How Can Integral Information Systems Create a Seamless Data Architecture that Measures Thriving?
By Bill Baue & Ralph Thurm
Where is the wisdom we have lost in knowledge? Where is the knowledge we have lost in information? (TS Eliot, The Rock, 1934)
The rise of Big Data, Internet of Things (IoT), Artificial Intelligence (AI), and Blockchain (or Distributed Ledger Technology — DLT), etc… heralds significant promise for accelerating and scaling up innovative solutions to humanity’s super wicked problems. However, data and technology alone do not automatically produce solutions; they are mere building blocks (that may even introduce unintended risks — think HAL’s “I’m sorry, Dave, I’m afraid I can’t do that…”). Successful solutions require the additional application of knowledge, or what some might even call wisdom. More specifically, the building blocks of data and technology must be integrated into systems designed to provide actionable (or “decision-useful” in accounting parlance) information that trigger responses that promote broadly beneficial solutions.
What’s the issue?
All our knowledge brings us nearer to our ignorance
So writes Eliot elsewhere in The Rock– an apt description of the current state of data and information in the corporate and investment spheres in particular. The primary problem is that this data and information remains obstinately disconnected from the broader systems within which business and investment operates.
This disconnect was clearly identified two decades ago, in Donella Meadows’ 1998 report Indicators and Information Systems for Sustainable Development, where she mapped the multiple capitals to the Daly Triangle (named after World Bank Economist and Ecological Economics Co-Founder Herman Daly) that outlines the relationship between intermediary and ultimate means and ends.
Meadows underlines how the Daly Pyramid (as she also calls it) illuminates a fundamental problem: governments and economies typically focus on delivering Intermediate Ends — in particular wealth — which often ends up undermining Ultimate Ends, ironically.
Meadows also points to a similarly ironic intermediary / ultimate distinction when it comes to environmental indicators:
An environmental indicator becomes a sustainability indicator (or unsustainability indicator) with the addition of time, limit, or target. The central questions of sustainability are: How long can this activity last? How long do we have to respond before we run into trouble? Where are we with respect to our limits?…
[S]ustainability indicators should be related to carrying capacity or to threshold of danger or to targets. Tons of nutrient per year released into waterways means nothing to people. Amount released relative to the amount the waterways can absorb without becoming toxic or clogged begins to carry a message.
Unfortunately, the lion’s share of corporate and investment metrics fall into the “means nothing to people” category. Part 8 of this series cites the Danish study finding that only 5% of the 40,000 corporate sustainability reports issued in the first decade-and-a-half of the millennium mention ecological limits. And a mere 0.3% apply those limits to strategy and R&D.
Why it’s important?
In order to “carry a message,” Meadows tells us, metrics need to relate to carrying capacity or thresholds. Fortunately, messaging on thresholds / carrying capacities has matured significantly over the past decade, with the coining of the Planetary Boundaries (ecological ceilings) in 2009 and Doughnut Economics (ecological ceilings + social foundations) in 2012.
Recognizing the shortcomings in most data architecture and information systems, the Reporting 3.0 Data Blueprint opted to take a First Principles approach to identify the fundamental needs of data architecture and information systems. We built our approach on the Daly Triangle, with a series of adaptations:
- We added an upside-down triangle for the base to contain the Ultimate Ends, to signal their commensurate importance as the Ultimate Means;
- We melded the two opposing triangles to form an hourglass, creating balance while also introducing the arrow of time;
- We flipped the hourglass, making the Ultimate Means of Natural Capital the resource that sets the process in motion;
- We introduced the notion of stocks and flows of capital resources;
- We overlaid sustainability thresholds (ecological ceilings & social foundations) to preserve vital capital resource stocks by operating off the flows.
We implemented these augmentations because we believe they enhance the ability to translate data into actionable information that “carries a message” — or as Eliot says in The Rock, “the endless cycle of idea and action.”
See Figure 3 to view what we at Reporting 3.0 call the Daly Hourglass:
How can you tackle it?
The Data Blueprint distills its guidance on how to build what it calls Integral Information Systems (labeled in a nod to Integral Theory) into three primary categories:
- Integration between and amongst the multiple capitals to optimize positive synergies for creating system value;
- Contextualization within the carrying capacities (i.e. sustainability thresholds) of the capitals, allocated in fair share proportions to organizations;
- Activation of responses when the sustainability of any capital — and hence rightsholder well-being — is placed at significant risk. Activated data also catalyzes “acceleration” to scale up transformation to systems levels. This category is inspired by Meadows’ notion of information that “carries a message.”
Integral Information Systems call for a seamless architecture that integrates data flows from internal and external sources at the micro (company), meso (industry, portfolio, habitat), and macro (economic, social, and ecological systems) levels. They also integrate data across the multiple capitals, contextualized to their carrying capacities (thresholds & allocations). This enables assessments of sustainable (or regenerative or thriving) performance, as distinct from unsustainable (incrementalist or degenerative) performance.
Scoping outward, such performance assessment at the organizational level enables benchmarking at the industry or portfolio or habitat level. And such assessments can then be disaggregated back to the company, industry / portfolio / habitat, or broader systems level. Integral Information Systems would enable free flow of data and information (knowledge even) between company and national accounts, for example, allowing for reconciliation of Science-Based Targets (at the company level) with Nationally Determined Contributions (NDCs) from national accounts.
What will you have achieved?
Ultimately, Integral Information Systems enable the determination of system value creation. This concept, first articulated by the Future Fit Business Benchmark, embeds shareholder (financial) value creation as well as shared (financial & social) value creation to encompass value creation and destruction across economic, social, and ecological systems. Integral Information Systems thus create a seamless data flow architecture that spans the full Reporting 3.0 Strategy Continuum, from business as usual to thriving on the horizontal (organizational) axis, and from the micro to the macro level on the vertical (scalability) axis.
What question will we discuss next time?
What will New Accounting Look Like 20 Years from Now? And How Will this Integrated Accounting Harmonize Financial, Management, and Sustainability Accounting? Please find part 15 here.
[Context of this series: This is part 14 of the Reporting 3.0 series that forms the basis of an Implementation Guide that summarizes the total value of Reporting 3.0 in implementing a future-ready sustainability strategy and disclosure approach, in line with the idea of a Green, Inclusive and Open Economy. By posting these articles here Reporting 3.0 seeks feedback in the writing process of the final document, to be released as Blueprint 5 at the 5th International Reporting 3.0 Conference in Amsterdam, The Netherlands, on June 12/13, hosted by KPMG, see www.2018.reporting.org]