Wave 1 – Archetypes

Identifying Candidates for Wave 1 via Contextual Problem-Framing to Uncover the Next M2ML Innovation

1) Structured environments

These environments are primed for optimization, as they are filled with data-rich procedural tasks, and accompanied by clear steps and decision trees to perform repeatable processes that are currently manual.

2) Stodgy industries left behind

Low-tech, analog industries with customer sets or management teams that don’t have the incentives or capabilities to identify and/or execute on process innovation are ripe for disruption. These archetypes are often locked in with legacy build-outs, and are struggling to maintain relevance amidst an ever expanding array of smarter IoT devices and automated workflows​.

3) Merging and synergizing disciplines to produce new data sources, applications, and breakthroughs

Identification of a new data source and/or a new way of harnessing existing data, paired with machine learning, allows for the next phase of human augmentation.

4) Newly realigned incentive structures

Sometimes, systems must first change from the inside out and are predicated on shifts in incentives. Case in point, the US Healthcare payer system is transforming to a value-based care model that measures provider success based upon patient outcomes, spurring new innovation cycles driving at brand new (albeit logical and overdue) sets of outcomes.

5) Macro trends translating to new bottlenecks and decentralized systems

Optimizing utilities and consumables in areas around ​power consumption, safety, privacy, security and environmental cost tracking​, are traditionally viewed as cost centers. However, current and looming threats like climate change, cyber attacks, and labor shortages are rapidly transforming these domains into essential business priorities on accelerated timelines.

Across all archetypes, economic feasibility must be addressed. Do the hypothetical mechanics make sense? Before tackling Wave 2’s practical logistics, in Wave 1 we must theoretically project ROI for the current and subsequent waves, and consider design for manufacturing (DFM) with economical production scale in mind.