Scientific Research and Analysis of Management Problems for the Purpose of Rationalization

Definition & Scope of Management Research

  • Scientific research can and should be applied to management problems; two pre-conditions:

    • Application of scientific methods (empirical, statistical, experimental, logical, philosophical).

    • Delimitation of the subject-matter to problems that truly belong to the management domain.

  • F. W. Taylor pioneered multi-disciplinary scientific approaches (technique, economics, psychology, physiology).

    • Many of Taylor’s original issues can now be treated with finer precision by specialised sciences (e.g., industrial psychology, ergonomics).

  • Elton Mayo and successors highlighted the decisive impact of psychological and social factors alongside the technical and economic.

  • Operations Research (OR) has strongly expanded the available methodological arsenal; OR models often serve as the quantitative backbone of modern management science.

Three Complementary Conceptions of the ‘Management Field’

  1. Activity-based / Functional View

    • Core managerial activities: Planning, Organising, Leading/Co-ordinating, Controlling.

    • Each function is analysable by technology, economics, psychology, physiology, statistics.

    • Helpful to split study into:

      • Structure (static architecture of roles, communication channels).

      • Process (dynamic functioning of managerial action in time).

  2. Decision-centred View

    • Decision making is the heart of management, but pre- & post-decision tasks remain crucial.

    • Even a minimal decision study requires time-study techniques and an economic optimisation framework Maximise π=R(Q)−C(Q)\text{Maximise }\pi=R(Q)-C(Q).

    • Realistic models must embed probability, uncertainty, resource limits, human values, group interests, societal constraints, and technological change.

    • Deep analytical treatment ultimately demands philosophy (e.g., Kant’s “Kritik der praktischen Vernunft”) to interrogate goals and values.

  3. Bureaucratic / Rule-System View

    • Organisation as a rule-based integration of many individuals toward common goals.

    • Emphasis on policy, goal definition, measurement of congruent results, clear duties.

    • Brings three intertwined goal-clusters to the foreground:
      a. Economic (productivity, profit).
      b. Human / social (satisfaction, stakeholder service).
      c. Normative / legal-ethical (rule compliance, social legitimacy).

The Nature of Scientific Analysis in Management

A. Pure Scientific Research

  • Purposes: discover principles, explain relationships, develop theory, create new methods/tools.

  • Canonical cycle (empirical): Observation → Analysis → Synthesis.

    • Hypotheses often originate via analogy, intuition, or informed guessing; must be tested (statistics, experiments).

  • Canonical cycle (a priori): Analysis → Synthesis → Critical testing of deductions.

  • Deliverables: theses, models, measurement devices, specialised equipment.

B. Analysis for Rationalisation (Practical Improvement)

  • Purpose: Better economy & satisfaction via actionable recommendations.

  • Same 3 steps (Observe → Analyse → Synthesise) but with pragmatic adaptations:

    1. Observation simplified—use existing records, spot samples, cost-effective data capture.

    2. Analysis focuses only on relationships critical to improvement; completeness is sacrificed for impact.

    3. Synthesis/presentation must ‘sell’ the change; practical judgement sometimes outweighs formal rigor.

Key Fields & Illustrative Analyses

A. Income & Cost Analysis

  1. Scientific Strand

    • Rooted in business economics (>50 yrs of scholarship).

    • Choice of calculation method depends on purpose, time-horizon, scope, and ex ante vs. ex post perspective.

    • Spatial delimitation (firm, department, product) is essential.

    • Two classical allocation logics:
      • Production orientation (machine utilisation, idle-capacity treatment).
      • Market orientation (customer value).

    • Average-cost vs. marginal-cost principles:
      • Average for pricing with full cost recovery.
      • Marginal for optimisation of given capacity.

  2. Rationalisation Strand

    • Necessarily uses standardised, simplified schemes (e.g., Schmalenbach Kontenplan, Swedish “Normalkontoplan”).

    • Separate internal cost accounting from external financial accounting for clarity.

    • Calculations should simultaneously reveal short-run and long-run effects; hence variables must distinguish Fixed Costs (FC)\text{Fixed Costs (FC)} vs. Variable Costs (VC)\text{Variable Costs (VC)}.

B. Profit & Loss (P&L) Calculation

  • The P&L rests on: (i) asset/liability changes; (ii) activity-based income & cost.

  • Schmalenbach clarified that the statutory balance sheet is primarily a profit determination tool, yet real-world issues (e.g., inflationary depreciation policies) complicate purity.

  • Standard valuation of normal inventories avoids spurious P&L swings when prices fluctuate.

  • For comparability, interest on own capital must be imputed and the finance function treated as a separate responsibility centre.

C. Decision-Game / Simulation Models

  1. IBM Three-Firm, Four-Market Model (dynamic, competitive):

    • Decision variables: price (4), marketing spend (4), production volume, capacity expansion, R&D.

    • Results computed via assumed demand elasticities and cost functions.

  2. Practical Illustration (Kristensson’s Case)

    • Concern revenue: 40 M SEK; three product groups (one loss-maker).

    • Elasticity study showed negligible quantity response to price cuts.

    • Recommended raise of selling price from 150 → 165 SEK, plus 3 SEK extra marketing per unit.

    • Comparative profit calculation:
      \begin{array}{ccc}
      \text{Scenario} & \text{Price} & \text{Unit Profit (\text{SEK})}\\hline
      I & 150 & -10\
      II & 165 & +2
      \end{array}

    • At 70 % of previous volume, Scenario II attains equal or better net profit—demonstrating price leverage over quantity.

D. General Management Model Construction

  • Start with objectives before structure.

  • Marketing-centred diagram: Sales → Manufacturing → Purchasing; each touches supply markets (materials, labour, capital, energy).

  • Indirect processes (finance, personnel, admin, planning, control) must be economically balanced with direct processes.

  • Table 1 in the article lays out how objectives decompose for analysis.

  • Organisation design must factor resource limits; purely theoretical charts often exceed affordable headcount.

  • General principles (H.A. Hopf, AMA etc.) provide heuristics but should never be applied mechanically.

    • Example: Rule "3–5 subordinates per manager" (Fayol) must be context-adjusted.

E. Work Research

  1. Scientific Foundations

    • Physiology: studies of workload, rest pauses, environmental stress; instruments for measuring metabolism, pulse, etc.

    • Psychology: Hawthorne studies (Mayo) proved productivity is shaped by social/attentional factors, not merely technical ones.

    • Methods Engineering: stop-watch studies, flow-process charts, therbligs, statistical frequency sampling.

  2. Rationalisation Applications

    • Human-engineering design of tools, layouts, lifting aids.

    • Stop-watch time studies identify set-up, cycle, necessary & unnecessary delay times; piece-rate standards boost self-driven productivity.

    • Work-simplification programs (war-time evolution of Gilbreth’s therbligs) reduced analysis complexity; use five symbols (operation, transport, storage, hold, delay) to focus on high-impact improvements (often 30–400 % gains).

    • Psychological programme: engaging workers to overcome resistance and secure co-operation.

Guidelines for Effective Rationalisation Analysis

  • Do NOT attempt exhaustive coverage or universal laws; instead:

    1. Choose the most fruitful systematic approach.

    2. Select the few variables that matter most.

    3. Validate via both scientific methods & pragmatic testing.

    4. Remain mindful of factors excluded from quantitative treatment (externalities, social repercussions).

  • Key Questions to answer:

    • What’s wrong? Why? What to improve? How? In what sequence? Who is responsible?

  • Beware of creating larger problems elsewhere while solving a local inefficiency.

How Management Science Supports Rationalisation

  1. Multi-disciplinary perspective guards against the ‘narrow-minded specialist’ trap; essential in executive and analyst education.

  2. Provides background knowledge for intelligent goal-setting and tool selection; highlights typical pitfalls.

  3. Supplies conceptual shortcuts enabling simpler yet adequate analyses in concrete cases.

  4. Insists on clear definitions, explicit assumptions, and known validity domains of methods.

  5. Reveals zones of uncertainty where guesswork is inevitable, fostering realistic humility rather than technological utopianism.

  6. Encourages broad ethical and societal reflection (Kant’s practical reason) to prevent harmful side-effects of narrowly economic rationalisation.