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here, particularly if the organization does not undergo transformational change frequently.
Hence, we specify a higher noise level of 0.4 to provide insight into the effect of noise. Table
3 includes a third column to summarize the noise effect and provides the values from Table
2 above for direct comparison. All other aspects of the model delineated in Figure 1 and
summarized in Table 2 above remain unchanged.
Table 10. Noise & Knowledge Effects
Measure Command Noise Experience
Duration 350 days 354 days 303 days
Cost $245K $250K $208K
Work Volume 1105 P-days 1105 Pdays
1105 P-days
Rework 298 P-days 360 P-days 317 P-days
Coordination 275 P-days 282 P-days 249 P-days
Wait 16 P-days 20 P-days 19 P-days
Project Risk .343 .374 .305
Backlog 11 days (Staff) 11 days (Staff) 11 days (Staff)
Notice that most of the performance measures do not change appreciably between
our baseline, command-first values summarized in Column 2 and those corresponding to
the higher noise environment summarized in Column 3. Indeed, the increased noise level
has negligible impact on Duration (4 additional days), Cost ($5K), Work Volume (no impact),
Coordination (7 P-days), Wait time (4 P-days) and Backlog (no impact). Alternatively, the
impacts on Rework (21%) and Risk (9%) are sizeable. This provides insight into how top
management can influence the work environment in a negative manner simply by allowing
interruptions to grow. It provides insight also into the kinds of performance measures (e.g.,
rework and risk) that are relatively sensitive to noise.
Table 3 includes a fourth column also to summarize the experience effect. As above,
all other aspects of the model delineated in Figure 1 and summarized in Table 2 above
remain unchanged. The Application Experience parameter represents the level of
experience that certain organizational actors have in a particular application domain. In this
case, we modify the experience levels of the Top Management team only, increasing its
Application Experience level one step, from Low to Medium. This represents the level of
experience the top-management team has with organizational change, with Low reflecting
minimal experience, and Medium reflecting some prior experience. This represents a topmanagement
team that has been involved with previous change processes, in addition to
possessing acquisition experience. In contrast to these top-management settings, the
Experts & Consultants actors have Application Experience set to the level High across all
models; this is why they are called “experts” and are hired as consultants.
As above, it is worth noting that most of the performance measures do not change
appreciably between our baseline, command-first values summarized in Column 2 and
those corresponding to the higher-experience actors summarized in Column 4. Alternatively,
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