Sep 04, 2026
Sep 04, 2026
An Indian Knowledge Systems Theory of Intertemporal Strategic Decision-Making in the Age of AI
Developing the SPSCM, Shreya Score & Return on Capability as a Testable Management Framework
Abstract
Can a strategy be financially successful and strategically destructive at the same time? Why do organizations repeatedly prefer measurable short-term gains over uncertain long-term capabilities? Can the value lost through layoffs, underinvestment, excessive automation or erosion of customer trust be captured before—not after—the consequences become visible? And can an indigenous Indian philosophical construct provide management scholarship with a theoretically useful framework for analyzing such intertemporal choices?
This conceptual paper develops the Shreya–Preya Strategic Choice Model (SPSCM) from the distinction between Shreya and Preya articulated in the Katha Upanishad I.2.1–2. Rather than equating Shreya with morally “good” decisions and Preya with “bad” decisions, the model conceptualizes them as competing temporal structures of value. Preya privileges immediately realizable benefit, whereas Shreya places greater weight on enduring capability and long-term flourishing while recognizing present economic constraints.
The paper proposes four decision-level constructs—Immediate Benefit, Long-Term Capability, Reversibility and Stakeholder Sustainability—and operationalizes them through a provisional 20-item psychometric instrument. It further develops a 100-point Shreya Score, a complementary Return on Capability (ROC) metric, seven empirically testable hypotheses, a validation protocol, and eight contemporary corporate mini-cases. The framework is positioned not as a substitute for established strategic-management theory, but as an Indian Knowledge Systems contribution to intertemporal strategy, organizational capability, AI transformation and strategic governance.
Keywords: Shreya, Preya, Katha Upanishad, Indian Knowledge Systems, strategic short-termism, artificial intelligence, organizational capability, strategic decision-making, Return on Capability, corporate governance
1. The Corporate Problem That Accounting Cannot Fully See
Modern corporations have become extraordinarily proficient at measuring outcomes.
Revenue.
EBITDA.
EPS.
ROCE.
Free cash flow.
Customer acquisition cost.
Employee utilization.
Productivity.
Yet some of the assets determining corporate survival remain only partially visible.
Institutional memory does not appear neatly on the balance sheet.
Employee adaptability does not.
Customer trust does not.
Strategic optionality does not.
Supply-chain resilience does not.
Nor does the ability of an organization to absorb the next technology before its competitors do.
This creates what may be termed temporal measurement asymmetry:
Short-term economic benefits are frequently observable before their long-term strategic costs, while long-term capability investments frequently incur observable costs before their eventual benefits.
Artificial intelligence dramatically magnifies this problem.
IBM's 2026 CEO research illustrates the capability gap. Although 86% of CEOs believed employees possessed the skills to collaborate with AI, only 25% of workers were regularly using AI. IBM also found that 83% of CEOs believed AI success depended more on employee adoption than on technology itself. Between 2026 and 2028, CEOs expected 29% of employees to require reskilling into different roles and another 53% to require upskilling within existing roles.
The challenge is therefore no longer merely technological.
It is intertemporal.
Organizations must determine which present benefits justify which future consequences.
This is precisely where the Katha Upanishad becomes analytically interesting.
2. Philosophical Foundation: Shreya and Preya as Temporal Choice
The textual foundation lies in Katha Upanishad I.2.1–2.
The text distinguishes Shreya from Preya and states that the discerning person examines the two and chooses Shreya, while the less discerning is attracted toward Preya through considerations of immediate acquisition and security. The Government of India's Vedic Heritage Portal preserves the relevant Sanskrit passage.
A rigorous management interpretation should avoid three errors.
First, Shreya does not simply mean “good.”
Second, Preya does not simply mean “evil.”
Third, the text did not “predict” corporations, artificial intelligence or modern finance.
Such claims would weaken rather than strengthen IKS scholarship.
The more defensible proposition is different:
The Shreya–Preya distinction provides a conceptual category for examining choices whose benefits and costs unfold across different time horizons.
That category maps naturally onto strategy.
Quarterly earnings versus research.
Automation versus reskilling.
Monetization versus trust.
Lean inventory versus resilience.
Job elimination versus organizational knowledge.
Rapid AI deployment versus governance.
Aggressive growth versus financial durability.
Every one of these is partly a contest between present value and future capability.
3. Defining the Shreya–Preya Strategic Choice Model
I define the Shreya–Preya Strategic Choice Model (SPSCM) as:
A decision-evaluation framework that assesses strategic alternatives according to immediate economic benefit, their contribution to enduring organizational capability, their reversibility and the sustainability of their consequences for material stakeholders.
The model is decision-level rather than organization-level.
A company is not inherently “Shreya” or “Preya.”
A particular decision may demonstrate one orientation while another decision taken by the same corporation demonstrates the opposite.
This is important for construct clarity.
Microsoft can simultaneously reduce roles, redeploy workers, invest heavily in AI and preserve particular intellectual assets.
TCS can invest aggressively in employee learning while restructuring other portions of its workforce.
The SPSCM therefore evaluates the strategic choice, not the moral character of the corporation.
4. Four Core Constructs
4.1 Immediate Benefit — IB
Immediate Benefit represents the extent to which a decision generates observable economic or operational gains within the organization's current planning horizon.
Possible manifestations include:
revenue increase,
margin expansion,
cost reduction,
cash-flow improvement,
productivity,
speed,
market-share gain,
reduced working capital,
or operational efficiency.
High Immediate Benefit is not inherently Preya.
A decision that generates high immediate benefit and high future capability may represent excellent strategy.
4.2 Long-Term Capability — LTC
Long-Term Capability represents the extent to which a decision creates, preserves or strengthens resources and organizational capacities that remain strategically useful beyond the immediate performance period.
These may include:
human capital,
technological capability,
institutional knowledge,
learning capacity,
innovation,
brand trust,
customer relationships,
data assets,
organizational resilience,
governance,
supplier ecosystems,
intellectual property,
and strategic optionality.
This is the conceptual heart of SPSCM.
4.3 Reversibility — REV
Reversibility captures the extent to which an organization can alter or reverse a strategic choice without disproportionate economic, technological, human or institutional loss.
A pricing experiment may be highly reversible.
A large-scale destruction of specialist capability may not be.
Closing a factory differs from changing a marketing campaign.
Outsourcing a strategic capability may create technological and knowledge dependencies that are difficult to undo.
Reversibility therefore determines the cost of managerial error.
4.4 Stakeholder Sustainability — SS
Stakeholder Sustainability represents the extent to which the economic benefits and burdens arising from a strategic decision remain viable across material stakeholders over time.
It does not require equal benefits for everyone.
That would be unrealistic.
Instead, it asks whether shareholder gains are being generated through consequences that eventually destabilize employees, customers, suppliers, communities, regulators or the organization itself.
This is not stakeholder benevolence.
It is strategic sustainability of trade-offs.
5. The SPSCM 2×2 Strategic Choice Matrix
The first-level diagnostic uses two dominant dimensions:
Immediate Benefit and Long-Term Capability.
| Low Immediate Benefit |
High Immediate Benefit |
|
| High Long-Term Capability |
Quadrant II: Shreya Investment |
Quadrant I: Strategic Sweet Spot |
| Low Long-Term Capability |
Quadrant III: Strategic Waste |
Quadrant IV: Preya Trap |
Quadrant I: Strategic Sweet Spot
High present benefit.
High capability creation.
Management should normally seek to scale these decisions.
Quadrant II: Shreya Investment
Low or delayed immediate return.
High future capability.
Examples can include R&D, workforce development, cyber resilience and new technological architecture.
These require patience—but also milestones.
“Long-term strategy” must never become immunity from accountability.
Quadrant III: Strategic Waste
Low present return.
Low capability creation.
These are often vanity initiatives, disconnected innovation laboratories, unused technology deployments or training programs that generate certificates rather than competence.
The managerial response is generally termination or redesign.
Quadrant IV: Preya Trap
High immediate gains.
Weak or negative long-term capability effects.
This is the most dangerous quadrant because its early financial indicators frequently look excellent.
The Preya Trap may therefore be defined as:
A strategic choice that creates attractive near-term measurable gains principally by consuming, transferring or degrading capabilities required for sustainable future value creation.
6. Operationalizing SPSCM: The 20-Item Scale
The SPSCM Decision Diagnostic Scale, or SPSCM-DDS, should initially contain 20 items—five per construct.
Respondents would evaluate one clearly identified strategic decision, not the organization generally.
Recommended response format:
1 = Strongly Disagree
2 = Disagree
3 = Somewhat Disagree
4 = Neither Agree nor Disagree
5 = Somewhat Agree
6 = Agree
7 = Strongly Agree
Importantly, respondents should never be asked:
“Was this a Shreya decision?”
Such language would create demand characteristics, cultural signalling and social-desirability bias.
Shreya classification should emerge from the scores.
7. Proposed SPSCM-DDS Items
Construct A: Immediate Benefit — IB
IB1. This decision is expected to generate measurable financial benefits within the organization's current planning horizon.
IB2. This decision improves operational efficiency in the near term.
IB3. The economic benefits of this decision can be observed relatively quickly.
IB4. This decision strengthens current-period organizational performance.
IB5. The decision produces benefits that senior management can readily quantify.
Construct B: Long-Term Capability — LTC
LTC1. This decision strengthens capabilities the organization will need several years from now.
LTC2. This decision increases the organization's ability to adapt to future technological or market changes.
LTC3. The decision preserves or develops knowledge that will remain strategically valuable.
LTC4. This decision expands the organization's future strategic options.
LTC5. The decision strengthens resources or competencies that competitors would find difficult to replicate quickly.
Construct C: Reversibility — REV
REV1. The organization could change course without excessive cost if this decision proved unsuccessful.
REV2. Capabilities surrendered through this decision could be rebuilt within a reasonable period.
REV3. This decision preserves flexibility for management to pursue alternative strategies later.
REV4. The organization would not become excessively dependent on irreversible commitments because of this decision.
REV5. Mistakes arising from this decision could be corrected without permanent strategic damage.
Construct D: Stakeholder Sustainability — SS
SS1. The benefits generated by this decision are not achieved primarily by transferring unsustainable costs to other stakeholders.
SS2. The decision preserves the organization's ability to maintain productive long-term relationships with employees, customers and other critical stakeholders.
SS3. Stakeholders who bear significant costs from this decision receive reasonable protection, transition support or compensating value.
SS4. The decision is unlikely to undermine stakeholder trust required for the organization's future success.
SS5. The distribution of benefits and burdens created by this decision is sustainable over time.
8. Why 20 Items?
Five items per latent construct provide an adequate initial item pool without making the instrument unnecessarily cumbersome.
The final validated scale may contain fewer.
Items should be deleted because of empirical weakness, cross-loading or redundancy—not merely to create symmetry.
Scale development should follow established psychometric procedures rather than rely on face validity alone. Churchill's classic scale-development paradigm emphasizes domain specification, item generation and empirical purification, while Hinkin similarly stresses disciplined construct definition and iterative measurement development for organizational research.
9. From Scale to the Shreya Score
The descriptive managerial instrument can translate construct scores into a 100-point Shreya Score.
The provisional weighting is:
| Construct | Proposed Weight |
| Immediate Benefit | 20% |
| Long-Term Capability | 40% |
| Reversibility | 20% |
| Stakeholder Sustainability | 20% |
| Total | 100% |
The overweighting of Long-Term Capability is intentional.
Otherwise the model would merely reproduce conventional short-horizon performance analysis.
However, the 40–20–20–20 distribution remains theoretical at this stage.
Future empirical research should test alternative weighting systems.
A defensible publication should never claim these weights have been “validated” before that work is actually performed.
10. Proposed Scoring Formula
Convert each construct's mean 1–7 score into a 0–100 normalized score:
Normalized Construct Score
NCS = [(Mean Score − 1) ÷ 6] × 100
The provisional overall score becomes:
Shreya Score = 0.20(IB) + 0.40(LTC) + 0.20(REV) + 0.20(SS)
where all variables are normalized to 0–100.
Suggested initial managerial interpretation:
| Score | Classification | Managerial Response |
| 80–100 | Transformational Shreya | Accelerate |
| 65–79 | Strategic Shreya | Invest and monitor |
| 50–64 | Contested Strategic Choice | Redesign/test |
| 35–49 | Preya Risk | Challenge rigorously |
| Below 35 | Severe Preya Trap | Reject/fundamentally redesign |
Again, these cut-offs are provisional decision heuristics, not psychometrically established clinical boundaries.
11. Return on Capability: Moving Beyond ROI
ROI asks:
What financial value did the investment generate?
SPSCM asks a second question: What strategically useful capability does the organization possess after the investment that it did not possess before?
That is the foundation of Return on Capability — ROC.
ROC should not be reduced to one arbitrary rupee number because capabilities differ across industries.
Instead, a capability portfolio should first be defined for the relevant strategic decision.
Possible capability indicators include:
AI proficiency,
employee redeployment,
patents,
product-development velocity,
new revenue capability,
data quality,
customer trust,
cybersecurity resilience,
supplier redundancy,
institutional knowledge,
automation competence,
managerial decision quality,
or learning agility.
12. The ROC Architecture
For each decision, management should identify 3–8 capability indicators.
Each indicator is standardized to a 0–100 measure.
Capability Gain Index
CGI = Σ(wáµ¢ × ΔCáµ¢)
Where:
ΔCáµ¢ = standardized post-decision capability minus pre-decision capability.
wáµ¢ = strategic importance assigned to capability i.
Σwáµ¢ = 1.
Then:
ROC = Capability Gain Index ÷ Resource Commitment Index
The Resource Commitment Index could combine:
capital,
management time,
training expenditure,
transition cost,
technology expenditure,
and implementation duration.
ROC should therefore initially be used for comparisons among similar investments within an organization, rather than as a universal cross-industry financial ratio.
A bank's ROC cannot sensibly be compared directly with a semiconductor company's ROC until standardization methodology becomes mature.
13. Why ROC Matters in the AI Economy
EY provides an unusually clear illustration.
After deploying Microsoft 365 Copilot to approximately 150,000 employees, EY reported a 15% productivity gain. Crucially, it reported that the gain was reinvested into client delivery and continued learning. Microsoft also reported monthly adoption of 94%, weekly adoption of 85%, and that 84% of employees experiencing time savings redirected some of that time toward higher-value work. EY subsequently began scaling the technology across a workforce exceeding 400,000.
Conventional ROI sees productivity.
ROC sees something additional:
What happened to the released capacity?
If saved time disappears into headcount reduction, capability consequences differ from a situation in which that time is reinvested into learning, client work, innovation or new services.
Efficiency is therefore only the first half of the story.
14. Seven Testable Theoretical Propositions
The original SPSCM propositions can now be developed into empirical hypotheses.
H1: Temporal Visibility Hypothesis
Proposition
Managers disproportionately favor strategic alternatives whose benefits are more immediately measurable than their long-term consequences.
Hypothesis
H1: The perceived measurability and temporal proximity of expected benefits will be positively associated with managerial preference for a strategic alternative, controlling for estimated total long-term value.
This directly tests the Preya bias.
15. H2: Capability Reinvestment Hypothesis
Proposition
Organizations that reinvest productivity improvements into complementary capabilities should produce stronger long-term outcomes than organizations that simply harvest efficiency gains.
Hypothesis
H2: The proportion of AI-generated productivity gains reinvested in human, technological and governance capabilities will be positively associated with subsequent Return on Capability.
A stronger longitudinal version could test whether ROC mediates subsequent financial performance.
H2a
Capability reinvestment will positively predict future organizational adaptability.
H2b
ROC will mediate the relationship between capability reinvestment and longer-term organizational performance.
16. H3: Irreversibility Hypothesis
Proposition
Capability consequences should matter more when strategic decisions are difficult to reverse.
Hypothesis
H3: Reversibility will moderate the relationship between Long-Term Capability and strategic-choice quality such that Long-Term Capability will exert a stronger effect on decision outcomes when reversibility is low.
In practical terms:
The harder the decision is to reverse, the less forgiving management can afford to be about capability destruction.
17. H4: Human Augmentation Hypothesis
Proposition
Where tacit knowledge remains strategically important, human–AI augmentation should generate stronger capability outcomes than indiscriminate substitution.
Hypothesis
H4: In knowledge-intensive work characterized by high tacit-knowledge dependence, AI augmentation strategies will generate higher ROC than predominantly substitution-oriented strategies.
H4a
Tacit-knowledge intensity will positively moderate the relationship between augmentation orientation and ROC.
This qualification is critical.
The model does not predict that augmentation is always superior.
Highly standardized, repetitive work may rationally be automated completely.
18. H5: Temporal Incentive Hypothesis
Proposition
Executive incentives influence the time horizon of strategic decisions.
Hypothesis
H5: Shorter executive-performance evaluation horizons will be negatively associated with Shreya Scores for discretionary strategic investments.
H5a
The relationship will be partially mediated by managerial emphasis on immediately measurable financial outcomes.
This is where SPSCM intersects corporate governance.
19. H6: Strategic Optionality Hypothesis
Proposition
Preservation of future strategic options creates real organizational value.
Hypothesis
H6: Strategic decisions that preserve greater future option value will demonstrate higher long-term organizational resilience after controlling for immediate financial return.
Examples include:
second suppliers,
modular technology,
retained human expertise,
flexible production capacity,
or multiple distribution channels.
20. H7: Capability Accounting Hypothesis
Proposition
What management measures affects what management chooses.
Hypothesis
H7: Decision processes that explicitly incorporate capability measures alongside financial-return measures will produce higher average Shreya Scores than decision processes based primarily on conventional financial metrics.
A field experiment could test this directly.
Give one executive group conventional ROI information.
Give another group ROI plus capability information.
Observe whether strategic choices differ.
That would provide an unusually clean test of the theory.
21. The Full Structural Model
The conceptual causal chain can be represented as:
Temporal visibility of benefits
Managerial short-horizon preference
Strategic choice
Immediate Benefit + Long-Term Capability + Reversibility + Stakeholder Sustainability
Shreya Score
Capability creation
Return on Capability
Organizational adaptability, resilience and long-term performance
Moderators include:
executive incentive horizon,
decision irreversibility,
industry turbulence,
tacit-knowledge intensity,
capital constraints,
and AI exposure.
This creates a model capable of being tested using longitudinal structural equation modelling rather than remaining a philosophical narrative.
22. Validation Strategy: Stage 1 — Content Validity
The first empirical study should not begin with hundreds of executives.
It should begin with experts.
A panel of approximately 12–20 experts could include:
strategic-management scholars,
organizational-behavior researchers,
psychometricians,
senior executives,
corporate strategists,
AI-transformation leaders,
and IKS scholars familiar with the Katha Upanishad.
Each item should be rated for:
relevance,
clarity,
construct representativeness,
and overlap.
An important safeguard should be introduced:
Half the academic validators should evaluate the scale without being told which construct is derived from Shreya–Preya philosophy.
If the instrument only appears sensible after philosophical explanation, its management construct validity is weak.
23. Stage 2 — Cognitive Interviews
Approximately 20–30 managers should complete think-aloud interviews.
The objective is not statistical validation.
It is interpretation.
Does “future capability” mean the same thing to a CFO and CHRO?
Does “stakeholder sustainability” sound normative rather than strategic?
Does “reversibility” adequately capture rebuilding capability?
Do respondents evaluate the decision or the entire company?
Ambiguous wording should be removed before large-scale data collection.
24. Stage 3 — Exploratory Factor Analysis
A development sample of approximately 250–400 managerial respondents could evaluate real strategic decisions their organizations have taken.
Exploratory factor analysis should test whether four distinct dimensions emerge.
Items should not be retained simply because the theoretical framework wants five questions per construct.
The data must be allowed to challenge the theory.
25. Stage 4 — Confirmatory Factor Analysis
A separate validation sample of approximately 400–600 respondents should then test:
a one-factor model,
a two-factor temporal model,
a four-factor SPSCM model,
and possibly a second-order Shreya orientation model.
The four-factor specification should demonstrate superior fit before SPSCM is treated as multidimensional.
Convergent and discriminant validity should then be examined using established measurement-model techniques rather than relying solely on coefficient alpha. Fornell and Larcker's work remains foundational in assessing latent-variable measurement and discriminant validity.
26. Stage 5 — Predictive Validity
This is where the model becomes consequential.
The researcher should return 12, 24 and preferably 36 months later.
Did high-Shreya decisions actually produce:
greater employee adaptability?
lower talent replacement costs?
higher innovation output?
stronger customer retention?
greater resilience?
higher AI adoption?
better post-shock performance?
greater long-term financial performance?
Without longitudinal prediction, SPSCM risks becoming merely an appealing classification framework.
The strongest proof of the theory would be:
The Shreya Score predicts future strategic outcomes beyond what conventional ROI predicts.
That should ultimately become the central empirical challenge.
27. Contemporary Mini-Case 1: Microsoft — Restructuring Without a Simplistic AI-Layoff Narrative
In July 2026, Microsoft announced the elimination of approximately 4,800 roles, around 2.1% of its global workforce. But Microsoft simultaneously reported that more than 4,000 employees had been redeployed into new roles during the preceding year, including approximately 500 that month. The company explicitly stated that the eliminated roles were not simply being “replaced by AI,” even while acknowledging that AI was changing tasks and work design.
SPSCM Research Question
Does workforce reduction accompanied by substantial redeployment produce higher LTC and Stakeholder Sustainability scores than equivalent reduction without redeployment?
Relevant Constructs
Immediate Benefit — potentially high.
Long-Term Capability — ambiguous.
Reversibility — moderate to low.
Stakeholder Sustainability — substantially affected by redeployment architecture.
Validation Value
Microsoft is useful because the case prevents simplistic coding.
Layoffs cannot automatically equal Preya.
The construct must capture capability consequences, not ideological preference.
28. Mini-Case 2: TCS — From Learning Expenditure to Capability Capital
TCS reported 69 million learning hours in FY2026, 270,000 employees with higher-order AI/ML skills, participation of approximately 281,000 employees in its AI hackathon, and annualized AI revenue of roughly US$2.3 billion.
SPSCM Research Question
Does large-scale skill creation translate into measurable commercial capability?
Relevant Constructs
Immediate Benefit — measurable through AI-related revenue and client productivity.
Long-Term Capability — potentially very high.
Reversibility — relatively high because learning expands options.
Stakeholder Sustainability — potentially high if productivity improvements coexist with mobility and employability.
ROC Variables
AI-skilled employees,
AI project deployment,
new AI revenue,
internal mobility,
productivity,
and client adoption.
TCS therefore offers an excellent test of whether training creates real capability rather than learning-volume theatre.
29. Mini-Case 3: Infosys — Bridge Programs and Strategic Redeployment
Infosys reported 328,594 employees at March 31, 2026. During FY2026, 81.8% of its workforce received training, with average learning of approximately 113.3 hours per employee, while 84% of the workforce was AI-aware. Particularly relevant to SPSCM, its Bridge programs offer training and internship pathways enabling employees to switch career fields while remaining inside the company.
SPSCM Research Question
Does internal redeployment create higher ROC than external replacement when skills become obsolete?
Construct Application
LTC can be measured through skill transition.
REV through preservation of human optionality.
SS through workforce transition.
IB through reduced external hiring and faster talent fulfilment.
This mini-case directly tests the Option Value Proposition.
30. Mini-Case 4: Wipro — Can Training Volume Become Deployable Capability?
Wipro reported 79.1 skilling hours per associate in FY2026 and indicated that more than 212,000 associates had completed GenAI training across different proficiency levels. It also reported 139 dedicated account academies covering roughly 78,000 associates.
SPSCM Research Question
What distinguishes skill acquisition from capability creation?
This is important because:
Training ≠ Capability.
Capability requires the ability to deploy learning in economically meaningful activity.
Possible ROC Measures
percentage of trained workers placed on AI-enabled engagements,
reduction in time to competence,
client revenue attributable to trained skills,
internal versus external talent fulfilment,
and productivity changes.
This mini-case guards SPSCM against becoming an advocacy framework for indiscriminate employee training.
31. Mini-Case 5: EY — What Happens to Productivity Gains?
EY's Copilot deployment provides perhaps the clearest direct ROC example.
The organization reported an initial deployment to approximately 150,000 employees and a 15% productivity gain, with gains being reinvested into client delivery and learning. Microsoft reported substantial adoption and employee redirection of saved time toward higher-value work. EY subsequently moved toward expansion across more than 400,000 employees.
SPSCM Research Question
Does reinvesting productivity gains create stronger long-term capability than harvesting the gains primarily as cost savings?
This can directly test H2.
32. Mini-Case 6: India's US$315-Billion IT Industry — When Preserving Jobs Could Itself Become Preya
Reuters reported in August 2026 that India's IT-services industry had reached approximately US$315 billion and was shifting toward outcome-based contracts as AI increased customer expectations for more output at lower cost. Mid-sized players were growing faster in some periods: Persistent Systems recorded roughly 16% Q2 growth and Coforge approximately 33%, compared with growth around 1–3% among some larger firms.
This case presents an important challenge to naïve interpretations of Shreya.
Suppose a legacy IT company refuses restructuring to preserve every existing role.
Is that Shreya?
Not necessarily.
If labor-arbitrage economics are structurally changing, protecting yesterday's job architecture may sacrifice tomorrow's organization.
SPSCM Research Question
Can immediate stakeholder protection itself become a Preya strategy when it prevents necessary capability transformation?
This case helps validate whether Stakeholder Sustainability captures durability rather than sentimentality.
33. Mini-Case 7: Charles Schwab — Capability Building While Others Optimize Headcount
Charles Schwab's Indian expansion provides a useful counterfactual.
Reuters reported in August 2026 that the company planned to scale its India technology centre to approximately 2,000 employees by the end of 2027, beginning with around 500 hires, while simultaneously bringing some technology work currently handled by contractors in-house. This was occurring during an industry period in which numerous financial institutions were using AI to constrain hiring or reduce roles.
SPSCM Research Question
When does insourcing constitute capability investment despite higher apparent fixed costs?
Relevant measures include:
institutional knowledge retention,
technical ownership,
vendor dependency,
talent development,
and strategic control.
A financial-cost model may favour outsourcing.
An ROC model may reach a different answer.
34. Mini-Case 8: Enterprise AI Adoption — Buying Technology Versus Building Capability
Thomson Reuters found that among C-suite respondents who believed their organizations were adopting AI too slowly, cited constraints included data quality and structure at 65%, budget at 55%, regulation at 47%, demonstrable accuracy at 45%, data security at 44%, and demonstrable ROI at 42%.
IBM meanwhile reported that only 25% of workers regularly used AI, despite 86% of CEOs believing workers were prepared.
The combined implication is critical.
Purchasing AI capability does not automatically create organizational AI capability.
Technology can be available while:
data remain inadequate,
governance remains immature,
workflows remain unchanged,
employees remain untrained,
and adoption remains weak.
SPSCM Research Question
Can organizations report positive technology ROI while generating low ROC?
This could become one of SPSCM's most important empirical applications.
35. Cross-Case Validation Matrix
The eight cases can be used as an initial comparative validation set.
| Case | Primary SPSCM Question | Dominant Construct |
| Microsoft | Restructure or preserve capability? | REV + SS |
| TCS | Does learning become economic capability? | LTC + ROC |
| Infosys | Can internal mobility preserve option value? | LTC + REV |
| Wipro | Is training volume equal to capability? | ROC |
| EY | Reinvest or harvest AI productivity? | LTC + IB |
| Indian IT sector | Can preserving the present damage the future? | IB + LTC |
| Charles Schwab | Outsource efficiency or internal capability? | LTC + REV |
| Enterprise AI adoption | Buy technology or build organizational capability? | ROC + LTC |
These cases should initially be independently scored by multiple expert raters.
Inter-rater reliability can then establish whether SPSCM classifications are reproducible rather than merely intuitive.
36. A Stronger Construct-Validation Experiment
The mini-cases make possible an interesting experiment.
Recruit several hundred managers.
Randomly assign respondents to three conditions.
Group A — Financial Information Only
Respondents receive traditional ROI, cost and revenue information.
Group B — Financial + Capability Information
They additionally receive information about skills, resilience, reversibility and knowledge loss.
Group C — Full SPSCM Diagnostic
They receive financial information plus the four SPSCM dimensions and complete the 20-item scale.
Then compare strategic choices.
If Group C consistently makes different choices—and those choices subsequently align better with expert or longitudinal outcomes—SPSCM gains evidence of incremental decision utility.
That would be considerably stronger than merely demonstrating internal reliability.
37. Discriminant Validity: What SPSCM Is Not
A new management construct must demonstrate that it is not simply another name for an existing idea.
SPSCM should therefore be distinguished empirically from:
long-term orientation,
stakeholder orientation,
organizational resilience,
dynamic capabilities,
strategic flexibility,
corporate social responsibility,
and
sustainable management.
SPSCM's distinct theoretical unit is the intertemporal strategic decision itself.
Its central question is not whether the organization is generally long-term oriented.
It asks:
What combination of present benefit, future capability, reversibility and stakeholder sustainability characterizes this particular strategic choice?
That is the proposed theoretical contribution.
38. The SPSCM–ROC Research Agenda
A serious research program could proceed through six studies.
Study 1: qualitative construct development and expert validation.
Study 2: psychometric scale development.
Study 3: confirmatory factor analysis and discriminant validity.
Study 4: scenario-based strategic decision experiment.
Study 5: longitudinal predictive validation.
Study 6: cross-cultural replication across India, the United States, Europe and East Asia.
Cross-cultural replication is especially important.
A model derived from Indian philosophy should not be considered globally useful merely because Indian managers understand it.
Its observable constructs must function consistently outside the Indian cultural context.
Paradoxically, the strongest validation of an IKS-derived theory would be evidence that its explanatory power travels beyond India.
39. From Indian Knowledge Systems to Indigenous Management Theory
This project raises a larger question.
What should serious IKS management scholarship attempt to accomplish?
Surely not merely:
“Kautilya said this.”
“Krishna taught leadership.”
“The Gita teaches motivation.”
“Hanuman demonstrated servant leadership.”
Those comparisons may introduce Indian texts to management audiences, but they rarely create theory.
The stronger path is:
Ancient Concept
Construct Definition
Boundary Conditions
Causal Mechanism
Measurement Instrument
Hypotheses
Empirical Testing
Predictive Validity
That is the pathway from civilizational wisdom to management scholarship.
The original text should inspire the conceptual lens.
Evidence should determine whether the resulting theory survives.
That distinction is essential.
IKS should not ask modern evidence to bow before ancient authority.
It should permit ancient intellectual categories to enter the modern contest of ideas—and then subject them to the same empirical scrutiny as every other theory.
That is how an intellectual tradition becomes alive.
40. Theoretical Contribution of SPSCM
The proposed framework makes five potential contributions.
First, it conceptualizes corporate short-termism at the decision level.
Second, it integrates financial benefit and organizational capability rather than treating them as competing literatures.
Third, it introduces reversibility as a central modifier of intertemporal strategy.
Fourth, it distinguishes Return on Capability from conventional Return on Investment.
Fifth, it provides a formal route through which an Indian philosophical construct may generate empirically testable management theory.
The contribution can therefore be summarized:
SPSCM proposes that strategic choice quality depends not merely on the amount of value created, but on when value appears, what capabilities remain after the value is created, how recoverable the decision is if wrong, and whether the distribution of its consequences remains sustainable.
41. Limitations
Several limitations must be acknowledged from the beginning.
The proposed Shreya Score weights are theoretical.
The 20-item instrument has not yet undergone psychometric validation.
Corporate data may create survivorship bias.
Managers may retrospectively rationalize successful decisions as long-term strategy.
Long-Term Capability can be difficult to quantify.
Stakeholder Sustainability may overlap partially with existing stakeholder-orientation constructs.
ROC may require industry-specific capability measures.
Causal inference will require longitudinal rather than merely cross-sectional studies.
Most importantly, Shreya cannot be identified solely because a decision eventually succeeded.
A fortunate gamble is not automatically wise strategy.
Likewise, a well-reasoned long-term investment that fails because of unforeseeable circumstances should not automatically be classified as poor decision-making.
The model must ultimately separate decision quality from outcome luck.
That distinction deserves a substantial future research stream of its own.
Final Thoughts
When Does Profit Become Liquidation?
What if a company's margins are rising because its capabilities are falling? What if an AI transformation celebrated for reducing headcount is quietly eliminating the human knowledge required to govern the AI itself? What if a training program praised for millions of learning hours creates almost no deployable competence? What if an apparently inefficient second supplier, extra engineer or retained specialist turns out to be the organization's most valuable insurance policy? And what if the great strategic error of the AI age is not failing to optimize enough—but optimizing away precisely what the corporation will later discover it needed most?
The Katha Upanishad does not provide an answer sheet for the modern corporation.
It provides something more valuable.
A question.
Shreya or Preya?
Not:
good or evil.
Not:
profit or purpose.
Not:
human versus machine.
But:
Which form of value are we choosing, and over what horizon?
That question deserves a place in strategic management.
The Shreya–Preya Strategic Choice Model attempts to give it one.
The Shreya Score converts it into diagnosis.
Return on Capability converts it into measurement.
The hypotheses convert it into science.
And the validation program places the idea where any serious management theory must eventually stand:
before evidence.
If empirical research eventually shows that SPSCM cannot predict strategic outcomes better than existing frameworks, the model should be rejected or revised.
That is not a failure of Indian Knowledge Systems.
That is scholarship.
But if the evidence demonstrates that managers systematically overvalue visible immediate benefits, undervalue capability destruction, underestimate irreversibility and make better decisions when capability measures are explicitly introduced, then something consequential will have happened.
An idea articulated in an ancient Upanishadic dialogue will not merely have been “applied” to management.
It will have generated a testable contemporary theory of strategic choice.
And perhaps that is where IKS must ultimately aspire to go.
Not ancient wisdom decorating modern management.
Not Sanskrit terminology attached to Western models.
But indigenous concepts generating new constructs, new hypotheses, new measures and—when the evidence permits—new management theory.
Because the corporation of the AI age faces exactly the dilemma Yama placed before Nachiketa in another form:
The attractive return is visible.
The enduring value is harder to see.
And leadership begins with knowing the difference.
Proposed Academic References
04-Sep-2026
More by : P. Mohan Chandran
