64 years ago, when my house was built the Long island Power Company installed electric meters in my basement. Two large grey metal meters are affixed to my foundation with insulated wires connecting them to my fuse box. They have a variety of dials and arrows beneath thick glass. I can see the meters but don't really understand what the numbers mean or how to read their information. Every other month or so, a polite person from the power company rings my bell to ask if they can come into my home and walk into my basement to read my meters and input the results into a handheld device that radios the information back to the power company.
The last time the meter reader was here I asked why the power company didn't trust me, the homeowner, to call in the numbers or input them in a form on the internet. She told me that many people don't understand the meters and if they do often lie to the power company about what they read to under-report their electricity usage. I asked why the power company couldn't read my meter remotely or why they couldn't measure how much elecricity my home was using.
Like, "don't THEY know that?" Nope. THEY don't, and the reason they don't has as much to say about how the electricity grid works as it does the way all complex modern industrial systems work and we in the Data Governance world can learn a lot from this.
The electricity grid was created as a downstream electrical production network. Upstream Power plants create electricity and send it downstream to factories and homes to be consumed. The power company did not build in mechanisms to measure how much electricity is being transmitted over the wires, how much is being consumed, and exactly by whom. Your monthly electrical bill is not based on your actual electricty usage. Its based on estimates of your useage based on your historical usage information. That is, the meters read your past and the power company forecasts your current usage and future performance based on that historical information.
The grid itself is run at 70% of electricity capacity to allow up to a 20% margin of error. If the lines carry over 90% of their rated capacity in aggregate, some lines could be running at 100% and therefore could overload and explode. And if some lines overload, capacity reroutes and burns up other lines, transformers, and sub-stations,. So the whole system is calibrated based on historical analytics. The power producers have no realtime understanding of how the electricity is used, in what quantity, when and where. And even the end users don't really understand where the electricity came from, how it was produced, or how the system actually functions.
In the Industrial Age, we human beings created many complex systems that function without many of the system participants understanding how the system works, and this is fine if we are all happy running our systems at 70% efficiency.
In enterprises today, we run our Data production and consumption systems with similar levels of complexity, performance, and ignorance. Most business users have no idea where the data came from, how it was produced, transmitted, and consumed. Conversely, most, if not all, Data Governance professionals have no idea how business people collect and use information to generate value. And this grid was created without any meters to read data volume, velocity, veracity, and utility.
Councils, Stewards, Policies, and Standards will improve human communication about the importance of data in an enterprise, but they won't change human behavior over time without new Data Governance "Smart Meters" that measure and report how data was created, who refined it, how it was transmitted, aggregated, repurposed, criticized, commented, stuffed in envelopes, posted in trades, hedged in inventory, reserved against premium, debated in legislation, trademarked, copyrighted, patented, packaged, and a million other uses and abuses. Until we can demonstrate a clean line between creation and use, Data Governance will be two steps forward and two steps back over and over again, generation after generation.
We need meters and readers and a new Information Age infrastructure that tells us, intelligently, what we are doing, why and when we are doing it. It should connect maintenance to operations, front office to back, middle to board, outside to in. We don't know enough today to tell regulators what we know and until we do we won't be able to close the gap between our forecasted capacity, current and optimal states.
The Information Governance Community is running a landmark Survey on the Cost of Data Quality and the #1 answer to all of the questions is "I don't know." Data Governance Professionals don't know how poor Data Quality effects Business Outcomes because they don't measure that. After Lehmen Brothers disintegrated in 2008, and the global financial meltdown spun out of control, the number one question from the public was "Didn't they know this would happen?"
No. No one knew then. No one knows now. And on one will ever know until we build more intelligent systems that connect Information Production to Consumption and measure the gaps every step of the way. This last recession has demonstrated that we are reaching the limits of our unintelligent Industrial Age networks and systems and its time for a major upgrade.