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Ins3705 Assignment 2 Semester 2 2026 - Complete Answers

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INS3705 ASSIGNMENT 2 SEMESTER 2 2026 - COMPLETE ANSWERS. FEEL FREE TO CONTACT ME FOR MORE ASSISTANCE. (0.7.6.0.8.3.6.0.7.0).

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, INS3705
ASSIGNMENT 2 SEMESTER 2
2026
DUE AUGUST 2026
QUESTION 1: (40 MARKS)

1.1 Analysis of Four Weaknesses in the Organisation's Knowledge Management Practices

The scenario depicts an organisation with critical deficiencies in its Knowledge Management (KM)
practices. These weaknesses not only hamper daily operations but also threaten long-term
sustainability. Drawing upon established KM theories and scholarly literature, four principal
weaknesses can be identified, each adversely affecting a specific KM process.

Weakness One: Failure to Capture and Codify Tacit Knowledge
The first significant weakness is the organisation's failure to document and codify the expert
insights that reside within its specialists. The scenario notes that "expert insights are rarely
documented" and that "critical know-how remains embedded in individuals," indicating a
dangerous reliance on tacit knowledge. This directly affects the knowledge capture and codification
process. According to Nonaka and Takeuchi’s (1995) SECI model, organisational knowledge creation
relies on the conversion of tacit knowledge into explicit knowledge through a process they term
"externalisation." By failing to externalise this expertise, the organisation breaks the knowledge
creation cycle and prevents individual know-how from becoming a shared organisational asset. This
creates what can be described as an "institutional knowledge gap," where the loss of an individual
means the irreversible loss of their contextual reasoning and decision-making logic. Research
supports that the codification of tacit knowledge is essential for organisational memory and
continuity, as it allows knowledge to be stored, retrieved, and reused independently of the
originating individual (Alavi & Leidner, 2001).

Weakness Two: Limited Knowledge Sharing Across Departments
The second weakness is the evident absence of knowledge exchange across departmental
boundaries, as the scenario explicitly states that "knowledge sharing across departments is
limited." This deficiency undermines the knowledge transfer process, which is the systematic
dissemination of knowledge from its source to areas where it is needed. The lack of
cross-departmental flow results in the formation of "knowledge silos," where valuable practices
remain trapped within specific teams. This leads to redundant efforts and prevents the
organisation from leveraging its collective intelligence. This is a structural failure, often rooted in a
lack of supportive systems or a culture that does not reward collaborative behaviour. Research
suggests that effective knowledge transfer is vital for cultivating a sustainable organisational future,

, as it improves the quality of decision-making by providing a broader, more integrated perspective
(Bock et al., 2005). When knowledge is not transferred across departments, the organisation
develops a fragmented view of its operations, inhibiting its ability to innovate and adapt.

Weakness Three: Uncritical Reliance on System Recommendations
The third weakness, which is particularly concerning given the investment in advanced technologies,
is the tendency of most employees to "rely uncritically on system recommendations without
understanding the assumptions or reasoning behind them." This directly affects the knowledge
application process. Effective application of knowledge requires that users understand the context,
limitations, and underlying logic of the information they are using (Van de Walle & Turoff, 2007).
When employees blindly trust system outputs, they fail to exercise professional judgment, meaning
they do not "knowledge-apply" but rather "data-follow." This uncritical reliance creates a passive
user base that treats sophisticated AI outputs as infallible, thereby eroding the human capacity to
challenge, interrogate, and refine knowledge. As argued by Davenport and Prusak (1998),
knowledge is a fluid mix of framed experience, values, and insight that provides a framework for
evaluating and incorporating new information; the absence of this evaluative framework leads to
poor application and potentially erroneous decisions.

Weakness Four: The Absence of a Learning Culture
The final weakness is the systemic failure to foster organisational learning, as evidenced by the fact
that knowledge is rarely shared or documented and that performance declines when experts leave.
This fundamentally undermines the knowledge creation and learning process. The organisation fails
to convert individual learning into organisational learning, which is a critical process for resilience
and adaptation. Argyris and Schön (1978) distinguished between single-loop learning (correcting
errors within existing frameworks) and double-loop learning (questioning and altering the
underlying frameworks themselves). The organisation's current practice, where expertise remains
individualised and unscrutinised, prevents even single-loop learning from being institutionalised.
Furthermore, the uncritical acceptance of AI outputs stifles double-loop learning, as employees do
not question the system's fundamental assumptions or suggest improvements. This is a sign of a
culture that does not value inquiry, reflection, or knowledge renewal, thereby ensuring that
performance remains dependent on the presence of specific individuals rather than a resilient,
learning-oriented system.

1.2 Determination of the Organisation's Operating Context
Based on the scenario, this organisation operates predominantly within a Knowledge Economy
context, with strong elements of a Knowledge Society framework that are not yet fully realised.

A Knowledge Economy is defined as one where growth and productivity are driven by the
production, distribution, and use of knowledge and information, rather than by traditional factors
like land or natural resources (Powell & Snellman, 2004). The scenario aligns with this definition, as
the organisation has "invested heavily in advanced digital systems, including artificial intelligence
and data-driven decision-support tools" to support strategic decision-making. This demonstrates a
clear economic priority on leveraging knowledge-based assets for competitive advantage. The
heavy reliance on technology and specialists to generate value and drive operations is a hallmark of
a knowledge economy.

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