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Local Innovation Labs in Balance with Nature. Doc Hall Urban Systems Web Conference July 26, 2013. Don’t tell me the answer; just explain the question. Yogi Berra. Vigorous Learning Organization. Big Picture Vision: Systems Thinking; Holism. 5. Servant Leadership.
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Local Innovation Labs in Balance with Nature Doc Hall Urban Systems Web Conference July 26, 2013 Don’t tell me the answer; just explain the question. Yogi Berra
Vigorous Learning Organization • Big Picture • Vision: • Systems Thinking; • Holism 5. Servant Leadership Ability to see a picture as if looking from outside in; including seeing yourself as others see you. 2. Common Mission & Goals 4. Behavior: What and Why; Mission, not Status 3. Rigorous Learning (Scientific Method) “Culture” must be reinforced every day
Ask basic questions: • What’s work? Why? Is prevention better than doing more and more? • What’s efficiency? Efficiency of what for how long? • Productivity of nature? • What’s quality of life? • How do we innovate to improve a total system?
Local Issue Learning Groups • Create local systems learning laboratories as economic microcosms, safe havens for broader thinking by vigorous learning organizations. • Start local issue learning groups, using systems thinking and focusing at first on one issue, like: • Cleaning • Safety and Security • Water • Energy • Health • Education • Transportation
Example 1: Scientific Cleaning – OS1 Barrel with “tool” apron Pro Team back pack vacuum Two-sided mop bucket Auto Scrubber using ionized water OS1 (Operating System 1) is a network of institutions across the U.S. dedicated to improving processes for cleaning larger buildings.
Quality of cleaning first; then quantity or efficiency. Respect janitors as professionals. Standardize cleaning processes. Educate janitors for 3 weeks; don’t just train.
Standard issue: • Pro Team Vacuum • Unger Bucket • PortionPac Chemicals • (only 3 used daily) • Microfiber mop Sustainability at UT Austin: 2011 Symposium
Janitor Education • 112 hours to start; 40 hours per year thereafter. • Some Selected Topics: • Pathogenic organisms; where they hide; where to clean • Particulates in air • Measurements, like taking a pH • Safety and hazards; hazmats • Finding info: Web sites like FDA, CDC, EPA…
Daily Standardized Work Clean in teams; each member a specialist (versus “generalists,” each assigned to an area). Work to a schedule. Beginning of shift meeting: Count out the cleaning pacs; review anything different for this shift. End of shift meeting: Count in; explain variances; report discrepancies – things needing fixing or attention. Ideal: Regard a building and its surroundings as an ecology to monitor and to preserve for its stakeholders – including the building itself.
Some Results University of Texas at Austin
University of Texas at Austin: Annual water usage in mopping 1,000,000 800,000 600.000 400,000 200,000 Main cause: Unger bucket 863,240 Gallons Per Year Other 262,302 Rest Rooms Other Rest Rooms 2002 2011
The Role of Suppliers to OS1 Unger (Mop Buckets & Other Equipment) PortionPac Chemical (packs of cleaning agents) Pro Team (back-packed vacuum cleaner)
The OS1 Network is small: a few dozen universities, K-12 school systems, and government labs, and the Post Office. Implementation is a multi-step odyssey. Many other K-12 schools, prisons, and agencies are in quasi-OS1 programs. The only big commercial “user:” Boeing. Why?
How can this nascent scientific cleaning movement expand its influence beyond the immediate campuses served? Cleaning is one of the last factors considered, or never considered, in building design or renovation – or in community design or renovation. But quality of cleaning makes a huge difference in ongoing sustainability.
Example 2: Safety & Security – Bergen County An existing cooperative of 12 community police chiefs are trying to expand their influence on community ethos. Budgets have been cut up to 50% in three years. Recurring hurricanes and blizzards. Fear of mass shootings. All are in some stage of “community policing.” In this situation (Compression), all practical countermeasures obviously require more citizen involvement in their own safety and security.
Example 2: Safety & Security – Bergen County Improvements in community policing have “monitized” into 10K upticks in housing values. Every storm, every water shortage, etc. calls for police assistance and intervention. How can this base load on policing be reduced? Further progress must overcome jurisdictional gridlock in community governance.
Example 2: Safety & Security – Bergen County: Questions In order for this group to progress further would the simple structure below be sufficient: One or more local group champions. A mentor/facilitator to keep a group in dialog, organize meetings, keep thinking long term, and guide learning via a VLO model. A core group of insiders and questioners, but interacting with the community as needed. Some worker bees to collect and compile data (college interns?).
Example 3: Water Groups Indianapolis, IN and Bergen County, NJ. Indianapolis has one utility for water and sewage, but it is reluctant to participate. Bergen County has many utilities; some are eager to participate. A kernel for a group is active in both locations, but reality is that one must cut through entrenched thinking everywhere.
Example 3: Water Groups Each local situation is different, but many issues are common: Unable to meet peak summer demand now; future supplies are limited. Pumped water losses are ≈ 20%. Aging pipes and pumps, but still sprawling. Water prices are rising. Sewage overflow into storm drains in heavy rains.
Example 3: Water Groups • Common issues: • 5. Experiments just now beginning with smart grid for water; too much guessing. • 6. Pricing rarely penalizes overuse. • 7. Little public understanding of need for: • Gray water (reuse) • Limiting usage • Their own usage patterns • The value of green infrastructure
Example 3: Water Groups How to mentor these groups to look at total system effectiveness in the long run? The paradigm shift is huge: Business managers tend to think of the efficiency (or profitability) of entities in isolation. Lots of possibilities are off the table for consideration.
“Compression” Do Much Better; Use Much Less Dramatically cutting the use of virgin energy, raw ores, and known toxins will alleviate many other problems – including those of which we are unaware.
By 2000 we knew we were globally using too much stuff. But we are still expanding – really fast. About 75% of stuff is used by 20% of global population in industrialized societies. So to dramatically reduce consumption, the big hit (80%) has to be in industrial societies.
business System Complexity Cyber-Theft Enterprise-Wide Risk Management (ERM)?? Complex Tax Codes Capital Market Complexity – Meltdown Risk? IP Protection “Arab Springs” Work skills deficits New Environmental Regulations Euro-zone Crisis Business scandals – who to trust Regulatory Morass Software security risks China Prices – BRIC Competition Big Data, etc – techniques overwhelm Technological Obsolescence ( banks call this mess “value at risk” ) Chief concern: risk to cash flow !
Stereotypical business assumptions: Making money = Efficiency (market success, labor productivity, jobs, etc.) Financial death is more likely, much quicker than environmental degradation. But the big assumption is that: GLOBAL RESOURCES ARE UNLIMITED
Total Environment Complexity Precarious Environment Excessive Consumption Finite Resources Globalization Pushback Climate Change Fresh Water Ocean Pollution Ozone Hole Health Care Soil Degradation Energy Drought and Flood Biodiversity Food Security Endocrine Disrupters Outsourcing: Long Transport Distances Landfills “Super Size” Me (Incessant Marketing) Financial Collapses Riots, Protests Terrorism, Insurgencies NIMBYs Everything effects everything else
Financially justifying the use of cheap energy to work ever lower yielding sources of energy and raw ores is the equivalent of using our last remaining bodily calories to strip the land in a desperate attempt to stay alive. EROEI Return on Energy Peak Time Real capitalism dedicates some of its effort and sets aside resources to assure that the system will keep going – just like the old family farm.
Were there no limits on use of resources, using as much as we can makes no sense anyway. Making small changes while continuing to expand will not take us where we need to be. We have to evolve smarter systems. (More relationship driven, less arms-length transaction driven.)
Conservation Find and solve problems mostly one-at-a-time, using limited measures of success. Learn to improve bigger external systems in addition to improving efficiency doing what we do now. Transition Constantly learn how to intervene in systems to make problems “melt away.” Compression