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08 Sep 2016
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The Eastman Kodak Company revolutionized the photography business when they created the first digital camera in 1975. As an avid landscape photographer, I was quickly amazed at the possibilities revealed through the digitization of our world through photographs. There would be no more clunky bundles of film containers, just beautiful 1s and 0s.
But sadly, in 2012 Kodak announced it would stop making digital cameras. After 125 years in business, they were unable to fully leverage their own precious creation to its full potential—lacking the ability to fully integrate their invention with the rest of the world. The winners in this battle were able to liberate our photos from separate devices, and allow us to share our masterpieces (and a few selfies) with the world at the click of a button.
Many entities are facing a similar dilemma with their antiquated methods of storing and using data. Their data (like those photos taken with the first digital cameras) sits in redundant locations, unshared, incomplete—its potential limited. For example, many entities maintain some form of GIS data for inventorying their stormwater infrastructure but they do not take full advantage of the data. Often, their data is developed, stored, and used with a single objective in mind. In fact, sometimes, multiple databases are created for the same stormwater infrastructure to serve separate functions, rather than finding ways to combine the datasets. This results in neither database being able to reveal the full picture. In limiting data requirements and database structure to solely meet a specific policy or project need, they miss out on being able to fully leverage that data for decision making and other functions, such as capital improvement planning, asset management, hydraulic analysis, etc. They will also miss out on inexpensively collecting additional key data that can expand decision-making capabilities in the future.
This siloed approach to data collection and database management is doomed to stagnation. But what is holding us back from making sure our valuable data can serve us well in the future? Why are we falling short when it comes to database planning to make sure we have options, flexibility, and adaptability in the future?
When we collect and digitize data with multiple end-purposes in mind—whether it is floodplain data, information about a city’s transportation system, elevations of a subsurface utility, or soil characteristics from a geotechnical boring—we open up a million possibilities to better understand past problems and predict future outcomes to better serve our communities and our residents’ well-being. We can save vast amounts of time and resources and make connections that we wouldn’t have been able to make otherwise. And when that data can be shared, repurposed, updated, and integrated with other systems, it can offer us an even more complete picture of our world. At its best, you might imagine a complete model of a city, where all of the infrastructure and landscape is visualized in 3D and you can zoom into any desired component—a model that allows you to gather updated data and test various scenarios—this is what a liberated database looks like. This is what it looks like when a database comes alive.
The good news is that this type of database doesn’t have to be an expensive proposition and is not out of reach for most cities. With some simple planning and visioning activities, we have an opportunity to further leverage our existing data and refine business processes to enhance the usability and functionality of the data. We can create relational geo-databases that can be used for multiple functions rather than a single objective. We can create “living” databases that are adaptable for multiple foreseeable functions that help maximize value from public expenditures to better manage our infrastructure, improve water quality, streamline transportation, and safeguard vulnerable communities, amongst many other possibilities.
So what is needed to create this kind of living database that can thrive and respond to its organization’s demands? First, you must recognize the problem and how much it is costing you in terms of lack of insight and usability. Next, it’s a matter of taking small steps in the right direction consistently and joining forces with the right players. It is important to work across agency lines and collaborate with different entities and stakeholders.
Through past experience, we’ve found that an internal champion, passionate about the cause, who helps push for this data-based future is critical to a project’s success. Further, with implementation or use of any new technology or system, the process is most effective when those who will be using the system also take primary ownership since they will be the ones putting it to use. This sense of ownership evolves when users, managers, and developers of the system collaborate and work together at the beginning of the process to define intended uses of the system in context with day-to-day operations, procedures and future needs. This should not be a process undertaken by a single department, but rather it should engage multiple departments and parts of the organization to co-create their living database. This is truly how cities realize significant ROI through their data.
With the right stakeholders engaged in the process, the next step is to conduct visioning exercises—outlining user needs and mapping out existing workflows and business process. It’s important to get clear understanding of the data you have (as well what data you don’t have) and what it can be used for. Take some time to imagine all of the possible future applications and potential end products. While there is no way to know exactly what an organization’s future needs will be, by the end of this process, you will have a solid list of possibilities that can be built into the system. Even without having the desired data in hand, by keeping these future needs in mind, specifications can be developed for the minimum systems requirements you’ll need once you do get there. From these basic requirements, it’s possible to start very lean and build an increasingly robust system as you go—incorporating your existing data into the new database.
At a minimum, the living database should provide a snap-shot of the current state of the data, be able to easily incorporate regular updates as new data is collected or available. It should have the ability to maintain and recognize inherent relationships between different types of information stored. It should provide the analytics necessary to support informed decision-making. Ultimately, it should save time and money by serving multiple purposes for multiple users.
An important point to remember is that any database, no matter how many bells and whistles it may have, is no better than the data it contains. The data is the star, just as the subject of any photo is its star. And doesn’t our data deserve better? At Atkins, we’ve helped our clients develop numerous databases and understand the potential value of data and the types of information needed to support complex decision-making. We also recognize that in collaborating with multiple stakeholders, we can offer our clients complete solutions that solve multiple data and decision needs well into the future. It’s never too late to give our data the living database that it deserves.
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