Asynchronous and distributed process improvement - Semantic Scholar

Info Systems J (2001) 11, 87–110

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Asynchronous and distributed process improvement: the role of collaborative technologies Ned Kock Department of Computer and Information Sciences, Temple University, 1805 N. Broad St., Wachman Hall (038-24), Philadelphia, PA 19122, USA, email: [email protected]

Abstract. The recent proliferation of low-cost computer networks has driven the development of a new type of organization, in which geographical and time constraints to collaboration among process teams have been gradually removed. As these organizations have to cope with a fast pace of change, they rely increasingly on distributed and asynchronous process improvement (PI) groups to redesign their processes. Yet little is known about the effects of asynchronous group support systems (GSSs) on PI groups. We investigate the effects of asynchronous GSSs on PI groups through a two-stage action research study of 38 such groups in three organizations, one in Brazil and two in New Zealand, over 4 years and 4 months. Different PI groups voluntarily conducted all, part or none of their communication through an e-mail conferencing (EC) tool. The research suggests that EC support causes a decrease in the organizational costs associated with PI groups, which, combined with an increase in the number of possible simultaneous PI groups, generates an increase in overall organizational PI efficiency. The research also suggests a neutral overall effect of EC support on PI group outcome quality. Two explanatory causal models summarizing these effects are developed, and implications for research and industry practice are discussed. Keywords: Action research, asynchronous group support systems, e-mail conferencing, process improvement, quality improvement, re-engineering

INTRODUCTION

Process improvement (PI) is viewed by many as one of the underlying change dynamic approaches of widely practised and researched, and at a certain stage revolutionary, management movements (Burke & Peppard, 1995; Kock & McQueen, 1996). Some representative examples that have attracted world-wide attention are the total quality management and the business process re-engineering movements (the term process improvement (PI) is used in this paper to refer to improvements in quality or productivity of processes in general,

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whether they are of radical or incremental nature, or target local or interdepartmental processes). Among PI’s general characteristics suggested by the literature, one is of particular relevance in this research – its group basis (Ishikawa, 1986; Walton, 1991; Soles, 1994; Hammer, 1996). It implies that business process change proposals will probably emerge from a group specifically formed to generate such proposals (Deming, 1986; Hammer & Champy, 1993; Davenport & Stoddard, 1994). This generic type of group is referred to, in this research, as PI group. A PI group typically has a finite and relatively short lifetime, during which its members define, analyse and search for alternatives to improve one or a few organizational processes (Choi, 1995; Choi & Liker, 1995; Hammer & Stanton, 1995). The recent proliferation of low-cost computer networks has driven the development of new organizational structures where geographical and time constraints to collaboration among process teams have been gradually removed. Low-cost, easy-to-implement wide-area networks have decreased process execution’s dependence on colocated teams. At the same time, the need for process teams to rely on computer support for communication and synchronization of activities has increased proportionally (Barnatt, 1995). Hence, the following question arises: Given the fast pace of change in most industries today, how can organizations cope with the need to transform their business processes in order to adapt to such fastchanging environment? We believe the answer lies in distributed and asynchronous PI groups. The general literature on empirical studies of group support systems (GSSs) widely acknowledges a number of potentially beneficial effects of its use as a tool to support a variety of groups (Sheffield & Gallupe, 1993; Dennis et al., 1996; Yoo, 1997), and PI groups in particular (Matthews, 1994; Dennis et al., 1995). However, this same literature also points to negative GSS effects and implementation failures (Grudin, 1988; Orlikowski, 1992; Yellen, 1993), as well as mixed findings (Turoff et al., 1993; Yellen et al., 1995). This lack of consistency in the findings of previous research hinders the development of expectations regarding the possible impact of specific types of GSSs on PI groups, and calls for research addressing particular types of applications supporting well-defined PI tasks. Empirical research of this kind has apparently been very limited.

R E S E A RC H O N A S Y N C H R O N O U S G S S S U P P O R T TO P I G R O U P S

The large body of research on group support technologies and their impact on groups produced from the late 1980s up to the 1990s has been chiefly based on either controlled experiments or studies where researchers have been ‘removed observers’, typically case studies and questionnaire surveys. Among these, the predominance of controlled experiments in laboratories or organizations has been particularly noticeable (Dennis & Gallupe, 1993; Davison, 1995). Such predominance has influenced the selection of group tasks and support technologies, leading to a focus on tasks and technologies that are particularly suitable for the isolation and control of research variables (Rodden & Blair, 1993). This can be felt in the disproportionately high number of studies of decision-making groups supported by synchronous,

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same-room group support technologies, relative to other group tasks and technologies (Pervan, 1994; Dennis et al., 1996). Although the importance of these studies is unquestionable, a better balancing of GSS research focus is necessary to prevent biases in the development of GSS theories and theoretical frameworks. There are representative examples of research where GSSs were used to support PI groups, such as Pietro’s (1992) study of quality improvement groups, Dennis et al.’s (1993) study of one business process re-engineering group, Dennis et al.’s (1994; 1995) studies of business process modelling groups, and de Vreede’s (1995) study of dynamic organizational modeling and change groups. These studies generally suggest an increase in PI group process efficiency, with no clear or significant increase or decrease in the quality of the outcomes generated by the groups. Yet, their focus mirrors that of GSS research in general. It is difficult to generalize the findings of these studies to asynchronous GSSs, because they employed almost exclusively synchronous group support tools, particularly group decision support systems (GDSSs). There are important theoretical reasons why synchronicity may considerably affect GSS impact findings (Cristian, 1996). One of the most obvious comes from the media richness theory, which claims that lack of synchronicity leads to losses in media richness (Daft & Lengel, 1986). The theory argues that media richness differences have the potential to significantly affect user behaviour (Lengel & Daft, 1988). Our research tries to contribute towards reducing the lack of research balance stemming from the lack of studies of asynchronous group support effects on group-based PI efforts, and the comparatively strong focus on controlled experiments involving GDSSs. This is particularly relevant given the commercial success achieved by some instances of asynchronous GSSs, such as those based on the e-mail paradigm, when compared with GDSSs and other synchronous GSSs (Grudin, 1988; 1994; Stevenson, 1993). Commercial success ensures that studies addressing such asynchronous GSSs are likely to be of direct interest to a wide range of organizations.

R E S E A RC H M E T H O D

The research was conducted in three organizations over a period of approximately 4 years and 4 months, and involved 38 PI groups. The participating organizations were (we only acknowledge by name the participant organizations that have given us written permission to do so):

• Events (pseudonym), an international events organizer based in Brazil; • MAF Quality Management (MQM), a branch of the New Zealand Ministry of Agriculture and Fisheries; and • The University of Waikato (Waikato), a medium-sized research university in New Zealand. The research approach employed was action research (Rapoport, 1970; Susman & Evered, 1978; Winter, 1989; Checkland, 1991), adapted for the specific context of information systems research (Wood-Harper, 1985; Baskerville, 1997; Lau, 1997). One of the main characteristics


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of organizational action research is that the researcher, or research team, applies ‘positive’ intervention to the participating organizations while collecting research data (Peters & Robinson, 1984; Francis, 1991; Elden & Chisholm, 1993). In our research, we tried to improve the organizations where research data were collected by collaborating with members of PI groups. Our main contribution was to provide technological and methodological support to PI group leaders (the nature of this support is explained in the next section). One distinctive characteristic of action research is the low control exerted on research variables (Jonsonn, 1991). We refrained from asking group members to follow specific procedures, or to use the e-mail conferencing (EC) system, rather presenting a group process and the EC system as tools that were ‘available’ to PI groups. We let group members decide whether they would use these, none, or any other group process and support tools available to them. In spite of its beneficial facets, the lack of control found in action research, combined with a high personal involvement in the study, makes the conduct of rigorous action research a very challenging task for the researcher (Baskerville & Wood-Harper, 1996). Action researchers face the risks of ‘perceiving’ generality where it does not exist, and falling into the traps created by their personal, often self-fulfilling, expectations (Kock et al., 1997). In order to avoid these sources of bias, we used triangulation in the analysis of research data by combining quantitative and qualitative data analysis techniques to account for related behavioural patterns and perceptions (Jick, 1979). Qualitative data were summarized through the general coding process proposed by Glaser (1992). We used statistical validation techniques, notably Chi-square tests and mean-centred deviation analysis, to confirm or disconfirm patterns that seemed to emerge from this coding process. The three main data sources used were unstructured interviews, transcripts of electronic postings from group members and structured interviews. One hundred and twenty-five unstructured interviews were conducted. These interviews lasted from 1 to 3 h each, and addressed perceptions of the respondents about their own or their colleagues’ participation in PI groups (some of the respondents in these interviews were not or had not been group members). Most of these interviews addressed perceived effects of the EC system on group members and on groups as a whole. Responses in unstructured interviews were summarized initially through interview notes on paper. These notes were later merged with participant observation notes into a ‘field notes’ file. Another source of research data was a set of transcripts of electronic messages from group members, organized by group and date. Additionally, 66 structured interviews were conducted. These interviews lasted from 45 min to 2.5 h each, were based on open-ended questions (i.e. not restricted to a set of predefined answers) and were audiotaped and later transcribed. A feature that distinguishes this research from much of the research conducted on GSSs so far is the absence of hypotheses or models to be tested. In doing so, we implicitly adopted an ‘emergence’ mindset, as opposed to trying to force the evidence collected to fit within or outside a predefined theoretical model (Glaser, 1992). As a consequence, summarization of data became as important as analysis. Three main techniques developed in the context of grounded theory methodology (Glaser, 1978; Glaser & Strauss, 1967; Strauss & Corbin, 1990)



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were iteratively used in the summarization of the research evidence collected in both stages of this research: (1) open coding, whereby research variables have been identified; (2) axial coding, whereby causal effects linking research variables have been identified; and (3) selective coding, whereby sets of causal effects and related variables have been categorized according to main dependent research variables.

GROUP PROCESS

In the three participating organizations, we offered our group facilitation services as a means to have access to research data about the impact of technology on PI groups. Group facilitation involved support for the use of a group methodology, called MetaProi and an EC tool. MetaProi, which stands for meta-process for process improvement, comprises a meta-process (that is, a process to guide process improvement) around which a structured set of activities, guidelines and graphical tools were developed to assist PI groups. This group methodology draws on a specific approach to guide process improvement projects (Kock, 1995) and on general normative literature in the field (e.g. Hammer & Champy, 1993; Harrington, 1991; Davenport, 1993a). MetaProi has been summarized as a 30-page manual that was distributed to group members to be used as a group-process guide. Note to readers: If we were to describe MetaProi here, it would probably take considerable paper space without adding much to what was said already. MetaProi is not presented here as innovative, and in fact is very similar to methodologies already employed by the organizations studied. A detailed description of MetaProi is provided by Kock (1999, appendix A). The EC tool supported electronic PI group discussions through public mailboxes developed using X-Post (Lantec Corp., Sao Paulo, Brazil) at Events, and electronic list servers developed using Novell Groupwise (Novell Corp., Provo, Utah, USA) at MQM and Waikato. In both cases, electronic mailboxes were created to allow group members to access electronic messages and file attachments posted by other members of their groups. The system allowed group members to store and exchange one-on-one electronic messages within and outside the group, as well as storing and posting messages and replies to the whole group. Spreadsheets, flow charts, presentations and graphs could be attached as files to electronic messages, and read by recipients. Attachments could be easily read by clicking on icons representing the attached files on the computer screen. PI groups have been typically formed by a prospective self-appointed group leader who had been approached by us or who independently sought our help for group facilitation. Our presence was advertized in the participant organizations by either the CEO, or senior managers in charge of autonomous organizational divisions (i.e. at the director or dean’s level). Our initial contacts with prospective leaders were usually follow-ups on contacts began or suggested by these senior managers, with the exception of cases where these senior managers were themselves the group leaders. Initially, we briefed the prospective leader on the proposed group process (i.e. MetaProi’s meta-process) and group support technology (i.e. the EC system). The prospective leader


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then proceeded to choose a general problem (associated with a process) to be tackled by his (her) group, and invite from five to 15 people to become members of the group, telling each of them of his (her) intention to lead the group and use our facilitation. We suggested the possibility of the use of MetaProi and the EC tool in our initial contacts with prospective leaders, but stressed that their use was not compulsory, leaving it to the group leader and member’s discretion. At this stage and afterwards, during the group discussion, we interacted almost only with the group leader. We almost never posted electronic messages to the whole group, and, when we did so, the messages concerned only group process rather than discussion content. Remarks in unstructured and structured interviews suggested that most ordinary PI group members were largely unaware of our presence and group facilitation. Once there was agreement on the medium to be used to begin the group discussion, the leader proposed an organizational process to be redesigned by the group. The group then started the PI discussion, whereby it collectively agreed on a process to be redesigned (which could be different from the process proposed by the leader), and modelled and analysed (i.e. presented and discussed information about) the process. Process modelling and analysis was carried out partially with our help, which was limited to enabling the group leader to properly model and analyse the process in face-to-face and one-on-one e-mail interactions (between us and the group leader only). The PI group then proposed and agreed on a number of changes to the process. These changes were, in most cases, later implemented under the supervision of the group leader.

R E S E A RC H S TAG E S

Our research was conducted through two stages. It begun with an exploratory stage, in which PI groups were both directly and indirectly facilitated and analysed. In this stage, an unstructured data collection and analysis approach was employed, which can be generally characterized by an absence of units of analysis. It was followed by a second stage, in which PI groups were closely facilitated and analysed using a more structured approach, that is, with well-defined units of analysis.

First stage: an exploratory intervention at events The research stage conducted at Events was begun in August 1993 and lasted approximately 1 year. The company had approximately 70 employees and yearly revenues of US$3.5 million. About 60 employees worked in the main office building where the research was conducted. The remaining 10 employees were based in offices in three other different cities and were not directly involved in the research. Events’ main business was to organize the participation of Brazilian companies in international trade exhibitions. The organization of exhibitions and conferences, product promotion and market analysis were among Events’ main secondary activities.



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Initially, three PI groups were formed involving the CEO and the company’s directors. All three groups had from five to seven members, were led by the CEO and facilitated by the researcher. Most of the members were the same in the three groups; the main difference being the process considered by each group for redesign. These groups targeted core organizational processes and redesigned those processes in a radical way. Group members decided to meet only face-to-face, and unanimously refused to use the EC system (already available to the directors, but unavailable to most of the other employees). In their opinion, the EC system was not ‘safe enough’ to be used as a medium for group discussions. According to most of the group members, the EC system kept a written record of their supposedly confidential discussions (where layoffs were discussed, for example) that could easily be accessed by anyone with above-average computer skills, and potentially distributed to all employees thereafter. The three PI groups conducted over 20 face-to-face meetings. These meetings, whose duration ranged from 2 to 10 h, were alternated with periods of intense collection and analysis of performance-related data, which were assembled by the group facilitator (i.e. the researcher). A number of PI groups targeting processes that involved only one or a few departments were conducted concurrently with the three core PI groups mentioned above. Most of these groups lasted no more than 1 month; some lasted as little as 3 days. Group duration seemed to have been generally correlated with target process scope; the shortest groups being those targeting very localized processes at the departmental level. About 4 months after the research iteration was begun, eight PI groups had completed their work. These groups met exclusively face to face, as the EC system was unavailable at that stage, and were typically led by managers. As the company had 60 employees working in the same building, and considering that a group would last on average 4 weeks, the company’s maximum PI group capacity (i.e. number of possible PI groups during a certain period of time) would have been approximately eight seven-member groups at any given time, or an average of 24 such groups per quarter (or 32 groups per 4-month period). As the numbers above suggest, several employees chose not to participate in PI groups. A number of these employees justified their lack of participation by pointing to the likely disruption that attending face-to-face PI meetings would have on their routine duties. They argued that they would often be engaged in external activities (e.g. meeting with a client) during scheduled PI group meetings, which usually put them off becoming members of PI groups. Given that nearly all employees at Events had access to a networked computer, this called for the introduction of the EC prototype developed by the researcher as a tool to allow PI group members to interact with each other from their own computers at different times. During the 3 months immediately after the introduction of the EC tool, the number of completed PI groups nearly doubled to approximately 15 groups. Most of the group members reported having used the EC system for PI-related interactions during approximately two-thirds or more of their total discussion time in PI groups. According to those members, the remaining one-third was spent in one-on-one phone or face-to-face conversations and group faceto-face meetings (in most of the cases without the presence of all group members). Several


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group leaders and facilitators reported feeling the need to resort to face-to-face interactions whenever, in the words of a group leader, ‘. . . the other members didn’t seem to understand what I was trying to say . . .’ or ‘. . . the issues being discussed were too risky to comment on via [the EC system] . . .’. The CEO and a number of senior managers reported great satisfaction with the outcome of the PI groups in general. One of these senior managers reported that: ‘. . . we have never been through such a successful motivational endeavour since the firm was founded’. PI groups were also reported as having improved the relationship between middle managers and their subordinates. A few managers reported being impressed, when browsing through public PI group mailboxes held in the EC system, by the awareness of workers about the problems of the company and their willingness to find solutions. Most managers previously thought such awareness was non-existent, which had often led to manager–subordinate conflict and was perceived by both groups as having been detrimental to co-operation in previous interlevel face-to-face PI efforts. In addition, leadership in local PI groups seemed to have been affected by EC support. In none of the eight face-to-face groups conducted early on in the research iteration, for example, did a junior employee leading the group invite the CEO or one of the directors to participate in the group. As soon as EC support was made available to PI groups, however, a few groups led by junior employees included the CEO and some of the directors as members. EC support was also seen by one manager as having increased the capacity of the company to cope with relatively simple problems at a local level, thus increasing the company’s ability to ‘learn’ (in the sense proposed by Senge, 1990). For example, after one international event where some problems were detected at the check-in and stand assembly processes, groups were immediately formed and came up with PI proposals that were seen by this manager as being of high quality, and likely to be effectively implemented before the next international event. The manager offered this as an indication that Events’ ability to learn and adapt to change was ‘. . . spreading over the company’s body, rather than concentrating in its head . . .’.

Second stage: close facilitation of PI groups at Waikato and MQM In the second stage of this research, six PI groups were closely facilitated by the researcher at Waikato over approximately 1 year and 6 months, beginning in June 1995. Over 60 staff and faculty from 15 different departments participated as PI group members. At that time, Waikato had 550 faculty and 750 staff, all based in the same campus in Hamilton, New Zealand. Waikato’s yearly revenues were approximately US$ 83.3 million. In addition, the researcher closely facilitated six other PI groups at MQM over approximately 7 months, beginning in September 1995. Forty-seven employees from 18 different offices participated as PI group members. At the time this study was conducted, MQM employed approximately 2500 people at a number of offices throughout New Zealand. These offices typically housed 5–200 people each, depending on the geographical area covered by them (e.g. a small town and its vicinities, or a large metropolitan area) and services supplied. Most services could be categorized as inspection audits, based on government regulations and industry standards,



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Table 1. PI groups conducted at Waikato and MQM

No. of members

Duration (days)

Departments involved

Change scope

Process description

W1 W2 W3 W4 W5

7 8 11 7 13

33 41 32 45 33

2 5 5 5 8

I B B I I

Teaching a university course Providing academic advice Providing computer support Handling student assignments Supporting graduate students

W6 M1 M2 M3 M4 M5 M6

11 5 5 7 11 15 14

54 26 25 14 29 28 10

4 1 1 1 4 6 3

I D I B B D I

Orienting international students Providing software support Editing the internal newsletter Reporting on an outbreak Providing quality consulting Providing hardware support Co-ordinating staff training

Group

Change scope: D, departmental; I, interdepartmental; B, business.

and related training and consulting services aimed at helping audited organizations comply with regulations and standards. MQM’s yearly revenues were approximately US$ 105 million. This action research intervention was headquartered at an office with 150 people. As a consequence, although a number of the participants were from other offices, all PI group leaders in this research interaction were housed in that office. The PI groups conducted at Waikato and MQM are listed in Table 1 as W1–W6 (Waikato) and M1–M6 (MQM) along with some of their main features. The columns in Table 1 show, from left to right: the name of the group; the number of group members; the duration of the group in days; the number of departments represented in the group; the scope of change of the group; and a brief description of the main process targeted by the group. Three scopes of change were used in the classification of PI groups: ‘D’, or departmental; ‘I’, or interdepartmental; and ‘B’, or business. The scope of change of a group was said to be ‘D’, when the process redesigned was totally contained in only one department; ‘I’, when the process redesigned spanned more than one department, but not a whole business unit; and ‘B’, when the process redesigned spanned a whole business unit. Business units were characterized by being at the first divisional level under Waikato University’s president and MQM’s CEO. One example of participating business unit at Waikato was the School of Management Studies, which itself comprised a number of related academic departments. At MQM, two examples of participating business units were the Food and Plant divisions, which provided inspection and consulting services to food and plant-related businesses in New Zealand respectively. The total quality and business process re-engineering movements have repeatedly been placed at opposite extremes of a scale measuring degree and scope of process change in organizations (Hammer, 1990; Hammer & Champy, 1993; Davenport, 1993a,b). Analogously, the PI groups in this research with scope of change ‘D’ can be seen as resembling typical quality improvement groups used in TQM projects – e.g. quality circles (Hutchins, 1985;


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Robson, 1988). PI groups whose scope of change is ‘B’ can be seen as resembling business process re-engineering groups. And, PI groups whose scope of change is ‘I’ can be seen as somewhere in between quality management and re-engineering groups. Most of the PI groups conducted at Waikato and MQM generated process change proposals that were later implemented either partially or as a whole. In most of these cases these implementations led to quality and productivity improvements in the processes targeted by the groups. One group at Waikato (W3) and two groups at MQM (M4 and M6) failed to generate process redesign proposals due to a lack of consensus and (or) participation among group members.

R E S E A RC H F I N D I N G S

In the following sections, we describe research evidence related to effects on two main dependent variables which emerged from the iterative coding process employed. These main dependent variables are organizational PI efficiency and PI group outcome quality. Later in the paper we discuss two main causal models which incorporate the research variables and respective variable-pair-effect links identified through the iterative coding process.

Organizational PI efficiency Organizational PI efficiency can be seen as the productivity of the PI meta-process (i.e. the meta-process carried out by process improvement groups). Process productivity, in turn, can be seen as the ratio between the production capacity of a process and its cost (Misterek et al., 1992; Horne, 1996). Therefore, organizational PI efficiency has been operationally defined as the ratio between organizational PI groups capacity, i.e. the number of PI groups that can be run in an organization over a given period of time, and the cost of those PI groups for the organization.

Organizational cost of PI groups There is evidence in this research that the cost of running PI groups was considerably reduced by the availability of EC support. Unstructured interview and participant observation evidence from Events suggests that EC support reduced disruption costs, caused by employees having to attend PI group discussions and in consequence neglect routine duties. At Waikato, several group members noted that EC support had considerably reduced the time they had to commit to PI group discussions, in comparison with previous face-to-face PI groups in which they had participated. At MQM, 14 out of 18 structured interview respondents, i.e. approximately 78 per cent of the respondents, perceived the organizational cost of their PI groups as having been reduced by the EC support (see Table 2). Most of these respondents described the reduction in cost as being ‘drastic’. In their view, cost reduction had been caused by a reduction in the time



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Table 2. EC support effect on the organizational cost of PI groups Answer Decreased Had no effect Increased Do not know

Frequency

Percentage

14 2 1 1

77.8 11.1 5.6 5.6

Eighteen respondents, c2 = 17.5, d.f. = 2, P < 0.001.

spent by each member with the group discussion, particularly for ordinary members and to a lesser extent for group leaders. The reduction in time was estimated at approximately 93% for ordinary members and 65% for group leaders, by members who had previously participated in face-to-face PI groups. These same estimates suggested a minimum absolute cost reduction of US$ 2415 for a nine-member PI group, calculated based on the mean hourly cost of MQM employees to the organization (including salary, benefits and overhead expenses). As travel expenses were disregarded, this is a very conservative saving estimate for a geographically dispersed organization such as MQM. There was also a striking lack of evidence regarding the opposite effect, that is, that EC support increased the cost of running PI groups. No spontaneous remarks by PI group members pointed to an increase in group cost due to EC support (negative remarks are an important source of evidence in emergence-focused data coding and analysis). Only one PI group member perceived such increase in the structured interviews (as can be seen in Table 2) conducted at MQM. This member had been a leader of his PI group, which led him to spend more personal time than the other members in the group discussion. Also, his group failed to generate a PI proposal, which led him to later state that he felt upset about the whole group discussion, and that as a result he had developed a negative bias regarding EC support impacts.

Organizational PI groups capacity One of the factors determining organizational PI groups capacity that emerged from this research is group duration. Obviously, a reduction in the duration (measured in days) of the average PI group would allow for more PI groups to be conducted per unit of time (e.g. per quarter or per semester), other factors remaining the same. This could be presented as an explanation for the sudden twofold increase in the number of PI groups per quarter at Events, which occurred immediately after the EC system was made available to PI groups. Yet, the evidence regarding a reduction in PI group duration due to EC support suggests that this effect was not as significant as that on organizational PI group cost. A large proportion of structured interview respondents at MQM, nearly 78 per cent (see Table 3), perceived EC support as having reduced PI group duration in days. Very few of these respondents perceived this reduction as being drastic.


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Table 3. EC support effect on PI group duration Answer Decreased Increased Had no effect Do not know

Frequency

Percentage

14 2 1 1

77.8 11.1 5.6 5.6

Eighteen respondents, c2 = 17.5, d.f. = 2, P < 0.001.

Group set-up time is decreased. The main cause for the reduction in group duration, according to the respondents, was a reduction in group set-up time. Group set up time was generally described by respondents as the time needed to accomplish group set-up activities such as defining a list of problems (or improvement opportunities) to be discussed by the group, selecting group members and inviting those members to take part in the group. It was also described as involving other activities more typical of face-to-face meetings, such as choosing and preparing a venue for the meetings and co-ordinating member attendance to the meetings. The negative influence of an increase in member response time, however, appeared to have countered the positive influence of a reduction of group set up time. As Table 3 indicates, about 11 per cent of the respondents (two of the respondents) thought that EC-supported PI groups lasted longer than similar face-to-face groups. These respondents were unanimous in their explanation, which pointed to an increase in feedback delay. The following quote, from a structured interview, is illustrative: Individually, [it is] probably faster to send an e-mail than ring around [i.e. use the telephone]. However, I have no idea how long it took people to read their E-mail and respond. Sometimes this is where the delays are caused and it can work out quicker to ring around. Members may take longer to respond to electronic messages than to oral requests made over the telephone or in a face-to-face meeting. The analysis of the mean times ordinary group members took to reply to postings from leaders at MQM and Waikato supports this perception. This analysis is summarized in Table 4, which shows the mean response time to leaders’ postings in each of the groups and the normalized variation (in standard deviations) of these means around the overall mean for each of these two organizations. Table 4 also shows the mean, minimum and maximum response times for each organization. The overall mean response time to postings from the leader was found to be 138 h (about 5. 1/2 days) for Waikato, and 80 h (about 3 1/3 days) for MQM. The normalized variation of this measure along groups was relatively low (up to 0.61 standard deviations around the mean, except for W5). In spite of this, even the lowest mean response time of 44 h is obviously much higher than one could expect in uninterrupted face-to-face meetings (i.e. meetings where the discussion flow is continuous, such as in the EC-support PI groups in this study). For example, McQueen’s (1991, chapter 4) study of 10 face-to-face business meetings yielded a mean transaction time of 12 s, where transaction time was defined as a change of speaker in the



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Table 4. Mean response times to EC postings from the group leader Group W1 W2 W3 W4 W5 W6

M1 M2 M3 M4 M5 M6

Mean response time (h)

Variation around mean*

51 76 71 200 277 128

–0.57 –0.37 –0.42 –0.61 1.23 0.04

m (Waikato) = 123 h, s = 126 h, range: 1–525 h 44 –0.51 54 –0.37 67 –0.18 46 –0.49 102 0.33 114 0.50 m (MQM) = 80 h, s = 69 h, range: 1–245 h

* In units of s.

meeting. Thus, a conservative mean response time estimate would be no more than 1 h in an uninterrupted face-to-face discussion. Given this, the ratio between mean reply time in ECsupported and face-to-face meetings can be estimated at 80 or greater. The influence of a reduction of group interaction seemed again to shift the balance towards decreased group duration, as initially perceived by most interview respondents at MQM. In both Waikato and MQM a marked decrease in group interaction, defined as the number of individual contributions in each group discussion, was observed as a result of the use of the EC system. As a basis for comparison, an aggregate analysis of McQueen’s (1991; chapter 4) research data on face-to-face meetings suggests a mean of approximately 42 individual contributions per hour per member in a seven-member group. In none of the groups facilitated at MQM and Waikato did this figure exceed 4.2 individual EC contributions per member. This was true even when the figure was calculated by dividing the total number of individual EC contributions in the group by the number of ‘active’ members only; active members being defined as those who contributed at least one EC group posting (see Table 5). In some of the PI groups in Table 5, part of the group (i.e. many-to-many) and one-on-one interactions were conducted through face-to-face meetings (e.g. W4, W6, M1, M3). However, in several of the PI groups investigated (e.g. W1, W2, M4, M5) all of the group interactions were conducted through the EC system. We can, thus, conclude that EC support generally tended to decrease group interaction, and therefore contributed towards a reduction in group duration (the relationship between group interaction and duration has been a recurring theme in the GSS literature – see, for example,Ellis et al. (1991). Group demand for senior leadership emerged from our research as an important factor in the increase of organizational PI groups capacity. At Events, not only was there a sharp increase in the number of PI groups per quarter after the EC system was made available,


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Table 5. Group degree of interaction Group interaction

No. of members

No. of active members

No. of EC postings

All members

Active members

W1 W2 W3 W4

7 8 11 7

5 8 7 5

21 30 23 15

3.0 3.8 2.1 2.1

4.2 3.8 3.3 3.0

W5 W6 M1 M2 M3 M4 M5 M6

13 11 5 5 7 11 15 14

8 7 3 4 3 7 11 6

22 15 7 9 4 18 23 6

1.7 1.4 1.4 1.8 0.6 1.6 1.5 0.4

2.8 2.1 2.3 2.3 1.3 2.6 2.1 1.0

Group

there was also a marked change in the leadership composition of these groups. In none of the eight face-to-face groups conducted early on in that study, when EC support was unavailable, did a junior employee leading the group invite the CEO or one of the company’s directors to participate in the group. As soon as the EC support was made available to PI groups, however, a few groups led by junior employees included the CEO and some of the directors as members. This can be seen as an indication that EC support may have made it easier for junior members to lead PI groups with a mixed composition in terms of hierarchical levels in the organization. At Waikato, some group leaders spontaneously remarked in unstructured interviews that EC support had made it considerably easier for them to lead PI groups. None of these leaders were the most senior members of their groups. Group W1’s leader, for example, was the most junior person in his group. One of his perceptions was that ‘. . . leading a face-to-face meeting would be considerably more demanding and stressful for me . . .’. He perceived his junior position in the organization as likely to have considerably hindered him from leading the PI group, had the group had only face-to-face discussions. Both at Waikato and MQM similar reasons were given for the EC support-induced reduction of demand for leadership seniority. The most common among these reasons were: (a) a suppression of social cues, which could differentiate junior from senior members; (b) a reduction in the influence that individual members have on the group, which was seen as likely to increase with seniority in face-to-face groups; and (c) a suppression of hierarchy barriers to an open discussion. The following quote, from a group leader, provides a good illustration of these perceptions: Normally if I am in a [face-to-face] situation and with [another member’s name – removed], who is my boss, his opinion counts over mine, when I’m sitting in the same room . . . on e-



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Table 6. EC support effect on factors influencing group demand for senior leadership Member perception No effect

Don’t know

c2 ( d.f. = 2)

Factor

Decreased

Increased

Social cues Waikato (n = 46)

36 (78.3%)

0 (0%)

10 (21.7%)

0 (0%)

>100 (P < 0.001)

Member influence Waikato (n = 46)

32 (69.6%)

3 (6.5%)

10 (21.7%)

1 (2.2%)

33.4 (P < 0.001)

Member influence MQM (n = 18)

8 (44.4%)

2 (11.1%)

7 (38.9%)

1 (5.6%)

3.5 (P = 0.174)

Hierarchy barriers MQM (n = 18)

13 (72.2%)

0 (0%)

3 (16.7%)

2 (11.1%)

15.7 (P < 0.001)

mail I feel just as equal – I don’t feel that he will influence me or that his opinion will be more important than mine. Because I feel like I can just freely put my ideas on an e-mail and I don’t feel threatened by him being above me. You [referring to PI group members in general] are all equals on e-mail . . . I definitely don’t think about the hierarchy structure when I’m on e-mail, but I do think about it when I’m sitting in a room and I see [names of two other group members – removed] sitting there. And they get a lot more influential because of that, because everybody is a bit more wary of what they say, whereas on email people are more likely to say what they’ve got to say. As shown in Table 6, all of these reasons, except reduction in member influence in MQM, represented statistically significant trends. Although the high P (chi-square test) associated with perceptions of the effect of EC support on member influence at MQM may have been caused by MQM being a more hierarchical type of organization than Waikato, it could also be explained by the smaller sample surveyed in that organization (n = 18). A reduction of group demand for senior leadership may be directly linked with increased organizational PI groups capacity, as suggested by the sharp increase in the number of PI groups per quarter at Events. Such a link may be explained based on the usually low number of senior employees and the nature of their work. In most organizations there is only a small number of people in senior positions compared with junior staff. This situation is compounded by the fact that senior employees tend to take on management roles, which tend to prevent them from engaging in focused, long-term PI group discussions (Mintzberg, 1975; Kurke & Aldrich, 1983). EC support, by allowing junior members to become PI group leaders, considerably increases the possible number of PI groups in an organization at a given time.

PI group outcome quality At Events, there was no clear evidence that the quality of the outcomes of PI groups had been either increased or decreased by EC support. The overall trend in the perceptions of


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Table 7. EC support effect on PI group outcome quality Member perception Organization (sample)

Increased

Decreased

No effect

Don’t know

c2 ( d.f. = 2)

Waikato (n = 46) MQM (n = 18)

22 (47.8%) 6 (33.3%)

10 (21.7%) 3 (16.7%)

11 (23.9%) 6 (33.3%)

3 (6.5%) 3 (16.7%)

5.97 (P = 0.05) 1.50 (P = 0.472)

both former PI group members was that EC support had a strong impact only on group efficiency. This perception trend matched the one from non-members who had closely observed some of the PI groups and had been affected by group-proposed process changes. At Waikato and MQM, the general trend of the perceptions seemed similar to those at Events. A slight trend towards a perceived group outcome quality increase could be noticed, but the statistical strength of this trend was relatively low, particularly at MQM. As shown in Table 7, the Chi-square analysis of the distribution of perception frequencies at Waikato or MQM do not allow for the rejection of the null hypothesis (i.e. that the perceptions were due to chance) in either case, with at least 95 per cent of certainty. It is important to note, however, that if the frequencies in the column ‘Don’t know’ had been considered, then the results of the Chi-square test would have been c2 (d.f. = 3) = 16.09 (P = 0.0011) for Waikato and c2 (d.f. = 3) = 2 (P = 0.5724) for MQM. That would indicate a statistically significant perception trend for Waikato. However, the column ‘Don’t know’ was disregarded in this analysis, as in the previous Chi-square tests in this paper. The reason is because its consideration could have overstated the Ps by introducing a degree of freedom related to a perception that would typically be low in frequency. On the other hand, it can be inferred from Table 7 that there was a general and statistically strong trend towards perceiving EC support as not having impacted group outcome quality negatively. At Waikato, about 72 per cent of the respondents viewed EC support as having increased or not having affected group outcome quality; at MQM, this proportion was about 66 per cent. This contrasts with PI group member perceptions at the beginning of group discussions, immediately after the EC system’s use began. These perceptions were consistent with the media richness theory (Daft & Lengel, 1986; Daft et al., 1987; Lengel & Daft, 1988), which argues that group discussions conducted on a medium such as EC are likely to be more ambiguous, and therefore lead to a lack of ‘discussion quality’, than face-to-face discussions. The two following quotes from PI group members illustrate this point: People read different things on e-mail. [Member’s name – removed], for example, was misunderstood as volunteering to do something, when in fact she had made just a supportive comment. I sometimes feel that things are left hanging because with e-mail people can understand different things out of the same message. At the end of the day I think you should have a face-to-face meeting not to leave things hanging.



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Table 8. Media of interaction and mean contribution length in each group Proportion of interaction time EC/other media (%)

Mean EC contribution length (words)

W1 W2 W3 W4 W5

71/29 81/19 96/4 77/23 52/48

258 291 293 320 317

W6 M1 M2 M3 M4 M5 M6

75/25 83/17 89/11 18/82 80/20 77/23 67/33

267 296 225 218 234 214 163

Group

In spite of the higher ambiguity, all of the PI groups, except for M3, chose the EC system as their main discussion medium. This is shown in Table 8, where the second column shows the mean proportion of time spent interacting through the EC system and through other media (e.g. face to face and telephone). Table 8 also shows the mean contribution length (through the EC system only) in words for each PI group, defined as the mean word count per posting for each PI group. Table 8 shows that the mean contribution length through the EC system varied from 163 to 320 words, which is considerably higher than one could expect in face-to-face meetings. For example, the lowest mean contribution length of 163 words is substantially higher than the mean contribution length in the face-to-face business meetings obtained by McQueen (1991; chapter 4) of 18 words (i.e. in those face-to-face meetings the mean oral contribution had only 18 words). This suggests that individual EC contributions, although less frequent (EC support reduced group interaction), were much longer than in similar face-to-face meetings. Individual EC contributions also appear to have taken longer to be prepared and posted to the group than oral contributions in face-to-face meetings. This is illustrated in Table 9, which shows that the mean contribution speed was six words per minute through the EC medium. This number is in sharp contrast with the 113 words per minute obtained by McQueen (1991, Chapter 4) in his analysis of face-to-face business meetings. The contribution speed in the EC medium was calculated based on group members’ estimates of time spent preparing and posting contributions to their groups and the actual word count of their postings. The numbers calculated for the facilitator and group leaders were based on direct measurement during participant observation, and are therefore highly reliable, although based on smaller samples. The low contribution speed through the electronic medium cannot be explained based on the fact that ‘typing is slower than speaking’, because average typists have been found to be able


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Table 9. Mean contribution speed through EC Source Facilitator Group leaders Ordinary members Mean

Sample size*

Words per min

5 12 103

6.93 5.29 5.92 6

* Electronic postings.

to type between 60 and 70 words per minute. A more plausible explanation is that the postings were better prepared, when compared with oral contributions in face-to-face meetings, which is consistent with the fact that EC support has also led to longer contributions. An improvement in the quality of individual contributions was also the main reason provided by interview respondents to explain their perception of an increase in PI group outcome quality. The second main reason was the higher departmental heterogeneity in PI groups enabled by the EC system. That is, EC support allows for the participation of members from several departments in PI groups, due to its asynchronous and distributed nature (which is an intuitively plausible finding). Regarding the less intuitive reason provided, the increase in the quality of individual contributions through the EC medium, the following quote from a PI group is illustrative. You think more when you’re writing something, so you produce a better quality contribution. Take for example what [member’s name – removed] wrote, she wrote a lot and it seemed that she thought a lot about it before she e-mailed it to the group. She was not just babbling off the top of her head, she tended to think out what she was writing. I know I did it a lot, specially my first message. I really thought a lot to put it together. This suggests that the voluntary adoption of the EC system led members to adapt their behaviour in order to overcome the limitations posed by the new medium, which was seen as ‘leaner’ when compared with the face-to-face medium. The adaptation consisted in preparing longer and better thought out contributions. This adaptive behaviour appears to have partially offset the communication constraints posed by the EC system, leading to the neutral effect on PI group outcome quality.

S U M M A R I Z I N G T H E F I N D I N G S : T W O C AU S A L M O D E L S

The findings of this research can be summarized in two main explanatory causal models. They are called explanatory because they summarize the research findings, rather than trying to generalize them (although we believe the models embody some degree of generality, given the relatively large and heterogeneous body of research data they are based on). Below we present and discuss both causal models. The first model has organizational PI efficiency as its dependent variable; the second model relates to PI group outcome quality.



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Figure 1. EC support availability effect on organizational PI efficiency.

Organizational PI efficiency The explanatory causal model in Figure 1 indicates that EC support causes a decrease in the organizational costs associated with PI groups. Organizational PI effectiveness is defined as the ratio between the organizational PI groups capacity (i.e. the number of possible PI groups per unit of time) and the organizational cost of PI groups. Therefore, this decrease in costs contributes, by definition, towards an increase in the variable organizational PI efficiency. The decrease in the variable organizational cost of PI groups combines with an increase in organizational PI groups capacity to generate an increase in organizational PI efficiency. That is, EC support increases organizational PI efficiency by reducing the cost of running PI groups as well as increasing the possible number of PI groups per unit of time (e.g. a quarter) in an organization. Organizational PI groups capacity seems to be increased by the combination of a moderate decrease in group duration and a large decrease in the group demand for senior leadership. A moderate group duration decrease leads to a moderate increase in the number of PI groups that can possibly be conducted per unit of time. A large decrease in group demand for senior leadership, on the other hand, leads to a large increase in the number of people able to lead PI groups in the organization, particularly people who are viewed as being at lower hierarchical levels relative to other group members. It gives virtually everyone in the organization, not only managers, the chance to lead PI groups, and therefore largely increases the number of PI groups that can be run concurrently in the organization.


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EC support appears to lead to a group set up time decrease, by allowing PI group discussions to be started with no delays, and to decreased group interaction. Apparently, the low disruptiveness of the EC system, combined with little participation control and the extra effort required from members to contribute postings (evidenced by a drastic reduction in member contribution speed through the EC medium), leads to decreased individual contributions. Also, a large increase in member contribution effort, combined with a decrease in member participation control, leads to a large increase in member response time. That is, members probably delay their contributions because they cannot be forced to quickly contribute postings that, in turn, take more time to be prepared. The combination of these effects leads to a moderate reduction of group duration.

PI group outcome quality The causal model shown in Figure 2 indicates that EC support increases group departmental heterogeneity. It does so by allowing for time–disconnected interaction from several different locations, eliminating time and distance constraints to group communication. The model also indicates that member contribution quality is increased. The two effects combined contribute towards and increase in PI group outcome quality. A negative effect of EC support indicated in the causal model in Figure 2 is that it apparently increases group discussion ambiguity, by, for example, eliminating non-verbal cues that add extra meaning to words and sentences, as well as adding feedback delay into the communication. Postings tend to take some time to be replied to, which may lead to some confusion as to what they are actually referring to when they eventually reach the group. This effect,

Figure 2. EC support availability effect on organizational PI efficiency.



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however, seems to be partially offset by an increase in member contribution quality, leading to an apparently neutral overall effect on the variable PI group outcome quality.

C O N C LU S I O N A N D I M P L I C AT I O N S

Our research findings generally suggest that asynchronous group support (represented by the EC support) is more likely to be beneficial than detrimental to PI groups, hence providing support to the recommendation that organizations should use asynchronous group support technologies to support PI projects. Our research findings are consistent with previous findings regarding synchronous GSS effects on PI groups, and with most of the empirical literature on synchronous GSS. These indicate major group process efficiency and slight group outcome quality gains (Dennis et al., 1994; Reinig et al., 1995). However, there seems to be a stark contrast in the reasons why these gains are achieved when synchronous and asynchronous GSSs are considered. GDSS effects on group process efficiency and group outcome quality have often been associated with an increase in the quantity of ideas generated by the group and a reduction in group discussion time in hours (Nagasundaram & Bostrom, 1995). Our findings suggest other factors related to EC support such as, regarding group process efficiency, a large reduction of group interaction (partially compensated by an increase in contribution length) and a large decrease of group set-up costs. Regarding group outcome quality, main factors were an increase in the quality of individual contributions, rather than in the number of contributions as in GDSS-supported groups. That is, in EC-supported groups, the number of individual contributions seems to be largely reduced, whereas the length of individual contributions seems to be considerably increased, in comparison with face-to-face meetings. Moreover, although EC support is perceived as reducing the duration of PI groups when compared with no GSS support at all, it seems to foster more reflection on the part of the members. These findings raise serious doubts about the appropriateness of the current GSS research focus, pointed out by Nagasundaram & Bostrom (1995), on the analysis of the number of ideas generated as a measure of group effectiveness. The analysis of the performance and outcomes of some of the PI groups indicates that group success is unrelated to the number of individual contributions or ideas.

AC K N O W L E D G E M E N T S

I would like to thank Bob McQueen for his advice, for sharing his research data about faceto-face groups with me, and for his support throughout this research; the group members at Events, MQM and the University of Waikato, for their participation in the process improvement groups and for sharing their impressions in interviews and informal conversations with the researcher; and Peter Grace, Andrea Jenkins and Robert Wellington, for their help in the collection and analysis of research data.


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Biography Ned Kock is CIGNA Research Fellow in the Fox School of Business and Management, and teaches information systems courses in the departments of Management Information Systems and Computer and Information Sciences, Temple University. He holds a PhD in information systems from the University of Waikato, New Zealand. Ned has been working as a systems analyst and organizational development consultant since 1987, having provided services to several companies including HSBC Bamerindus Bank, PricewaterhouseCoopers, Johnson & Johnson, Rio de Janeiro State Construction Company, Westaflex, New Zealand Ministry of Agriculture and Fisheries, True North and Day and Zimmermann. He is the author of three books, including Process Improvement and Organizational Learning: The Role of Collaboration Technologies (Idea Group Publishing, 1999). He has also authored articles in a number of journals including Communications of the ACM, Journal of Organizational Computing and Electronic Commerce, Information & Management, Information Systems Journal and Information Technology & People. Ned is associate editor of the Journal of Systems and Information Technology, co-editor of ISWorld’s Professional Ethics Section, and member of the editorial board of the Journal of Information Technology Cases and Applications. Branches of the Brazilian, New Zealand and US governments, as well as several private organizations in these countries, have funded his research.
