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Washington, D.C.’s Chief Data Officer Shares his Vision for the City’s Data Makeover

Barney Krucoff, Washington D.C.’s first ever Chief Data Officer, has his sights set on improving the data capacity of one area of city government in particular: business intelligence.

“Business intelligence is sort of the wild west within the government,”
“We want to make sure the Office of City Administrator has the tools and data it needs to hold agencies accountable for performance,” Krucoff said.

Read more about how this data progressive, Chief Data Officer, is addressing Business Intelligence here:

http://www.govtech.com/people/Washington-DCs-Chief-Data-Officer-Shares-his-Vision-for-the-Citys-Data-Makeover.html

Be Pithy. A Woman’s Guide to Being Direct.

 

Back in the early 2000s, I was cutting my teeth as CEO of a tech consulting company that worked exclusively with public sector organizations. Needless to say, I became intimately familiar with what it feels like to be a female leader in a male-dominated field. Literally every single CIO and CTO I met with was male.

Over the years, I struggled mightily to position my company as a major player in the industry. Even as I listened to customers’ challenges, exuded empathy, and presented our solutions, I kept being told that I’d be better off becoming a go-to subcontractor of larger, better-known vendors.

Looking back, I wish I had stayed the course in directly communicating why my company could do a better, faster, and more cost-effective job than the big boys. But, all told, this was a great learning experience for me — one I feel every woman in the working world could learn from. Read the full article here.

http://www.blogher.com/ask-what-you-want-importance-being-direct

What Makes the List for Your 2017 Strategic Plan?

The Need for Governing Intelligence

A focus on making data accessible across the enterprise is the basis for organizational wisdom

This article in Governing Magazine highlights what should be at the top of your organizations 2017 Strategic Plan. Eliminating Data Silos will save you technology infrastructure costs while at the same time illuminating what could be critical decision making and planning for the future or your organization. A great read below:

http://www.governing.com/blogs/bfc/col-accessible-data-governing-intelligence.html

 

Three Ways Texas is Leading in Transparency

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3 Ways Texas’ Approach to Transparency Offers Significant Gains

Successful transparency portals don’t just provide information; they share it in a way that educates and empowers citizens. One state making headway toward a solution is Texas. Check out what they are doing in our latest Government Technology magazine and how Mo’mix MyGovCenter can help your organization share information that matters to those you serve.

As seen in Government Technology

 

The Future of Government Transparency

Beyond the Data Dump

Governments at all levels are finding better ways to provide fiscal transparency. But there’s a lot more that they could do.

We are honored to be adding to the conversation with our article for Governing Magazine this last week on the Future of Transparency and Engaging with the Public. Check our the article written by our CEO, Erin Latham.

http://www.governing.com/gov-institute/voices/col-fiscal-transparency-open-data-checkbook-portals-predictive-analytics.html

 

3 Ways Government Can Better Manage Their Finances

Our latest Gov Loop Article:
When governments can’t glean useful insights from their mountains of data, it’s nearly impossible for them to build anything that resembles an effective budgeting road map.

Tech-driven strategic methodologies and cloud-based applications brought us into this era of big data, and they can also help us thrive within it. Here are three potential solutions to the public sector’s budgetary issues:

Click here for their full article: Gov Loop-3 Ways Government Can Better Manage Finances

Data Hoarding an Expensive Habit

Our latest Governing article found here: Governing Article Link

Mo’mix article: Government’s Troublesome Data Hoarding Habit Published February 9, 2016 in Governing Magazine
Those of us who have seen the reality show “Hoarders” have watched in amazement as people try to justify the large collections of junk they’ve amassed over the years. What many of us don’t realize, however, is that governments at all levels are hoarders as well.

Long before corporations embraced big data and business intelligence, the public sector was on the case, collecting mountains of data with hopes of finding efficiencies, making service improvements and bettering the lives of constituents. This type of data hoarding follows the old logic: It’s better to have something and not need it than the reverse. But if government agencies aren’t careful, this hoarding habit could result in an uninhabitable, unproductive operation — just as it does for the hoarders we see on television.

Government databases are filled with everything from traffic data to pet-ownership statistics, and many agencies lack the necessary staff and infrastructure to maintain and analyze all of this information. Public-sector data analysts report that they spend 47 percent of their time collecting and organizing data but less than a third of their time actually gleaning actionable insights from it.

A primary cause of government data hoarding is the public sector’s fragmentation: Data is segregated into specific departmentalized systems and in most cases cannot be compared or analyzed across entire organizations. As a result, analysts are forced to run multiple reports from each system and manually combine all of the data into spreadsheets. It’s a time-consuming and error-prone process that many refer to as “Excel Hell.”

Rather than accept this crowded and arduous data approach as reality, organizational leaders need to adopt strategic plans for the future that streamline the collection, storage and analysis process. In other words, governments must learn how to quickly identify and sort good data and bad data. They can adopt a number of effective approaches, and doing so will pave the way for greater accessibility, better analysis and major financial savings. The federal government ended up saving more than $1 billion when it opted to shut down 1,200 of its data centers with hopes of eliminating not only data duplication but also fragmentation and waste.

A good strategic plan should have the ultimate goal of aligning objectives with key results or outcomes in the most efficient way possible. Identify exactly which data will shine light on the organization’s particular objectives and then establish an ideal time frame for the extraction of that data. When reporting historically, going too far back in time can skew analysis due to changing economic factors (among other things). It is important to be able to compare apples to apples, so organizational leaders must maintain a strategic plan that determines what data is still relevant and what should be archived. Setting this timeline also develops an enterprise-wide common understanding of priorities and goals. You’re no longer measuring for measurement’s sake.

One county government was seeking to better understand its workforce spending, particularly its overtime trends. While the organization’s payroll information was housed in one system, its time-keeping information was on another, making it virtually impossible to extract relevant information from the noise. The hoards of data elements, combined with the “Excel Hell” of sorting through it all, was inefficient and ineffective.

By identifying and extracting just the historical and operational data that mattered most, the county was able to systematically filter out its unneeded data. As a result, not only could the county identify a payroll pattern but it could also gain actionable intelligence on how to plan for the future and achieve its strategic objectives. Today, instead of keeping every component of a payroll and time transaction, the county keeps only the relevant data that’s aligned to retention regulations.

Data is crucially important, but only if it’s current, relevant, of high quality and easily accessible. Keeping everything that’s collected “just in case” is seldom a good idea, as going too far back in time will likely only result in outdated, inaccurate analysis. That alone is the strongest argument for governments to get out of the data-hoarding habit.

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