When thinking of a supply chain, most of us automatically picture manufacturing production lines or delivery networks. However, in a world that is increasingly going digital, the data supply chain will be critical in all aspects of our lives.
But what do we mean by “data supply chain?” It means thinking about your data as more than a static element. It’s when data becomes something that lives and breathes through the supply chain, where it is created, shared, combined with other data and enriched incrementally, acquiring incremental value along the way.
A recent trip to the pharmacy reminded me how important the use of data is for my health. The sharing of health data between my primary care doctor and the pharmacy is critical to avoid potentially life-threatening risks that can be caused by mixing medications. Luckily, more and more companies, like Walgreens, are providing application programming interfaces (APIs) to allow third party applications to interact with their systems and data. This pharmacy prescription API is designed to increase prescription compliance and aid in personal health management. This not only improves service, but it also provides me, the customer, with better data to make important, informed decisions about my health.
We all know data is important, but in order to maximize the value of data, it needs to flow through the organization, making it visible and accessible to those who need it, when they need it. Consider the field of health security and surveillance, where the data supply chain is essential in the early detection of biological outbreaks. Detection relies on the speed and accuracy of how disparate data sources come together and become actionable, resulting in timely engagement of federal agencies such as FEMA and state and local emergency responders.
In another example, the data supply chain enables early identification of natural disasters. Collaborate.org is an example of an open data source, where its global collaboration platform allows users to view data geospatially—such as satellite imagery and air quality. The state of Hawaii uses Collaborate.org to share data across organizations monitoring environmental risks. These examples show that it’s not just about allowing internal data to flow through the organization; it’s about how internal data is used in conjunction with external data sources that can correlate and enrich our data to create new value from it. We must think of a different infrastructure and data governance in order to be sure we have the ability to treat data in the right way – the most holistic way.
Federal data ecosystems are complex and littered with data silos, limiting the value federal agencies can get out of their own data by making it difficult to access. As a result, federal data is vastly underutilized. Data technologies are evolving rapidly, but many times they are adopted in a piecemeal fashion. To truly unlock that value, agencies must start treating data more as a strategic asset, architecting a data supply chain that enables the data to flow easily and usefully through the entire organization and, eventually throughout the organization’s network of partners, too. Energy conservation, literally, brings this to light. Dr. Ernest Moniz, U.S. energy secretary, declared that energy efficiency will be a focal point for the department during his tenure. He will push for efficiency improvements across multiple sectors of the economy by strengthening collaboration with states and regions, where a lot of activity is taking place.
One such place is the city of Seattle. Seattle wanted to take energy conservation to the next level. They implemented smart building technology, which uses predictive analytics to extend building management systems and optimize equipment for energy reduction. The Seattle Smart Building program is deploying assets that apply analytics to building management data to optimize equipment and related processes for energy reduction and comfort requirements. They are using optimization and fault-detection software that pulls data from disparate building management and control systems driving new opportunities for reducing energy. Energy efficiency efforts, like Seattle’s, are expected to save 10 percent in energy and 25 percent in maintenance expenditures – reducing the carbon footprint and costs.
The implications of enabling the data supply chain are extensive. Our federal agencies now have the opportunity to ingest new sources of data, cross agency data, public data, and data from commercial providers. Then, the manipulation of data through new methods of data discovery further adds significant value. The federal government can now look externally to realize value from data in new ways. It’s time for leaders to start thinking about the entirety of the data supply chain—as an end-to-end process that is outcome driven and matched to strategy. Today, data is more than just an important IT asset; it can be a strategic operational asset helping agencies achieve their mission. Let’s start breaking down silos and treating it that way.