Personal before businessin requirements prior-IT-ization

Johan F. Hoorn & Mark E. BreukerVrije Universiteit

Computer ScienceInformation Management and Software Engineering

jfhoorn@few.vu.nl

Contents

Problem Analysis Predictions Method Results Conclusions Discussion

Johan F. Hoorn, 2005

M M I 9 9 0 0 9

Problem How to anticipate requirements change, for example, in prioritization?

Johan F. Hoorn, 2005

Analysis Where do change requests come from?

Business model 1 Business model 2 Change in business sub goals - Main goals: Profit - Sub goals: Cost-effectiveness, efficiency

How come business goals change? Change in personal sub goals (strategic management) - Main goals: Earn my living - Sub goals: Fire employees (not me),

improve IT to guarantee same output

Johan F. Hoorn, 2005

Predictions If business or personal goals change, requirements prioritization will change accordingly

BM1: Traditional office BM2: Flexible workplace1 Mainframe 1 Laptops2 Thin clients 2 Bluetooth3 Laptops 3 Mainframe4 Bluetooth 4 Thin clients

Priority change

Method (1) Requirements rank-ordering test System: Blackboard (BM1) vs.

Didactor (BM2) Internet survey (the e-learning hoax) Stakeholders: Science students (N= 154) Four conditions of goal change: 1 From business egotistic to business altruistic (n= 36) 2 From business altruistic to business egotistic (n= 39) 3 From personal egotistic to personal altruistic (n= 43) 4 From personal altruistic to personal egotistic (n= 36)

Johan F. Hoorn, 2005

Condition 1: From business egotistic…

Students putrank numbers1 up to 16

Differentrandomizationbetween andwithin students

…to business altruistic

For business altruistic toegotistic, theMotivation order wasreversed

Students, again,put rank numbers1 up to 16

Interviews with students of the Free University showed thatstudents want to benefit more from the knowledge economy.They belief that students should enter the market while beingtop qualified. To get a well paid job, they think that governmentalsubsidies should be invested in advanced technology and learning materials that support the individual student. Fromseveral options, the students chose the new digital learningenvironment Didactor® as the best alternative.

Likewise for personal egotistic…

Interviews with students of the Free University showed thatstudents feel socially responsible for developing the knowledgeeconomy. They belief that investments on top qualified masters should show some returns to society. They think that governmental subsidies should be invested in advanced technology and learning materials with which students cansupport one another. From several options, the students chose the new digital learning environment Didactor® as the best alternative.

…to personal altruistic and v.v.

Method (2) Calculating priority change Spearman’s rho (S) is a rank order correlation coefficient that analyzes whether a bivariate set of paired rankings correlates by rank sum

S was calculated for each student in a condition

S (altru to ego) S (altru to ego) S (ego to altru)

(Business) (Personal)

161423791110815

159513611248145

167119310614158

237912116413146

S (ego to altru)

Johan F. Hoorn, 2005

6 ΣD2

S = 1 – N(N2 – 1)

Method (3) Four measures of priority change S1 over data of those who filled in both lists (N= 103) S2 over data of the 10 features that best contributed to S= -1 (N= 92) S3 feature to feature rank-order total-scores,* using data of all those who filled in the first list (N= 154) S4 feature to feature rank-order total-scores* over data of the 10 features that best contributed to S= -1 (N= 154) *(see paper or last slides)

Rho moves between 1 and -1. The closer S approaches -1, the higherthe disagreement between the two sets of ranked features

(= priority change) Johan F. Hoorn, 2005

Johan F. Hoorn, 2005

Only S3 (feature to feature rank-order total-scores),* usingdata of all students who filled in the first list (N= 154),rendered significant results

*(see paper or last slides)

Results (1)

Main effect (Business vs. Personal):F(1,146)= 4.09, p< .05, ηp

2= .03

The onlysignificant difference

Mean S3 = .60(priority changeis low)

Mean S3 = .48(priority changeis high)

Johan F. Hoorn, 2005

Results (2)

RE should be oriented to personal goals Changes in personal goals had the most impact on changes in requirements prioritization This effect occurred irrespective of the type of goal change (from egotistic to altruistic or v.v.) Business model change had less impact on changes in requirements prioritization

Johan F. Hoorn, 2005

Conclusions

Effects were not too strong (ηp2= .03).

Replication in a business case is urgent

Johan F. Hoorn, 2005

Discussion

Appendix (1)Calculating S3 (feature to feature rank-order total-scores)

Only the data of the first requirements list were used(N= 154)

For each feature, the sum of rank-order scores was computed across all students in a condition (e.g., Businessegotistic (Be) or Personal altruistic (Pa))

On the basis of the rank-order total score per feature(which were between 91 and 576), the 16 features were then rank-ordered from the lowest to the highest rank-order total score

Johan F. Hoorn, 2005

Subsequently, the actual rank-order total score of a featurewas replaced by the rank order number of their relative position in this general priority list. The feature with thelowest rank-order total score (= 91) received a 1 and thefeature with the highest rank-order total score (= 576)received a 16

The feature to feature rank-order total-scores were established by calculating,for each student in a condition, s between

Be (as based on the raw data) and the revised Ba (as based on the rank-order total scores)Ba (as based on the raw data) and the revised Be (as based on the rank-order total scores)Pe (as based on the raw data) and the revised Pa (as based on the rank-order total scores)Pa (as based on the raw data) and the revised Pe (as based on the rank-order total scores)

Johan F. Hoorn, 2005

Appendix (2)