Disrupt is a Dirty Word

Disrupt is a Dirty Word
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When it comes to being reliable, like a business people can count on, disrupt is a dirty word. As your organization is ready to make changes or updates, there’s no need to start over from scratch. Unless, of course, something is broken beyond repair. Chances are, you can’t completely overhaul your infrastructure even if you did want to. To start, it doesn’t make sense to rip out and replace the processes that successfully provide value.  Nor would it make sense — or be financially favorable, assuming it’s even possible — to hire all new resources.

Why not embrace what you already have and figure out how to take it to the next level? Let’s stop aligning innovation with disruption.


Don’t let the fetishizing of disruption hold you back.

Turning a wheel is easier than turning an aircraft carrier. Yet, I consistently hear stories of vendors striding into offices touting the latest technology that will delight and disrupt. Odds are, you don’t actually buy it. Neither do we.

You don’t have to disrupt in order to innovate. In fact, this pressure to disrupt may very well undermine your efforts toward progress and meaningful change.  

Take compliance, for example. The client of compliance is the regulator. Thus, compliance technology solutions (regtech, for short) tend to be very conservative, understandably foregoing innovation in favor of ensuring that the client remains satisfied. We believe this is increasingly a false choice, but it’s a false choice born of institutions appropriately dismissive of “disruptors.” Recent episodes involving Zenefits and Theranos only confirm this instinct.

Often, real and effective change comes from taking existing assets and innovating incrementally in novel, responsible ways you can sustain. 

Read: rewiring, not ripping out the entire infrastructure. The sustainability piece here is key. This is no less true in the private sector than it is for government.


Putting data to work — without disruption

The best approach to driving effective change is to put your data to work alongside your people. People and credibility are arguably your greatest enterprise assets. When you’re looking to use your data most effectively, these two are the best places to start.

Too often, companies approach data projects from a displacement perspective:  you can either use your data or your experience. But the solution isn’t binary. Thinking in terms of either/or can significantly limit progress and innovation.

Respecting — and choosing technology that complements — the real-world experience of your team, however, will pay off in spades.

For example, take Nolalytics, the New Orleans Office of Performance and Accountability (OPA) initiative focused on applying data analytics to solve problems facing city departments and the residents they serve. Often, the insights that inform their projects are derived from data already collected by their department or other public sector agencies. By utilizing data to make small changes in how they work — prioritizing high-impact or easy-to-resolve cases, ordering service delivery in a new way, or changing dispatch protocols — they are able to deliver better results and measurable impact within existing resource constraints.

OPA’s recent initiative to improve EMS response times is an excellent example of leveraging both human experience and data to create new efficiencies. In the past, the city’s ambulance standby locations were chosen based on dispatchers’ habits and instincts as to where they could get to emergencies most easily. However, based on personal experience, teams tend to work with only a limited view of total EMS demand in the city. By streamlining data ingestion from multiple sources, OPA was able to incorporate city-wide data on accidents, hospital transfers, and traffic to build upon the dispatchers’ insights. With quicker access to better information, teams could be deployed more flexibly — and in locations that could significantly reduce response times.

In another important initiative, OPA, in tandem with the New Orleans Fire Department, used existing public data to build a model that enabled far more efficient targeting of smoke alarm outreach. Using the tool, the fire department is now able to prioritize the highest-risk areas to make a large impact without extra patrols, more resources, or disruptive changes. You can read more on the Smoke Signals initiative here and here.

In both cases, OPA was able to put existing data in the context of the real world to solve specific challenges.


Using data to innovate responsibly – what to look for

Data is an enterprise asset whose value often goes unrealized, largely due to solutions-focused approaches that fail to tap the human intuition and experience.

As you take steps to uncover new insights from your data, here are a few things to keep in mind:

  • Focus on a people-first approach. Data is at its best when in synthesis with the people who are supposed to be using it for the benefit of the organization.

  • Embrace your existing technology stack. Is it agnostic and ready to plug into your current infrastructure, APIs, etc.? Are you able to manage and maintain it with your existing capacity? Once you start bringing on more bodies to make technology usable, the added costs are painful and will quickly chip away at the stated value.

  • Once you prove ROI through a manual, people-first process, enlist technology to automate non-decisional processes to create repeatable, scalable insights more efficiently.