to deliver that impact – to convince leaders to act, to drive policy changes, to lower the cost of broadband – and to solve the classroom connectivity gap.
Here are some ways we used data to drive results:
800,000 tests in 36,000 schools demonstrated to governors and federal policymakers that there was a significant problem – 40 million students without sufficient broadband – and provided a specific roadmap for solving it.
Collected and analyzed public broadband data, which enabled us to convince policymakers to implement data-driven policy changes to the E-rate program.
An online price transparency portal highlighted better broadband deals enabling district leaders to upgrade on their own.
Used Salesforce to track the specific districts that needed to be upgraded, allowing us to deploy resources in an effective way.
Annual reports held leaders accountable for their commitments and gave them credit for progress, which encouraged them to maintain the partnerships until the problem was solved
When we began our mission in 2012, school broadband was not an issue on policymakers’ radar. The statistic everyone focused on was that 99% of schools had broadband. The problem was that the typical school had so little bandwidth that 80% of teachers said they couldn’t use technology in their classrooms. We used data to show federal and state policymakers that broadband was a problem they needed to focus on.
In 2012, we launched the National School Speed Test to measure the bandwidth available in every classroom in the United States. We partnered with 30 states, conducted more than 800,000 speed tests, and demonstrated that 90% of students were in schools that had insufficient bandwidth to use technology for teaching and learning. As a result, President Obama launched the ConnectED Initiative to connect 99% of students to high-speed broadband and the Federal Communications Commission (FCC) agreed to modernize the E-rate program. Later, we would use data again to convince 85 governors in all 50 states to join our mission and state policymakers to provide critical matching funds for fiber construction. In every case, leaders were compelled to act because we had data that quantified the problem and showed them how to solve it.
To close the classroom connectivity gap, we needed the FCC to make substantial changes to the E-rate program. This was not a popular point of view amongst the school advocacy organizations and broadband providers who had been the primary voices shaping E-rate policy over the previous 15 years. We used data to win the debate. By investing eight months and a million dollars in our efforts, we were able to collect data from 1,000 school districts showing how they were spending over $200 million of E-rate funding. Our analysis of this data provided fact-based support for the policy changes we were advocating and as a result, the FCC adopted virtually all of our recommendations – including making all E-rate data public. Why did we win? Because we had data and everyone else just had opinions.
When we first began our work in 2012, the cost of broadband for K-12 school districts was exorbitantly high, making it difficult for them to afford enough bandwidth to use technology in the classroom. The typical school district was paying $22 per Megabit per second (Mbps) per month for their Internet access, while businesses and school districts with advanced procurement processes were paying just $3 per Mbps. If we wanted to achieve our mission, we knew we needed to dramatically lower the cost of broadband.
Our theory of change was that transparency into school Internet costs could drive the median price down from $22 per Mbps to $3 per Mbps. Thanks to E-rate modernization, we now had access to data on the broadband every school district was buying and we used that data to create a price transparency tool called Compare and Connect K-12. The tool enabled school district leaders to see who was buying what, from whom, and at what price and then use that information to negotiate better deals with their providers – all without our direct involvement. In essence, the data behind Compare and Connect K-12 drove the cost of broadband down 90% and helped us accomplish the affordability part of our mission without having to deploy additional human capital.
With more than 13,000 public school districts serving nearly 50 million students, we knew we would not be able to offer individual upgrade support to every district. In order to scale our work, we needed to categorize districts based on the type of support they needed so that we could limit the direct service resources applied to each district. Using connectivity and pricing data, we were able to divide districts needing upgrades into one of three groups:
We then designed specific upgrade programs for each category – focusing our human capital on the districts needing fiber connections and leveraging Compare and Connect K-12 and Wi-Fi value-added resellers to address the other two categories. The result: We helped thousands of districts upgrade with a direct service team of just 15 people.
EducationSuperHighway published five annual State of the States reports from 2015 to 2019. Each report used connectivity data from the E-rate program to track progress toward our goal of upgrading 99% of America’s K-12 classrooms and to provide a roadmap of actions key stakeholders could take in the coming year to accelerate the pace of upgrades. The reports were one of the most effective tools we created and helped us achieve our mission. By using data to celebrate success, show exactly which schools still needed to be upgraded, and identify the types of upgrades they needed we were able to:
THE RESULT:
85 governors from all 50 states partnered with us to achieve our mission – setting goals, conducting outreach to districts on our behalf, and providing matching funds to get the job done.
Watch our webinar: Make your data work for you, given by Solomon de los Reyes, Head of Data
Much of EducationSuperHighway’s work revolved around acquiring and analyzing large amounts of data. That data helped us convince key stakeholders to act, drive policy change, reduce K-12 broadband costs through price transparency, and target our programs that helped schools upgrade. It also presented some challenges that forced us to rethink our data systems and tools.
When we began working with data at EducationSuperHighway, our primary tools were Excel and a SQL database. These tools allowed us to get started without having a tremendous amount of data expertise on our staff, and were all we needed to analyze the data we collected manually from school districts in our early years. However, once we convinced the Federal Communications Commission to make all of their K-12 broadband data public, the depth and quantity of our data exploded, making our original tools insufficient.
When it became clear that our early methods for analyzing data would no longer support our data needs, we knew we had to invest in more sophisticated tools and processes. We started by defining the major pain points we were experiencing:
We addressed each pain point as part of a four-part technical and procedural overhaul:
If you are concerned your organization is drowning in data we suggest interviewing all your data stakeholders – including analysts and end users – to better understand their needs and challenges. Once you can identify some of the major pain points, consider not just introducing new tools and processes but eliminating and reducing tools as well.
If you answered “yes” to any of these questions, your organization may want to consider scaling your data systems.
In order to close the classroom connectivity gap, EducationSuperHighway needed to use data to influence stakeholders and drive change. We started with a focus on federal policymakers to increase K-12 broadband funding and obtain comprehensive data on the broadband school districts purchased. We then used this data to convince state and school district leaders they could upgrade their connections.
Early on, we learned that the Federal Communications Commission’s E-rate program, which funded over 70% of the cost of K-12 broadband, needed to be modernized if we were going to accomplish our mission of upgrading all of America’s K-12 classrooms. The program needed to increase funding for broadband, prioritize fiber connections, lower the cost of broadband for schools, and ensure every school had the resources to deploy Wi-Fi networks. We used data in two ways to make this happen:<
Our data convinced the FCC of the importance of maximizing the impact of the E-rate program. They soon decided to make all E-rate application data publicly available for the first time. This provided us access to itemized data about what services schools were buying, who they were buying from, and how much they were paying for Internet services.
Armed with this information, we were able to accelerate the pace of upgrades by influencing state and district leaders.
With the availability of national E-rate data detailing the broadband services every school district was purchasing, we turned our attention to convincing governors to make K-12 broadband upgrades a priority. Our strategy was part carrot and part stick. First, we used the data to show them exactly which schools needed to be upgraded, which made it clear that this was a goal they could accomplish (especially with the availability of new E-rate funding). Second, we let them know that we would be publishing every state’s K-12 broadband statistics annually in our State of the States report. We then made it easy for them to commit to taking action by simply making a public statement that upgrades were a priority for their administrations. This data-based strategy was tremendously successful. 35 governors committed to upgrading all the schools in their states in our first year and over the course of five years, 85 governors in all 50 states made the same commitments.
We also used E-rate data to influence other state policymakers. In order to achieve our goal of getting fiber built to 99% of school buildings, we needed to convince nearly half the states in the country to put up state funds for fiber construction. Using the data on which schools lacked fiber connections, we were able to show which schools in their districts were impacted and the amount it would cost to connect their schools. This analysis made it easy for the legislatures to say yes to providing matching funds as it showed them the need to invest to create equity across the state. It also gave them a win to talk about in their districts and provided comfort that the state could afford the request in their budget. As a result, nearly every state provided the matching funds needed to connect their schools to fiber.
Finally, we used data to keep state leaders engaged in our mission. Every year in our State of the States report, we created a “state snapshot” for each state summarizing its performance against the FCC’s bandwidth goals. The snapshots showed the number of schools and students connected each year, the amount the state had reduced the cost of broadband and the total E-rate funding they had received. This gave state leaders the data they needed to celebrate progress (which we helped them do) and allowed them to compare their progress against other states (governors love a friendly competition). Most importantly, the snapshots kept governors and their teams motivated to finish the job and act as our distribution channel to districts for our data-based strategies to convince them to upgrade.
The last layer of our stakeholder engagement was with individual districts. Our basic strategy was to show district leaders that they could get the broadband they needed without spending more money.1
To implement this strategy, we created Compare and Connect K-12, a price transparency tool that showed what broadband services every school district was buying, from whom, and at what price. For each district, the tool also showed other districts in their area that were spending similar amounts and getting more bandwidth. This allowed district leaders to quickly identify service providers that could give them more broadband for their budget as part of an upgrade. We then conducted extensive email campaigns in partnership with state departments of education highlighting to districts and service providers that these deals existed in order to spur action. The results: Two-thirds of districts visited the tool, the cost of K-12 broadband declined over 90%, and 99.7% of districts upgraded to the FCC’s bandwidth goal.
Using data to make friends and influence people is more than a numbers game. It requires a combination of relationship building and data-driven persuasion. We recommend:
Many nonprofit annual reports are written for the benefit of funders. They tell the story of the amazing work an organization has done each year, the impact that has been created, and the work still left to do. The goal is to educate donors so they continue to support the organization. At EducationSuperHighway, we focused our annual reports on the people we needed to take action in order for us to achieve our mission. They still accomplished the job of keeping funders engaged with our mission but were even more pivotal in driving the success of our programmatic work.
EducationSuperHighway published five annual State of the States reports from 2015 to 2019. Each report tracked progress toward our goal of upgrading 99% of America’s K-12 classrooms and provided a roadmap of actions key stakeholders could take in the coming year to accelerate the pace of upgrades. They were one of the most effective programmatic tools we created and helped us achieve our mission by:
Who is the report for? What do you want to convey to the audience and what actions do you want them to take? Written for state leaders and school districts, our State of the States reports detailed national and state progress in upgrading the Internet in K-12 classrooms. But the reports were also calls to action about the work that still needed to be done – with specific steps we wanted state and school district leaders to take.
For example, in our final 2019 report we celebrated the completion of our mission, and set a new goal for state and school district leaders. We detailed the steps that had been taken to connect 99% of America’s schools to fiber and over 46 million students to the bandwidth they needed to begin using digital learning in the classroom. More importantly, we leveraged the report to get the K-12 broadband ecosystem committed to the Federal Communications Commission’s new 1 Megabit per second (Mbps) per student standard that would allow digital learning to be used in every classroom, every day. We did this by making the case for why the goal was important, showing that districts of all sizes had already achieved the goal and detailing how the same strategy used to complete our mission could be used to achieve this new goal. We then used the report’s publication deadline to obtain commitments from an additional 22 governors to the goal – giving them the opportunity to be seen as leaders and ensuring their states would help drive progress in the coming year.
One of the key objectives of our annual report was to hold federal, state, and school district leaders accountable for solving the K-12 broadband problem. However, we knew that success was a better motivator than failure, so our approach to accountability started with celebrating the progress that had been made rather than focusing on what was still left to do. This made leaders feel good about our partnership and ensured they brought open minds to the discussion of how they could take action to connect the students who still lacked broadband.
For example, one of the primary goals of our 2016 State of the States report was to hold governors accountable for closing the fiber gap and convince them to provide matching funds for fiber construction. We began by celebrating the fact that state action had already increased the percentage of schools with a fiber optic connection from 71% to 95%. Then, we demonstrated that a lack of funding was the primary barrier to connecting the remaining schools and that governors could solve this problem by putting up matching funds for fiber construction. This started conversations in state houses across the country. Within two years, 23 states — covering the vast majority of schools that needed financial support — had established matching funds.
Government leaders want nothing more than to make progress on the issues facing their communities. It’s one of the main reasons they go into public service and it’s what they will be evaluated on when they run for re-election. By giving policymakers credit for the progress being made in upgrading their schools in our State of the States reports and then investing in PR to get the press to write about that progress, we were able to make K-12 broadband a “winning” issue for government leaders. This not only kept the issue at the top of governors’ priority lists but helped convince other governors to join our mission. As a result, nearly every governor elected since 2016 made upgrading their K-12 schools a priority for their administration.
Creating our State of the States report was a four-month process each summer. While this may seem like a tremendous amount of time to devote to an annual report, it was the process, rather than the final report, that actually delivered most of the impact on our mission.
Externally, we used the State of the States report creation process to engage governors and their staffs. Two months prior to the report being published, we began sharing data with governors’ offices in the form of a “state snapshot” on the progress they had made upgrading their schools in the prior year. This gave them a chance to ask questions about our data and also catalyzed conversations about what they could do in the coming year to keep the momentum going. It also gave us the opportunity to ask them to recommit to the mission through a public statement by the governor to the press. It was a tremendously successful strategy that also ensured they received credit for the progress being made.
Internally, we used the reports as an additional way to engage our staff and reconnect them to the organization’s mission. Nearly everyone in the organization had an opportunity to participate in the reporting process and this encouraged everyone to reflect on how their actions and goals aligned with our mission. In doing so, we created buy-in and strengthened our commitment to achieve our goals in each consecutive year.
Many nonprofits only make their annual reports available online as downloadable PDFs. We did that, but we also invested in creating separate digital versions that told the story in a concise, mobile-friendly way. The website provided quick access to national and state-level statistics and headline conclusions, while leveraging video content to show the human impact of the work. Because the digital experience was engaging, it generated more media attention than we would have received with a traditional press release and PDF. We also made the digital version the focus of our promotional efforts across our digital marketing channels, which significantly increased the number of people who engaged with our report.
Creating and executing a successful data strategy cannot be done without buy-in from senior leadership. If leveraging data isn’t a priority in your organization, it will be tough to get the resources you need to implement your data strategy, and it will be hard to convince others to spend time on the detailed, iterative work required before a data strategy bears fruit. Equally critical, if senior leadership doesn’t place data at the foundation of their decision-making processes, it’s unlikely that the data culture needed to make data a force multiplier through your organization will take root.
At EducationSuperHighway, data was a top priority and we invested heavily in it; up to 40% of our annual budget was allocated for data-related spending. While some of that funding was for data acquisition and tools such as Tableau, most of it was for people – our engineering and analysis teams. At our peak, we had 25 analysts, engineers, and data scientists helping us leverage data to achieve scale in our advocacy and programmatic work.
Without the support of senior management, we never would have been able to invest so heavily in our data strategy. However, we didn’t start there. In the beginning we started with a single staff member focused on data – a former management consultant with great Excel skills. As our data strategy produced results, we went back to senior management and made the case for more resources.
Leadership buy-in doesn’t begin and end with a CEO’s budget allocation. Executing a data strategy requires a great deal of work, a lot of which doesn’t produce much impact. Leaders throughout the organization must be willing to give staff the time and space they need for that work – an iterative process that includes mistakes, failures, and course corrections until you figure out how to leverage the right data in the right ways to execute your organization’s data strategy.
At EducationSuperHighway, one of the key components of our data strategy was our annual State of the States report. We used this report to celebrate the progress that states had made connecting schools in the previous year, hold governors accountable for continued progress, and identify the key actions that states needed to take in the coming year to accelerate upgrades. Developing the action plan was a months-long effort that required our data science team to conduct hundreds of analyses to understand what the key drivers of upgrades had been in the prior year and which of those could be applied at scale during the next upgrade cycle. Ultimately, less than a dozen insights mattered, but we wouldn’t have found them without the time and space provided by senior management to pursue hundreds that didn’t pan out.
To maximize the impact that data has on your mission, leadership must also establish a data culture in the organization. Data is only impactful if it is consistently used to make decisions and if everyone in the organization is thinking about how to leverage data to be more effective. Senior leadership must model these behaviors if they want them to take root in the organization.
At EducationSuperHighway, our data culture started at the top. Our CEO’s favorite question in any meeting always came down to “what does the data say?” and he was deeply involved in our analysis work from day one. Over time, this set an expectation in the organization that any proposal or decision needed to be supported by data and consequently, “what does the data say?” became a common refrain in almost every meeting – with or without the CEO.
By allocating budget, giving your data strategy time to develop, and modeling the behaviors needed to establish a data culture, senior leadership can pave the way for data to be a force multiplier in scaling your organization’s impact through advocacy and programmatic work.
Data was EducationSuperHighway’s secret weapon. It enabled us to convince stakeholders to act, create policy change, and accelerate the implementation of our programs. But before any of this happened, we had to make our data accessible to everyone in our organization so that every team member, regardless of role, was comfortable using and talking about data.
Our first forays into making our data more accessible involved Excel and Google Sheets. Our simple objective was to give all members of the organization the opportunity to see the available data and filter it as they needed. We were still improving the quality of our data and finalizing the types of metrics we wanted to collect, but we didn’t let that hold us back from sharing what we had so our team members could start thinking about how to use it to drive our mission.
As the organization’s appetite for data grew and our analysis team became more sophisticated, we tried a few different tools to make the data in our databases more accessible. We used a tool called Mode to create reports in which non-technical team members could refresh and download the latest data themselves. This allowed our marketing, consulting, and partnerships teams to make quick decisions based on real-time data. Later, we began to use interactive web apps such as Shiny to automatically refresh data, customize views, and create visualizations that enabled our colleagues to follow high-level trends.
While these new tools made the data in our databases more accessible and useful to the organization, they still required an analyst to build the applications and did not give our colleagues the ability to easily manipulate the data to answer follow-up questions. The good news was that data was becoming integral to everything we were doing at EducationSuperHighway. The bad news was that our analysis team became a serious bottleneck. To address this, we took another step in our data journey.
Our big breakthrough was the introduction of Tableau, a tool that allowed us to provide our team with self-service online dashboards. Tableau was a game changer for both our analysts and the people who used the dashboards they created. For our analysts, Tableau shortened development cycles, made it easy to create and iterate on data visualizations, and enabled us to utilize standardized metrics across dashboards. For the rest of the EducationSuperHighway team, Tableau ensured that the data they used was always up to date, gave them the ability to ask and answer follow up questions and let them customize the visualizations they needed without waiting for an analyst. The net impact was a dramatic increase in how we used data to drive our programs without a meaningful increase in the size of our analysis team.
To achieve this impact we adopted two best practices across the organization. First, whenever data requests came in from a team or individual, the analyst team would ask itself, “Does an existing dashboard address this? And if not, should we add this to an existing dashboard or create a new dashboard?” Our goal was to identify which requests were likely to be re-requested so the analyst team only had to do the work once. Second, we provided training and supporting documentation to the organization. We included data dictionaries in spreadsheets, set up training sessions to introduce new dashboards, and coached team members on how to talk about new metrics and methodology changes externally. This ensured that the organization got the most out of the data available to them and that our team members could answer any questions from our partners.
Making our data and data tools accessible helped our team members work better and faster. By giving everyone the tools and confidence to answer their own requests, staff were able to find and use the right data for their work. It also meant that everyone could access the data they needed without having to wait for help from an analyst. As a result, we needed fewer analysts to execute our data strategy and our analysts had more time to work on higher-level problems.
Making data more accessible can be done in many different ways; there is no one-size-fits-all solution. The goal is to make your data easy to access and understand so that everyone at your organization can use it. We recommend:
