Putting Data to Work


I’m not a technologist. I’m a problem solver with an unrelenting focus on data and data analytics – there’s always a job that needs to be done, and to get it done, you need data.

I started my career as a prosecutor and have worked in a variety of dynamic environments where organizational challenges impede the mission.

But for the last decade, I’ve been working with organizations of all types to help them operationalize data and solve real problems to move the dial forward in a real way.

Most notably, and definitely most publicized, was my role as Chief Analytics Officer (CAO) of NYC under Mayor Bloomberg. My job was to own the data problem as an intelligence resource and morph data into a true enterprise asset.

As the founding member of NYC’s Mayor’s Office of Data Analytics, I helped to “liquefy” both proprietary and public data / intelligence to transform city operations like public safety, public health, finance and economic development.

Mike Flowers Lr

We identified meaningful data. We broke down silos across 40 agencies. As a result, the Bloomberg Administration intelligently coordinated the work of New York City’s 300,000 employees and $70 billion annual budget. It was a big success and a model that bears repeating for any municipality or enterprise.

In my current role as CAO of Enigma, I continue to advise people who recognize the tremendous opportunity to put data to work as a reliable enterprise asset. It’s simple, really: with data “on tap,” you can achieve better outcomes.

Case in point: London, which is now piloting a program to establish a London Office of Data Analytics (LODA), similar to what we did in NYC. But consider this: NYC has 5 boroughs, all centralized under the Mayor’s office. London has 33 however, they operate on their own, autonomous when it comes to trash, tax collection…everything. Right now, London has little systematic pooling of data or information sharing, beyond its successful open data portal.

But that’s about to change, thanks to Eddie Copeland, Director of Government Innovation at Nesta, a U.K.-based innovation charity, and Andrew Collinge, Assistant Director at the GLA. They’re working together to demonstrate that analyzing data sourced from multiple local authorities and public sector bodies can help reform public services in the capital. I’ve been lockstep with them on the project, advising on how to adapt the model that worked in NYC for a UK context.

The low-hanging fruit project they’re tackling? Identifying houses not correctly registered as a “Houses of Multiple Occupation” (or HMOs). Up to 90% of HMOs in some boroughs are estimated to lack the appropriate license. An unregistered HMO can correlate with poor quality or dangerous private rentals, not to mention lost revenue for local authorities.

While suspected HMOs are investigated by teams of inspectors, the hit-rate of finding suspect properties is low. Here’s the thing: it’s a pure data issue. Analytics can help them prioritize in a need-driven way.

I have no doubt that data sharing, along with a cooperative relationship among boroughs, will lead to huge ROI for the government and people of London. By leveraging data as an enterprise asset – just like trucks and personnel and bridges and roads – London will be able to better predict unregistered HMOs and better target inspections. We expect to see higher hit rates of successful inspections with the same amount of resource and more income through a rise in the number of HMO registrations

[Check out Eddie’s blog post, 'Offices of Data Analytics: next steps for London and the North East']

Since I used to be a prosecutor, here’s my closing argument:

Data is an enterprise asset whose value has yet been unrealized because of a Solutions-focused approach. Data is at its best when in synthesis with the people who are supposed to use it on behalf of the organization – be it a city or a corporation. Once you prove the return on investment through a manual, people-first process, then you enlist the technology to help your project take off and truly scale on an enterprise level.

Next week I’ll share more on the London project, with excerpts from a recent conversation I had with Eddie.

Stay tuned. There’s so much more to come. With London. With Enigma. And with the possibilities of putting data to work.