assessing the risks of it infrastructure – a personal network perspective

Assessing the Risks of IT Infrastructure – A Personal Network Perspective

Daniel J. HinzJochen Malinowski

HICSS 39 20. April 2023

Summary

Information technology (IT) management for end-user computing systems like desktop computers is of high importance, especially the availability of these systems

Users are a vital part of these systems, and any user incident renders the system unavailable until the incident is resolved

Classical approaches consider only measurable user incidents, eg. number of helpdesk calls

Integrating personal network characteristics may give a more realistic view of user incident behaviour


IT infrastructure management is a hot topic for more than 15 years now

1990 "IT infrastructure" appears for the first time in the top 10 issues identified by the survey

1995 "Building a responsive infrastructure" was ranked number one challenge

2000

2001

"IT infrastructure management" ranked third in these two informal surveys

2003 "Infrastructure developments" ranked second in the category of top application and technology developments

Survey to identify the most critical issues in IS management

Conducted regularly by the Society for Information Management (SIM), supported by the MIS Research Center (MISRC)

Among their members consisting of top executives as well as IS researchers

SIM survey

Source: [Niederman, Brancheau, Wetherbe 1991], Brancheau, Janz, Wetherbe 1996], [Luftmann, McLean 2004]


End-user computers are a central component of IT infrastructure

End user computers are a central component, as they are influenced by all other infrastructure components

Availability is a major aspect [Niessink and Van Vliet, 1998]

Potential causal model for desktop availability

Findings from the literature

Users may have major effect on desktop availabilityIf the user is lost, the system is inoperational, although all hardware and software is working


And users are a vital part


What would you do, if ….

… You want to order a Canon MP730 printer in the online purchasing platform of your company, but cannot find it in the printers section?

Keep on searching? (perhaps it's listed as "input device")

Call the helpdesk?

Ask the colleague next door, who just got his new Canon last week?

Order a different model?

Give up?

?


Classical approaches focus on "official" incidents, but they are only one part

SituationClassical approaches measure mostly official incidents (e.g., helpdesk calls) [Niessink and Van Vliet, 2000]

Complication Not all incidents are reported

but instead solved by asking co-workers or known experts

How can those aspects be considered to get a more realistic number of incidents?


Social network characteristics may have an influence on problem solving behavior

Social network characteristics may influence problem solving behavior…

… and Social Network Analysis (SNA) may offer a promising solution to address them[Wassermann and Faust 1994; Scott 2000]

The problem solving capability of the social network of co-workers influences the number of ‘unofficial’ user incidents

The problem solving capability of the helpdesk influences the number of ‘official’ user incidents

Focus on the relations between individuals

Body of qualitative measures of network structures

Widely applied in sociology and organizational studies


The density of the social network has an influence on problem solving

Based on expert interviews, two SNA measures to influence problem solving were chosen

Socio-Centric Density (SCD)of the network of co-workers [Barnes 1974]

)1(

nn

lSCD

n

lECD

Ego-Centric Density (ECD)of the helpdesk [Scott 2000]


SCD and ECD can be used to get a more realistic number of user incidents

ECD

SCDCHDUI 1

U3

U1

U2 HD0.9

0.8

0.8

0.6

1.0

0.8

Calculation of user incidents:

SCD = 0.68

ECD = 0.80

UI = 185

UI: User incidents

CHD: Calls that reach the helpdesk

α: Scaling factor

The ratio of both densities can be used to predict the unkown number of total user incidents (UI) from the number of known incidents (CHD)

Example


The initial model has to be extended to reflect these findings

Helpdesk quality and social network density now determine the user action upon an incident


Further research

Validation of the model with real-life data

Evaluation of the applicability of other SNA measures

Consideration of multiple hops

Consideration of dynamic aspects

assessing the risks of it infrastructure – a personal network perspective

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