Government Data Unbound

GovTribe gives government contractors a simple interface to find and track contracting opportunities.

GovTribe CEO Nate Nash and his two co-founders were consultants in Deloitte’s federal government practice where they spent hours each week poring over contracting information. They were frustrated that there was no easy way to track particular contract solicitations or categories of contracts through the lengthy acquisitions process, which resulted in contractors and consultants spending far more time on busy work.

Contracting data was open to the public, but it was scattered in so many places on difficult-to-search websites that even skilled searchers often missed notices they were interested in.

The trio left Deloitte in 2012 and began building technology that scrapes data from a slew of federal contracting sites, including the Federal Business Opportunities website, the System for Awards Management site and contract dispute documents from the Government Accountability Office. The team then built iPhone and iPad apps around that data that allows users to search for contracting notices by keywords, track particular solicitations and receive alerts when a solicitation changes.

GovTribe sells subscriptions to all the data offered through the tool for $5 per month. The team also produces custom reports for a negotiated fee.

“We did a lot of heavy lifting up front on the tech side so we wouldn’t have to do as much manual cleaning of the data as our competitors do on the back end,” Nash said. “That means we can operate at a lower price point.”

Nash credits the government with making strides in putting more information online, but faults agencies for not doing nearly enough to make that information easily searchable and machine readable.

“It’s government’s responsibility to make this data as easily consumable as possible, especially by machines,” he said. “From there forward, anyone can innovate on top of that data.”

• Government data’s value isn’t in the data itself but what you do to it, how you turn it into something valuable for companies or consumers.
• Government data can be dry, so it’s good for an entrepreneurial company to have an edge, “a bit of personality, something that makes your brand and your product matter, that shows you’re not a nameless monolith that will spit out hard-to-read reports.”

iMedicare crunches all the data on seniors’ prescription drug costs so pharmacists can help them choose the right Medicare plans.

Pharmacy student Matthew Johnson noticed something interesting during his residency rotations. Independent pharmacists spent a lot of time helping seniors work through their Medicare options but had little training and few tools to guide them through the tangled process.

Johnson shared his stories with a friend, computer programmer Flaviu Simihaian, and it sparked an idea. After touring more than 200 pharmacies, the pair came up with iMedicare, which takes in a list of seniors’ prescription drugs, calculates the most common prices and reimbursements for those drugs and produces a recommendation for the best Medicare and Medicare Part D plans.

That sort of advice can be particularly hard to work out on paper because of the “donut hole” in Medicare Part D coverage. The team is working now on adding so-called Medigap plans to their calculator. Those are private insurance plans that supplement Medicare.

Simihaian and Johnson sell the tool mostly to independent pharmacies for $1,400 per year.

iMedicare runs on Medicare data and also on data from non-govermment groups that analyze likely drug prices. The iMedicare team spends a lot of time cleaning data so their tool can easily consume it, but Simihaian said the best thing government could do to improve their product would be to release more data. If the Centers for Medicare and Medicaid Services released cost data for what insurance companies reimburse pharmacies for particular drugs, he said, iMedicare could rely less on estimates and would give much more accurate information.

• Look for inefficiencies and find ways to solve them. You can do a lot of cool things with data, but if you’re not making life easier, no one’s going to buy your product.

Panjiva offers companies with global supply chains intelligence on which international suppliers are most popular among their peers.

Panjiva co-founders Jim Psota and Josh Green wanted to help companies make smarter decisions about global sourcing. Their original plan was to do this through eBay style reviews. When they went looking for official data to validate those reviews, however, they realized they had stumbled upon an even better gauge for which companies are the best suppliers of a given product—the ones other companies are buying from.

Panjiva is built with import and export data from the U.S. Customs and Border Protection bureau, which isn’t available online. Panjiva pays to have that data overnighted on CD-ROMs. It also purchases data from some other U.S. government agencies through resellers and export data from other nations, including China and parts of Latin America.

Panjiva customers pay a monthly fee beginning at $99 to view profiles of product buyers and suppliers around the world, including the most popular suppliers of a given product and which companies buy from them.

The bedrock of Panjiva’s business—U.S. customs data—is only open in the broadest sense of the term. That lack of transparency, however, is also the company’s competitive advantage, because it’s willing to do the hard work of acquiring and crunching through that data when other companies aren’t. One example of the value the company adds is that the U.S. Customs and Border Protection bureau is now a Panjiva customer, effectively buying back its own data in a cleaned up form.

• Start with a problem you want to solve and find the best way to go about it. The data should be secondary.
• Keep it simple. Don’t over-engineer a data solution just because you can.
• Start small and iterate, getting feedback along the way. Otherwise you may spend months or years building something that doesn’t speak to what other people are interested in.

WeMakeItSafer.com is a platform where businesses and consumers can search for recall data on food, toys, electronics and other items. They can also register products they own and be alerted if they’re recalled.

Founder and CEO Jennifer Toney launched WeMakeItSafer in 2006, before any major push to put raw government data online. Toney had previously worked as a litigation consultant for companies facing product liability suits. One day she realized a recalled food product she’d been brought in to discuss was sitting at home in her refrigerator and it occurred to her that there’s no way for most companies to alert consumers about recalls. Methods that do exist, such as FDA press releases, tend to use a megaphone approach that is unlikely to reach most consumers.

At first, Toney’s team laboriously translated recall information from government press releases into in alert system and used computer learning technology so the system could transfer recall information itself and correct for common government errors. Now, most of WeMakeItSafer’s data is culled directly from websites managed by the Consumer Product Safety Commission, the Food and Drug Administration, the Agriculture Department and the National Highway Transportation Safety Administration.

WeMakeItSafer offers free searches to consumers for product recalls stretching back to 1999 and allows them to register for alerts when products they own are recalled. The company also helps companies register consumers for recall alerts through their own websites. WeMakeItSafer runs a paid service for retailers and secondary sellers to monitor their entire inventory for recalls. Those plans begin at $29 per month.

The difference between recall data available today and in 2006 is “night and day,” Toney said. But government hasn’t found a happy medium between simply making data available to outside developers and building its own public information portals. There’s also not an easy, standard way for data consumers to ask questions of government data producers so they’re sometimes left guessing what particular data entries mean or whether something is a mistake.

• Make sure you understand the data you’re working with inside and out. Don’t make assumptions about its quality, its history or how it was gathered.
• Know the problem you want to solve before you set out. Don’t just try to build an app around some cool data you found.