Every public sector agency in California produces, modifies, processes, transforms and reports out on a gargantuan amount of data each year. Policy makers make decisions based on conclusions drawn from those data analyses each and every day. Some decisions are small, others impact billions of dollars of the California economy. The challenge we face is that, to a very large extent, there are few if any true data scientists working for government who are performing detailed data analytics.
In recent months, public agencies have issues a number of reports calling for policy makers to act virtually instantly on the reports’ conclusions. For example, almost every transit agency has seen a fairly steep decline in bus ridership. What’s lacking is real data-driven analysis of this phenomenon. Some proposed causes are intuitive, but no real quantitative work has been done. Nonetheless, policy makers around California are shifting or cancelling bus routes and reducing services dramatically. Detailed analytics on how to reverse these trends: nonexistent. Similar problems impact water agencies, who have targets on water reduction, but beyond, “conserve” and raising rates, little analysis. Pick a public agency, and these decisions are being made daily.
And now we move on to other technology inflection points. We have heard about the “shared economy,” but how will it really affect public transportation? legislators and local elected officials are taking actions and proposing policies that restrict or impact Uber, Lyft, Airbnb, and others. We elected officials are impacting people’s lives, but – aside from some sound bites – with possibly little understanding as to how and why. Policy makers include references to the Shared Economy and Autonomous Vehicles in all their presentations, while lacking true, data-driven understanding of the technology’s future or where it may lead; billions of dollars of decisions, impacts on air quality, sustainability, and economic development, are being made absent the input and insight of top data scientists.
And one thing our government rarely does: look back five years to evaluate the accuracy of decisions made, the data analyzed, and the projected results.
The government and elected officials must not only do more to engage companies and individuals who specialize in data analytics, but must embrace them. All too often, attempts to engage in that manner are met by staff assurances of “We have this, we know exactly what to do.” How often do elected officials challenge their internal teams? We need to create an open and transparent environment in which experts trained in data analysis are used as a resource for our staffs and our decisions. As new technology and new companies emerge, we must do what we can to make decisions based on deeper analysis of the data we have.