The Awakened Enterprise, Part 1 (REVISED, January 2024)
Provenance for Decision-Making
to curate the most consequential use of our mind, our senses, and our experiences.
Decisions drive the actions that shape our experience of the present and the unfolding future. We make those decisions within the limits of what the present moment exhibits to us and what our past experience has collected.
In making consequential decisions, professionals bear the burden of accountability to act wisely within the confines of confidence, time to act, and resources to expend. To clarify which path to choose, we seek tools and tactics to mitigate “VUCA” (volatility, uncertainty, complexity, & ambiguity).
The Awakened Enterprise concept of these articles explores an approach to achieve greater operational robustness by incorporating context into the pedigree of crucial decisions. Two supporting articles set foundational concepts: Despite Uncertainty (ability to act in a VUCA environment) and Digital = Magic (human + machine teaming).
Aspirational Possibilities
Consider…
An engineer approves a design, recording assumptions made in prioritizing selection criteria to choose between alternatives — ready for reassessment upon discovering a contradiction to an assumption in the future.
A court grants a conditional variance on a building code, asserting the circumstances for reversing the decision — and limiting use as precedent.
A marketing team puts a product launch on hold, placing a detailed plan on the shelf — ready to execute when triggered by key metrics of the market.
An oncologist forms a plan for her patient, monitoring change to the tumor, to qualifications for reimbursement, and approvals of novel therapies.
In each case, the decisions and actions recognize how the unknowable future and VUCA limit clarity and confidence in the present. To overcome conventional conservatism, deliberative delay, and other forms of risk-aversion, the decision is explicitly framed as a plan rather than recorded into an archive— explicitly anticipating change and adaptation.
Information Infrastructure
Digital systems embody the creation, flow, consumption, and archival of modern thought and action, from raw data into refined information, to a still-emerging field of knowledge capture and management. Recognizing the value of data, we even created data-about-data (termed metadata).
Threads and Twins
The “digital thread” concept refers to a tactic to improve enterprise coordination and decision-making clarity by developing infrastructure and processes that interoperate and exchange information across distinct systems and organizations (e.g., leveraging in-use field data for calibrating product design models).
Integrating multi-stage tasks (and the hand-offs between them) requires structural commonality of both data and software — such as coherent “genealogy” data over the design-make-operate-maintain lifecycle of a product. This compatibility can be valuable to urgency or complexity driven assessments, such as when performing root cause analysis of a product failure (e.g., comparing as-designed vs. as-made part history)
Through the data and infrastructure of a digital thread, we can connect specific physical products with individualized digital models, called digital twins. Digital twin models embody an operationally valuable level of understanding of the physics of the product’s operation, informed by continually-updated data from sources such as live connected sensors.
For example, sensors in your car’s tires could monitor tread wear (product performance) or road conditions (operational environment). Tire replacement would be based on product condition rather than a calendar or number of miles. Dynamic traction control in the car would be informed by information on the ground (literally).
Data Lake to Data Swamp
To implement a digital thread, previously-separated databases may be consolidated or federated into a “data lake” to support cross-functional unified query and access to systems-of-record previously confined within organizational silos. There are several means by which this pristine data lake metaphor unfortunately can degrade into more of a data swamp.
“Quod Me Nutrit, Me Destruit” (What Nourishes Me, Destroys Me) — attributed to Christopher Marlowe
Targeted Convergence Corporation (TCC), founded by Texas Instruments engineers, observed how repositories for engineering analyses fall into disorder and disuse over time, due to systemic and behavioral problems adversely affecting implementations of Knowledge Management systems. Consider:
- Legacy data expands with continual addition of new data — and since productivity focuses on action, documenting is often treated as an overhead task; performed grudgingly and only as minimally required.
- As more data are captured into your system, ever-longer result lists get returned from each search query, expanding the burden of filtering.
- The usefulness of potentially relevant archived analyses will be limited by the user’s trust in prior process rigor, contextual assumptions, etc.
- Users become inclined to simply recreate the target data (preferring to trust their own expertise), introducing redundant if not inconsistent data.
- This leads to a vicious cycle of degradation as the content of the data lake becomes evermore redundant, untrusted, and obsolete and therefore the results of queries increasingly less relevant and valuable.
TCC then asserts the purpose of an organization is to master decision-making in their field of expertise and the knowledge systems must serve rather than burden decision-making.
Index by Decision
The digital thread’s intent to create/collect data, publish an index and provide access does not in itself assure value. Sensible traditional mindsets might index enterprise data to enable searching by product line, part family, analysis type, test facility, model number, etc.
However, if we recognize the central importance of the decisions made from the data and analyses, we can consider asserting a framework, overlaying (highly consequential) decisions as the primary search index.
‘Searching’ is an activity — ‘Finding’ is a result.
The main assertion driving the concept of Decision Provenance is the most valuable “index” to find useful previously-captured knowledge is based upon the list of decisions informed by all that archived knowledge.
Decision Provenance
To build a decision-centric repository, key contextual information should be recorded for decisions of potential interest in subsequent queries.
Scientists employ “Data Provenance” to improve understanding and reproducibility of experiments and analyses — for example, the DT&A (https://dataandtrustalliance.org) suggests metadata covering data types, lineage, source, generation method, generation date, intended use, etc.
Decision Provenance metadata would provide similar details on the origin and lineage of decisions of significance — the Who, What, Why and How, and potentially adaptations (genealogy) over time.
Consistently capturing the metadata needed as provenance would become part of the standard process of making consequential decisions (review, budget approval, customer/patient visit, rendition of verdict, etc.) and collated with familiar documentation (shipping manifest, service bulletin, patient record, legal brief, air worthiness directives, etc.)
Capturing metadata courteously may reduce reluctance to complicating tasks or usability of present software tools — (for example, by employing low-friction entry — such as conversational AI like Google or Amazon Alexa).
By formally recording caveats, concerns, assumptions, and unknowns — decision-makers can move past present deliberation and analysis paralysis, with confidence that emergent clarification and change can robustly trigger re-assessment of the decision, with future-granted insight.
This re-assessment may then be carried out with the full benefit of prior efforts considering relative merits of alternatives, processes to reproduce supporting analyses and previous results, mappings between dependent decisions, and even cross-linking via related assumptions and unknowns.
While legacy processes may informally capture such information already in annotations of archived reference documents (e.g., slides, spreadsheets, or email) — the explicit mapping of contextual metadata into a searchable knowledge representation will be a foundational function of the Knowledge Steward (discussed in more detail in Part 3).
Cultural Transformation
The degree of candor and transparency suggested in Decision Provenance may require cultural shifts that some would consider radical. Therefore, leadership support and community acceptance will be crucial to empowering and emboldening genuine participation.
“Real knowledge is to know the extent of one’s ignorance.” — Confucious 孔子
There must be acceptance of qualified accountability — moderation in judging with hindsight, fully considering the constraints and context for the decision. This includes rejecting any delusions of infallibility — welcoming error as learning (the primary meaning of the Latin root “errare” is “to wander”, as in an unanticipated direction, not necessarily “wrong”).
C4ISR-oriented tools and culture may offer strategies to more confidently traverse this path between exposure to repercussions vs. risk-aversion behaviors that dampen potential for impact. Bottom-line, avoid the traps of irresponsible caution.
Awakened Enterprise
An Awakened Enterprise acknowledges the limitations of knowledge and continuity of organizational memory. It systematizes self-reflection and humility to promote agility and robustness in decisions made in the present and future.
Decisions of emergent interest may now be revisited with greater clarity into the factors recorded in the provenance. Such metadata facilitate enterprise collaboration as an organizational archive of criteria for trade-off evaluation, analytical tools and practices, opportunities to discover unknowns or confirm / disprove assumptions — and perhaps most significantly, reliable continuity in recalling the next steps to take as future information, resources, and opportunities unfold.
Further, a Decision Provenance system can perform searches into the future as a hedge against flaws deriving from present-day unknowns, assumptions or evaluation criteria — which may be clarified in future hindsight. That is, we can make decisions in the present — with knowledge that an informational “safety net” can keep an eye out for important developments in the future for which we may revise our decision.
When fully assimilated into crucial decision-making processes, a prevalent awareness of this facility to leap between present and future lends confidence to swiftly act despite uncertainty. This essential attribute of The Awakened Enterprise will be described as the “continuum mindset.”
© 2020 All Rights Reserved. Revised 2024.
Continued in
The next article discusses organizational mindfulness — holistic awareness spanning enterprise silos, supply chains, and operational product fleets — as a strategy to counter volatility, uncertainty, complexity and ambiguity.
See also:
- “Success is Assured,” Cloft, P., Kennedy, M., Kennedy, B., Productivity Press, 2018, ISBN 9781138618589, see also Targeted Convergence.
- Attribute metadata are also thoroughly explored in the concept of Design Rationale, which may provide insight into implementation and adoption obstacles, such as tedious and restrictive detail requirements.
- Beautifully-rendered futuristic vision — complete with AR/VR and nanobot manufacturing: Lockheed Martin: Future of Work (YouTube)
