Limits to Growth (1972) and the World Conservation Strategy (1980) led to the development of sustainable development (SD) frameworks over the next half century. Each generation of SD frameworks has incorporated best-available science, expanded the breadth of its scope and inclusivity. SD platforms have been embraced and operationalized within the private sector, all levels of government and civil society. Most recently the UN Research Institute for Social Development has developed a new platform “redefining sustainable development reporting”. See https://sdpi.unrisd.org/ for the SDPI platform and https://www.youtube.com/watch?v=hiaVeDWC7zc for recordings of the webinar.

Enhanced SD frameworks benefit from lessons-learned during each prior generation of SD frameworks and from the information infrastructure legacy of earlier generations of SD platforms. This post focuses on the use of the legacy information infrastructure developed for earlier SD generations.

Data acquisition and compilation although a necessary and indispensable element for the operation of SD platforms is not necessarily the highest priority for budget and talent allocation. Even with the best of intentions legacy information and datasets may have unintended shortcomings and “traps” for the new users unacquainted with the specific administrative and organizational history of the information. Given the fiscal focus of todays management, it is not unexpected that defaulting to existing information acquisition processes and historic data sets, or simply tweaking it, will be seen as an “easy” money saving strategy. Indeed, this may be true. But is should be thoroughly reviewed with staff directly involved in the original process (even if it means dragging them out of retirement.)

Legacy datasets and procedures may have incorporated short-cuts such as “work-arounds” and accounting “plugs”. Reasons for the use of these short-cuts include:

• unexpected mandated budget cuts which were common during periods of fiscal tightness
• resource limitations
  • time pressures such as deadlines
  • human resources (e.g. experienced people replaced by those without relevant corporate memory)
  • skills (pay scales falling falling behind and no longer competitive to maintain quality)
  • capacity (too much to do, too quickly, and new skill needs)
• uncoordinated shared responsibilities in an evolving joint endeavour,

The latest version of SD platforms will incorporate best-available science, a broader scope beyond the simple industry-environment dimensions of the earliest SD frameworks and the enhanced inclusivity of most modern policy frameworks. But the integrity the the SD platform as a whole will still rest on an investment in the information infrastructure to ensure the integrity of the whole.