delphi technique rowe wright

International Journal of Forecasting 15 (1999) 353–375www.elsevier.com/ locate / ijforecast

The Delphi technique as a forecasting tool: issues and analysis

a , b*Gene Rowe , George WrightaInstitute of Food Research, Norwich Research Park, Colney, Norwich NR4 7UA, UK

bStrathclyde Graduate Business School, Strathclyde University, 199 Cathedral Street, Glasgow G4 0QU, UK

Abstract

This paper systematically reviews empirical studies looking at the effectiveness of the Delphi technique, and provides acritique of this research. Findings suggest that Delphi groups outperform statistical groups (by 12 studies to two with two‘ties’) and standard interacting groups (by five studies to one with two ‘ties’), although there is no consistent evidence thatthe technique outperforms other structured group procedures. However, important differences exist between the typicallaboratory version of the technique and the original concept of Delphi, which make generalisations about ‘Delphi’ per sedifficult. These differences derive from a lack of control of important group, task, and technique characteristics (such as therelative level of panellist expertise and the nature of feedback used). Indeed, there are theoretical and empirical reasons tobelieve that a Delphi conducted according to ‘ideal’ specifications might perform better than the standard laboratoryinterpretations. It is concluded that a different focus of research is required to answer questions on Delphi effectiveness,focusing on an analysis of the process of judgment change within nominal groups. 1999 Elsevier Science B.V. All rightsreserved.

Keywords: Delphi; Interacting groups; Statistical group; Structured groups

1. Introduction been largely inappropriate, such that our knowledgeabout the potential of Delphi is still poor. In essence,

Since its design at the RAND Corporation over 40 this paper relates a critique of the methodology ofyears ago, the Delphi technique has become a widely evaluation research and suggests that we will acquireused tool for measuring and aiding forecasting and no great knowledge of the potential benefits ofdecision making in a variety of disciplines. But what Delphi until we adopt a different methodologicaldo we really understand about the technique and its approach, which is subsequently detailed.workings, and indeed, how is it being employed? Inthis paper we adopt the perspective of Delphi as ajudgment or forecasting or decision-aiding tool, and 2. The nature of Delphiwe review the studies that have attempted to evaluateit. These studies are actually sparse, and, we will The Delphi technique has been comprehensivelyargue, their attempts at evaluating the technique have reviewed elsewhere (e.g., Hill & Fowles, 1975;

´Linstone & Turoff, 1975; Lock, 1987; Parente &´Anderson-Parente, 1987; Stewart, 1987; Rowe,*Corresponding author. Tel.: 144-1603-255-125.

E-mail address: [email protected] (G. Rowe) Wright & Bolger, 1991), and so we will present a

0169-2070/99/$ – see front matter 1999 Elsevier Science B.V. All rights reserved.PI I : S0169-2070( 99 )00018-7

354 G. Rowe, G. Wright / International Journal of Forecasting 15 (1999) 353 –375

brief review only. The Delphi technique was de- invalid criteria (such as the status of an idea’sveloped during the 1950s by workers at the RAND proponent). Furthermore, with the iteration of theCorporation while involved on a U.S. Air Force questionnaire over a number of rounds, the indi-sponsored project. The aim of the project was the viduals are given the opportunity to change theirapplication of expert opinion to the selection – from opinions and judgments without fear of losing face inthe point of view of a Soviet strategic planner – of the eyes of the (anonymous) others in the group.an optimal U.S. industrial target system, with a Between each questionnaire iteration, controlledcorresponding estimation of the number of atomic feedback is provided through which the group mem-bombs required to reduce munitions output by a bers are informed of the opinions of their anonymousprescribed amount. More generally, the technique is colleagues. Often feedback is presented as a simpleseen as a procedure to ‘‘obtain the most reliable statistical summary of the group response, usuallyconsensus of opinion of a group of experts . . . by a comprising a mean or median value, such as theseries of intensive questionnaires interspersed with average ‘group’ estimate of the date by when ancontrolled opinion feedback’’ (Dalkey & Helmer, event is forecast to occur. Occasionally, additional1963, p. 458). In particular, the structure of the information may also be provided, such as argumentstechnique is intended to allow access to the positive from individuals whose judgments fall outside cer-attributes of interacting groups (knowledge from a tain pre-specified limits. In this manner, feedbackvariety of sources, creative synthesis, etc.), while comprises the opinions and judgments of all grouppre-empting their negative aspects (attributable to members and not just the most vocal. At the end ofsocial, personal and political conflicts, etc.). From a the polling of participants (i.e., after several roundspractical perspective, the method allows input from a of questionnaire iteration), the group judgment islarger number of participants than could feasibly be taken as the statistical average (mean/median) of theincluded in a group or committee meeting, and from panellists’ estimates on the final round. The finalmembers who are geographically dispersed. judgment may thus be seen as an equal weighting of

Delphi is not a procedure intended to challenge the members of a staticized group.statistical or model-based procedures, against which The above four characteristics are necessary defin-human judgment is generally shown to be inferior: it ing attributes of a Delphi procedure, although thereis intended for use in judgment and forecasting are numerous ways in which they may be applied.situations in which pure model-based statistical The first round of the classical Delphi proceduremethods are not practical or possible because of the (Martino, 1983) is unstructured, allowing the in-lack of appropriate historical /economic / technical dividual experts relatively free scope to identify, anddata, and thus where some form of human judg- elaborate on, those issues they see as important.mental input is necessary (e.g., Wright, Lawrence & These individual factors are then consolidated into aCollopy, 1996). Such input needs to be used as single set by the monitor team, who produce aefficiently as possible, and for this purpose the structured questionnaire from which the views, opin-Delphi technique might serve a role. ions and judgments of the Delphi panellists may be

Four key features may be regarded as necessary elicited in a quantitative manner on subsequentfor defining a procedure as a ‘Delphi’. These are: rounds. After each of these rounds, responses areanonymity, iteration, controlled feedback, and the analysed and statistically summarised (usually intostatistical aggregation of group response. Anonymity medians plus upper and lower quartiles), which areis achieved through the use of questionnaires. By then presented to the panellists for further considera-allowing the individual group members the oppor- tion. Hence, from the third round onwards, panelliststunity to express their opinions and judgments are given the opportunity to alter prior estimates onprivately, undue social pressures – as from dominant the basis of the provided feedback. Furthermore, ifor dogmatic individuals, or from a majority – should panellists’ assessments fall outside the upper orbe avoided. Ideally, this should allow the individual lower quartiles they may be asked to give reasonsgroup members to consider each idea on the basis of why they believe their selections are correct againstmerit alone, rather than on the basis of potentially the majority opinion. This procedure continues until

G. Rowe, G. Wright / International Journal of Forecasting 15 (1999) 353 –375 355

a certain stability in panellists’ responses is achieved. of controlled experimentation or academic inves-The forecast or assessment for each item in the tigation that has taken place . . . (and that) asidequestionnaire is typically represented by the median from some RAND studies by Dalkey, most ‘evalua-on the final round. tions’ of the technique have been secondary efforts

An important point to note here is that variations associated with some application which was thefrom the above Delphi ideal do exist (Linstone, primary interest’’ (p. 11). Indeed, the relative paucity1978; Martino, 1983). Most commonly, round one is of evaluation studies noted by Linstone and Turoff isstructured in order to make the application of the still evident. Although a number of empirical exami-procedure simpler for the monitor team and panel- nations have subsequently been conducted, the bulklists; the number of rounds is variable, though of Delphi references still concern applications ratherseldom goes beyond one or two iterations (during than evaluations. That is, there appears to be awhich time most change in panellists’ responses widespread assumption that Delphi is a useful instru-generally occurs); and often, panellists may be asked ment that may be used to measure some kind of truthfor just a single statistic – such as the date by when and it is mainly represented in the literature in thisan event has a 50% likelihood of occurring – rather vein. Consideration of what the evaluation studiesthan for multiple figures or dates representing de- actually tell us about Delphi is the focus of thisgrees of confidence or likelihood (e.g., the 10% and paper.90% likelihood dates), or for written justifications ofextreme opinions or judgments. These simplificationsare particularly common in laboratory studies and 4. Evaluative studies of Delphihave important consequences for the generalisabilityof research findings. We attempted to gather together details of all

published (English-language) studies involvingevaluation of the Delphi technique. There were a

3. The study of Delphi number of types of studies that we decided not toinclude in our analysis. Unpublished PhD theses,

Since the 1950s, use of Delphi has spread from its technical reports (e.g., of the RAND Corporation),origins in the defence community in the U.S.A. to a and conference papers were excluded because theirwide variety of areas in numerous countries. Its quality is less assured than peer-reviewed journalapplications have extended from the prediction of articles and (arguably) book chapters. It may also belong-range trends in science and technology to argued that if the studies reported in these excludedapplications in policy formation and decision mak- formats were significant and of sufficient quality thening. An examination of recent literature, for example, they would have appeared in conventional publishedreveals how widespread is the use of Delphi, with form.applications in areas as diverse as the health care We searched through nine computer databases:industry (Hudak, Brooke, Finstuen & Riley, 1993), ABI Inform Global, Applied Science and Technolo-marketing (Lunsford & Fussell, 1993), education gy Index, ERIC, Transport, Econlit, General Science(Olshfski & Joseph, 1991), information systems Index, INSPEC, Sociofile, and Psychlit. As search(Neiderman, Brancheau & Wetherbe, 1991), and terms we used: ‘Delphi and Evaluation’, ‘Delphi andtransportation and engineering (Saito & Sinha, Experiment’, and ‘Delphi and Accuracy’. Because1991). our interest is in experimental evaluations of Delphi,

Linstone and Turoff (1975) characterised the we excluded any ‘hits’ that simply reported Delphigrowth of interest in Delphi as from non-profitmak- as used in some application (e.g., to ascertain experting organisations to government, industry and, final- views on a particular topic), or that omitted keyly, to academe. This progression caused them some details of method or results because Delphi per seconcern, for they went on to suggest that the was not the focus of interest (e.g., Brockhoff, 1984).‘explosive growth’ in Delphi applications may have Several other studies were excluded because weappeared ‘‘ . . . incompatible with the limited amount believe they yielded no substantial findings, or


because they were of high complexity with uncertain authors whether there were any evaluative studiesfindings. For example, a paper by Van Dijk (1990) that we had overlooked. The eight replies caused useffectively used six different Delphi-like techniques to make two minor changes to our tables. None ofthat differed in terms of the order in which each of the replies noted evaluative studies of which we werethree forms of panellist interaction were used in each unaware.of three ‘Delphi’ rounds, resulting in a highly Details of the Delphi evaluative studies are sum-complex, difficult to encode and, indeed, difficult to marised in Tables 1 and 2. Table 1 describes theinterpret study. characteristics of each experimental scenario, includ-

The final type of studies that we excluded from ing the nature of the task and the way in whichour search ‘hits’ were those that considered the Delphi was constituted. Table 2 reports the findingsuniversal validity or reliability of Delphi without of the studies plus ‘additional comments’ (which alsoreference to control conditions or other techniques. concern details in Table 1). Ideally, the two tablesFor example, the study of Ono and Wedermeyer should be joined to form one comprehensive table,(1994) reported that a Delphi panel produced fore- but space constraints forced the division.casts that were over 50% accurate, and used this as We have tried to make the tables as comprehen-‘evidence’ that the technique is somehow a valid sive as possible without obscuring the main findingspredictor of the future. However, the validity of the and methodological features by descriptions of minortechnique, in this sense, will depend as much on the or coincidental results and details, or by repetition ofnature of the panellists and the task as on the common information. For example, a number oftechnique itself, and it is not sensible to suggest that Delphi studies used post-task questionnaires to assessthe percentage accuracy achieved here is in any way panellists’ reactions to the technique, with individualgeneralisable or fundamental (i.e., to suggest that questions ranging from how ‘satisfied’ subjects feltusing Delphi will generally result in 50% correct about the technique, to how ‘enjoyable’ they found itpredictions). The important questions – not asked in (e.g., Van de Ven & Delbecq, 1974; Scheibe et al.,this study – are whether the application of the 1975; Rohrbaugh, 1979; Boje & Murnighan, 1982).technique helped to improve the forecasting of the Clearly, to include every analysis or significantindividual panellists, and how effective the technique correlation involving such measures would result inwas relative to other possible forecasting procedures. an unwieldy mass of data, much of which has littleSimilarly, papers by Felsenthal and Fuchs (1976), theoretical importance and is unlikely to be repli-Dagenais (1978), and Kastein, Jacobs, van der Hell, cated or considered in future studies. We have alsoLuttik and Touw-Otten (1993) – which reported data been constrained by lack of space: so, while we haveon the reliability of Delphi-like groups – are not attempted to indicate how aspects such as theconsidered further, for they simply demonstrate that dependent variables were measured (Table 2), wea degree of reliability is possible using the technique. have generally been forced to give only brief de-

The database search produced 19 papers relevant scriptions in place of the complex scoring formulaeto our present concern. The references in these used. In other cases where descriptions seem overlypapers drew our attention to a further eight studies, brief, the reader is referred to the main text whereyielding 27 studies in all. Roughly following the matters are explained more fully.procedure of Armstrong and Lusk (1987), we sent Regarding Table 1, the studies have been classi-out information to the authors of these papers. We fied according to their aims and objectives as ‘Appli-identified the current addresses of the first-named cation’, ‘Process’ or ‘Technique-comparison’ type.authors of 25 studies by using the ISI Social Citation Application studies use Delphi in order to gaugeIndex database. We produced five prototype tables expert opinion on a particular topic, but considersummarising the methods and findings of these issues on the process or quality of the technique as aevaluative papers (discussed shortly), which we secondary concern. Process studies focus on aspectsasked the authors to consider and comment upon, of the internal features of Delphi, such as the role ofparticularly with regard to our coding and interpreta- feedback, the impact of the size of Delphi groups,tion of each author’s own paper. We also asked the and so on. Technique-comparison studies evaluate

G.

Row

e,G

.W

right/

InternationalJournal

ofF

orecasting15

(1999)353

–375357

Table 1aSummary of the methodological features of Delphi in experimental studies

Study Study Delphi Rounds Nature of Delphi Nature of Task Incentives

type group size feedback subjects offered?

Dalkey and Helmer (1963) Application 7 5 Individual estimates Professionals: e.g., economists, Hypothetical event: number of No

(process) (bombing schedules) systems analysts, electronic bombs to reduce munitions

engineer output by stated amount

Dalkey, Brown and Cochran (1970) Process 15–20 2 Unclear Students: no expertise on task Almanac questions (20 per No

group, 160 in total)

Jolson and Rossow (1971) Process 11 and 14 3 Medians (normalised Professionals: computing corporation Forecast (demand for classes: No

probability medians) staff, and naval personnel one question)

Almanac (two questions)

Gustafson, Shukla, Delbecq and Walster (1973) Technique 4 2 Individual estimates Students: no expertise on task Almanac (eight questions requiring No

comparison (likelihood ratios) probability estimates in the

form of likelihood ratios)

Best (1974) Process 14 2 Medians, range of estimates, Professionals: faculty members Almanac (two questions requiring No

distributions of expertise of college numerical estimates of known

ratings, and, for one group, quantity), and Hypothetical event

reasons (one probability estimation)

Van de Ven and Delbecq (1974) Technique 7 2 Pooled ideas of group Students (appropriate expertise), Idea generation (one item: defining No

comparison members Professionals in education job description of student

dormitory counsellors)

Scheibe, Skutsch and Schofer (1975) Process Unspecified 5 Means, frequency Students (uncertain expertise Goals Delphi (evaluating No

(possibly 21) distribution, reasons (from on task) hypothetical transport facility

Ps distant from mean) alternatives via rating goals)

Mulgrave and Ducanis (1975) Process 98 3 Medians, interquartile Students enrolled in Educational Almanac (10 general, and 10 No

range, own responses to Psychology class (most of related to teaching) and Hypo-

previous round whom were school teachers) thetical (18 on what values

in U.S. will be, and then should be)


Tab

le1.

Con

tinue

d

Stud

ySt

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Del

phi

Rou

nds

Nat

ure

ofD

elph

iN

atur

eof

Task

Ince

ntiv

es

type

grou

psi

zefe

edba

cksu

bjec

tsof

fere

d?

Bro

ckho

ff(1

975)

Tech

niqu

e5,

7,9,

115

Med

ians

,rea

sons

(of

Prof

essi

onal

s:ba

nkin

gA

lman

acan

dFo

reca

stin

gY

es

com

paris

on,

thos

ew

ithre

spon

ses

(8–1

0ite

ms

onfin

ance

,ban

king

,

Proc

ess

outs

ide

ofqu

artil

es)

stoc

kqu

otat

ions

,for

eign

trade

,

for

each

type

)

Min

er(1

979)

Tech

niqu

e4

Up

to7

Not

spec

ified

Stud

ents

:fr

omdi

vers

ePr

oble

mSo

lvin

g(ro

le-p

layi

ngN

o

com

paris

onun

derg

rad

popu

latio

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erci

seas

sign

ing

wor

kers

to

suba

ssem

bly

posi

tions

)

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rbau

gh(1

979)

Tech

niqu

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73

Med

ians

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ges

Stud

ents

(app

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iate

expe

rtise

)Fo

reca

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Fisc

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(198

1)Te

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32

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Boj

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dM

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(198

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chni

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3,7,

113

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Alm

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paris

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(198

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Rig

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983)

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niqu

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divi

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expe

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rela

tions

hip

was

repo

rted;

.,g

reat

er/b

ette

rth

an;

5,n

o(s

tatis

tical

lysi

gnifi

cant

)

diff

eren

cebe

twee

n;D

,Del

phi;

R,fi

rst

roun

dav

erag

eof

Del

phi

polls

;S,

stat

iciz

edgr

oup

appr

oach

(ave

rage

ofno

n-in

tera

ctin

gse

tof

indi

vidu

als)

.Whe

nus

ed,t

his

indi

cate

sth

atse

para

test

atic

ized

grou

psw

ere

used

inst

ead

of(o

rin

addi

tion

to)

the

aver

age

ofth

ein

divi

dual

pane

llist

sfr

omth

efir

stro

und

Del

phi

polls

(i.e.

,ins

tead

of/i

nad

ditio

nto

‘R’)

;I,

inte

ract

ing

grou

p;N

GT,

Nom

inal

Gro

upTe

chni

que;

r,‘r

ound

’;P,

‘pan

ellis

t’;N

A,n

otap

plic

able

.


Tab

le2

aR

esul

tsof

the

expe

rim

enta

lD

elph

ist

udie

s

Stud

yIn

depe

nden

tDe

pend

ent

Resu

ltsof

techn

ique

Othe

rres

ults,

Addi

tiona

lcom

men

ts

varia

bles

varia

bles

com

paris

ons

e.g.r

epr

oces

ses

b,c

(and

levels

)(an

dm

easu

res)

Dalk

eyan

dHe

lmer

(196

3)Ro

unds

Conv

erge

nce

(diff

eren

cein

NAIn

crea

sed

conv

erge

nce

(cons

ensu

s)A

com

plex

desig

nwh

ere

quan

titati

vefe

edba

ck

estim

ates

over

roun

ds)

over

roun

ds(N

DA)

from

pane

llists

was

only

supp

lied

inro

und

4,

and

from

only

two

othe

rpan

ellist

s

Dalk

eyet

al.(1

970)

Roun

dsAc

cura

cy(lo

garit

hmof

med

iangr

oup

Accu

racy

:D.

R(N

DA)

High

self-

rated

know

ledge

abili

tywa

sLi

ttle

statis

tical

analy

sisre

porte

d.

estim

atedi

vide

dby

true

answ

er)po

sitiv

elyre

lated

toac

cura

cy(N

DA)

Littl

ede

tailo

nex

perim

ental

meth

od,e

.g.n

ocle

ar

Self-

rated

know

ledge

(1–5

scale

)de

scrip

tion

ofro

und

2pr

oced

ure,

orfe

edba

ck

Jolso

nan

dRo

ssow

(197

1)Ex

perti

se(ex

perts

vs.n

on-e

xper

ts)Ac

cura

cy(n

umer

icale

stim

ates

onth

eAc

cura

cy:D

.R

(expe

rts)(

NDA)

Incr

ease

dco

nsen

sus

over

roun

ds*.

Often

repo

rted

study

.Use

da

small

sam

ple,

Roun

dstw

oalm

anac

ques

tions

only

).Ac

cura

cy:D

,R

(non

-exp

erts)

(NDA

)Cl

aimed

relat

ions

hip

betw

een

high

r1ac

cura

cyso

little

statis

tical

analy

siswa

spo

ssib

le

Cons

ensu

s(d

istrib

utio

nof

Pre

spon

ses)

and

low

varia

nce

over

roun

ds(‘s

igni

fican

t’)

Gusta

fson

etal.

(197

3)Te

chni

ques

(NGT

,I,D

,S)

Accu

racy

(abso

lute

mea

npe

rcen

tage

Accu

racy

:NGT

.I.

S.D

(*fo

rtec

hniq

ues)

NAIn

form

ation

give

nto

allpa

nelli

ststo

cont

rol

Roun

dser

ror).

Accu

racy

:D,

R(N

S)fo

rdiff

eren

ces

inkn

owled

ge.T

his

appr

oach

Cons

ensu

s(v

arian

ceof

estim

ates

Cons

ensu

s:NG

T5D

5I5

Sse

ems

atod

dsto

ratio

nale

ofus

ing

Delp

hiwi

th

acro

ssgr

oups

)he

terog

enou

sgr

oups

Best

(197

4)Fe

edba

ck(st

atisti

cvs

.rea

sons

)Ac

cura

cy(ab

solu

tede

viati

onof

Accu

racy

:D.

R*Hi

ghse

lf-ra

tedex

perti

sepo

sitiv

elyre

lated

Self-

rated

expe

rtise

was

used

asbo

tha

Self-

rated

expe

rtise

(hig

hvs

.low

)as

sess

men

tsfro

mtru

eva

lue).

Accu

racy

:D(1

reas

ons).

D(no

reas

ons)*

toac

cura

cy,a

ndsu

b-gr

oups

ofse

lf-ra

tedde

pend

enta

ndin

depe

nden

tvar

iable

Roun

dsSe

lf-ra

tedex

perti

se(1

–11

scale

)(fo

rone

oftw

oite

ms)

expe

rtsm

ore

accu

rate

than

non-

expe

rts*

Van

deVe

nan

dDe

lbec

q(1

974)

Tech

niqu

es(N

GT,I

,D)

Idea

quan

tity

(num

bero

funi

que

idea

s).Nu

mbe

rofi

deas

:D.

I*;N

GT.

D(N

S)NA

Two

open

-end

edqu

estio

nswe

reals

oas

ked

Satis

facti

on(fi

veite

ms

rated

on1–

5sc

ales).

Satis

facti

on:N

GT.

D*,I

*ab

outl

ikes

and

disli

kes

conc

erni

ngth

e

Effe

ctive

ness

(com

posit

em

easu

reof

idea

Effe

ctive

ness

:NGT

*,D*

.I

proc

edur

es

quan

tity

and

satis

facti

on,e

quall

ywe

ight

ed)

Sche

ibe

etal.

(197

5)Ra

ting

scale

s(ra

nkin

g,ra

ting-

Confi

denc

e(as

sess

edby

seve

nite

mNA

Littl

eev

iden

ceof

corre

latio

nbe

twee

nre

spon

sePo

orde

sign

mea

ntno

thin

gco

uld

beco

nclu

ded

scale

sm

ethod

,and

pair

com

paris

ons)

ques

tionn

aire)

chan

gean

dlo

wco

nfide

nce,

exce

ptin

r2(*

).ab

outc

onsis

tency

ofus

ing

diffe

rent

ratin

gsc

ales.

Roun

dsCh

ange

(five

aspe

cts,e

.g.f

rom

r1to

r2)

False

feed

back

initi

ally

drew

resp

onse

sto

it(N

DA)

Miss

ing

info

rmati

onon

desig

nde

tails

Mul

grav

ean

dDu

cani

s(1

975)

Expe

rtise

(e.g.

,on

item

sab

out

Chan

ge(%

chan

ging

answ

ers)

NAHi

ghdo

gmati

smre

lated

tohi

ghch

ange

over

Abr

iefstu

dy,w

ithlit

tledi

scus

sion

ofth

e

teach

ing

Psco

nsid

ered

expe

rt,Do

gmati

sm(o

nRo

keac

hDo

gmati

smro

unds

*,m

oste

vide

nton

item

son

which

the

unex

pecte

d/co

unter

-intu

itive

resu

lts

onge

nera

litem

sth

eyno

n-ex

pert)

Scale

)m

ostd

ogm

atic

were

relat

ively

inex

pert

Roun

ds


Broc

khof

f(19

75)

Tech

niqu

es(D

,I)

Accu

racy

(abso

lute

erro

r)Ac

cura

cy:D

.I(

alman

acite

ms)

(NDA

)No

clear

resu

ltson

influ

ence

ofgr

oup

size.

Sign

ifica

ntdi

ffere

nces

inac

cura

cyof

grou

ps

Grou

psiz

e(5,

7,9,

11,D

;4,6

,8,1

0,I)

Self-

rated

expe

rtise

(1–5

scale

)Ac

cura

cy:I

.D

(fore

cast

item

s)(N

DA)

Self-

rated

expe

rtise

notr

elated

toac

cura

cyof

diffe

rent

sizes

were

due

todi

ffere

nces

in

Item

type

(fore

casti

ngvs

.alm

anac

)Ac

cura

cy:D

.R

(NS)

initi

alac

cura

cyof

grou

psat

roun

d1

Roun

ds(A

ccur

acy

incr

ease

dto

r3;t

hen

decr

ease

d)

Min

er(1

979)

Tech

niqu

es(N

GT,D

,PCL

)Ac

cura

cy/Q

ualit

y(in

dex

from

0.0

to1.

0)Ac

cura

cy:P

CL.

NGT.

D(N

S)NA

Effe

ctive

ness

was

deter

min

edby

the

prod

uct

Acce

ptan

ce(1

1sta

temen

tq’n

aire)

Acce

ptan

ce:D

5NG

T5PC

Lof

quali

ty(ac

cura

cy)a

ndac

cept

ance

Effe

ctive

ness

(pro

duct

ofot

heri

ndex

es)

Effe

ctive

ness

:PCD

L.D*

,NGT

*

Rohr

baug

h(1

979)

Tech

niqu

es(D

,SJ)

Accu

racy

(corre

latio

nwi

thso

lutio

n)Ac

cura

cy:D

5SJ

Quali

tyof

decis

ions

ofin

divi

duals

incr

ease

don

lyDe

lphi

grou

psin

struc

tedto

redu

ced

exist

ing

Post-

grou

pag

reem

ent(

diffe

renc

ebe

twee

nPo

st-gr

oup

agre

emen

t:SJ

.D

(‘sig

nific

ant’)

sligh

tlyaf

terth

egr

oup

Delp

hipr

oces

sdi

ffere

nces

over

roun

ds.A

gree

men

tcon

cern

s

grou

pan

din

divi

dual

post-

grou

ppo

licy)

Satis

facti

on:S

J.D

(‘sig

nific

ant’)

*de

gree

towh

ichpa

nelli

stsag

reed

with

each

othe

r

Satis

facti

on(0

–10

scale

)af

tergr

oup

proc

ess

had

ende

d(p

ost-t

ask

ratin

g)

Fisc

her(

1981

)Te

chni

ques

(NGT

,D,I

,S)

Accu

racy

(acco

rdin

gto

trunc

ated

Accu

racy

:D5

NGT5

I5S

NA

loga

rithm

icsc

orin

gru

le)(P

roce

dure

sM

ainEf

fect:

P.

0.20

)

Boje

and

Mur

nigh

an(1

982)

Tech

niqu

es(N

GT,D

,Iter

ation

)Ac

cura

cy(d

eviat

ion

ofgp

mea

nfro

mAc

cura

cy:R

.D,

NGT

Nore

latio

nshi

pbe

twee

ngr

oup

size

and

Com

pare

dDe

lphi

toan

NGT

proc

edur

ean

dto

Grou

psiz

e(3

,7,1

1)co

rrect

answ

er)Ac

cura

cy:I

terati

onpr

oced

ure.

Rac

cura

cyor

confi

denc

e.an

itera

tion

(no

feed

back

)pro

cedu

re

Roun

dsCo

nfide

nce

(1–7

scale

)(P

roce

dure

s3Tr

ials

was

signi

fican

t)*Co

nfide

nce

inDe

lphi

incr

ease

dov

erro

unds

*

Satis

facti

on(re

spon

ses

on10

item

q’na

ire)

Spin

elli(

1983

)Ro

unds

Conv

erge

nce

(e.g.

,cha

nge

inNA

Noco

nver

genc

eov

erro

unds

Noqu

oted

statis

tical

analy

sis.

inter

quar

tile

rang

e)In

r3an

dr4

,Ps

enco

urag

edto

conv

erge

towa

rds

majo

rity

opin

ion!

´La

rrech

ean

dM

oinp

our(

1983

)Te

chni

ques

(D,I

)Ac

cura

cy(M

ean

Abso

lute

Perc

entag

eEr

ror)

Accu

racy

:D.

R*Ex

perti

seas

sess

edby

self-

ratin

gha

dno

signi

fican

tA

mea

sure

ofco

nfide

ncew

astak

enas

syno

nym

ous

Roun

dsEx

perti

se(v

ia(a)

Confi

denc

ein

estim

ates,

Accu

racy

:D.

I*va

lidity

,but

did

when

asse

ssed

byan

with

expe

rtise

.Evi

denc

eth

atco

mpo

sing

(b)e

xter

nalm

easu

re)Ac

cura

cy:R

5I

exter

nalm

easu

re.*

Aggr

egate

oflat

ter‘e

xper

ts’De

lphi

grou

psof

the

best

(exter

nally

-rated

)

incr

ease

dac

cura

cyov

erot

herD

elphi

grou

ps*

expe

rtsm

ayim

prov

eju

dgem

ent

Rigg

s(1

983)

Tech

niqu

es(D

,I)

Accu

racy

(abso

lute

diffe

renc

ebe

twee

nAc

cura

cy:D

.I*

Mor

eac

cura

tepr

edict

ions

were

prov

ided

fort

heCo

mpa

rison

with

first

roun

dno

trep

orted

.

Info

rmati

onon

task

(hig

hvs

.low

)pr

edict

edan

dac

tual

poin

tspr

eads

)hi

ghin

form

ation

gam

e.*De

lphi

was

mor

eSt

anda

rdin

form

ation

onth

efo

urtea

ms

inth

e

accu

rate

inbo

thhi

ghan

dlo

win

form

ation

case

stw

oga

mes

was

prov

ided

´Pa

rent

e,An

derso

n,Fe

edba

ck(y

esvs

.no)

Accu

racy

(IFan

even

twou

ldoc

cur;

Accu

racy

:D.

R(W

HEN

even

tocc

urs)

Deco

mpo

sitio

nof

Delp

hise

emed

tosh

owTh

ree

relat

edstu

dies

repo

rted:

data

here

onex

3.

Mye

rsan

dO’

Brien

(198

4)Ite

ratio

n(y

esvs

.no)

and

erro

rin

days

reW

HEN

anev

ent

Accu

racy

:D5

R(IF

even

tocc

urs)

impr

ovem

enti

nac

cura

cyre

lated

toth

eite

ratio

nSu

gges

tion

that

feed

back

supe

rfluo

usin

Delp

hi,

woul

doc

cur)

com

pone

nt,n

otfe

edba

ck(W

HEN

item)

howe

ver,

feed

back

used

here

was

supe

rficia

l

Erffm

eyer

and

Lane

(198

4)Te

chni

ques

(NGT

,D,I

,Gro

upQu

ality

(com

paris

onof

rank

ings

to‘c

orre

ctQu

ality

:D.

NGT*

,I*,

Guid

edgp

*NA

Acce

ptan

cebe

ars

simila

rity

toth

epo

st-tas

k

proc

edur

ewi

thgu

ideli

nes

rank

s’as

signe

dby

NASA

expe

rts)

Quali

ty:D

.R*

,also

note:

I.NG

T*co

nsen

sus

(‘agr

eem

ent’)

mea

sure

of

onap

prop

riate

beha

vior

)Ac

cept

ance

(deg

ree

ofag

reem

entb

etwee

nAc

cept

ance

:Gui

ded

gppr

oced

ure.

D*Ro

hrba

ugh

(197

9)

Roun

dsan

indi

vidu

al’sr

anki

ngan

dfin

algr

pra

nkin

g)


Tab

le2.

Con

tinue

d

Stud

yIn

depe

nden

tDe

pend

ent

Resu

ltsof

techn

ique

Othe

rres

ults,

Addi

tiona

lcom

men

ts

varia

bles

varia

bles

com

paris

ons

e.g.r

epr

oces

ses

b,c

(and

levels

)(an

dm

easu

res)

Erffm

eyer

etal.

(198

6)Ro

unds

Quali

ty(co

mpa

rison

ofra

nkin

gsto

‘cor

rect

Quali

ty:D

.R*

Quali

tyin

crea

sed

upto

the

four

thro

und,

Isth

isan

analy

sisof

data

from

the

study

of

rank

s’as

signe

dby

NASA

expe

rts)

butn

otth

erea

fter:

‘stab

ility

’was

achi

eved

Erffm

eyer

and

Lane

(198

4)?

Dietz

(198

7)W

eight

ing

(usin

gco

nfide

nce

vs.n

o)Ac

cura

cy(d

iffer

ence

betw

een

fore

cast

Accu

racy

D.

R(N

S)W

eight

edfo

reca

stsles

sac

cura

teth

anno

n-Ve

rysm

allstu

dywi

thon

lyon

egr

oup

ofeig

ht

Sum

mar

ym

easu

re(m

edian

,mea

n,va

lue

and

actu

alpe

rcen

tage)

weig

hted

ones

,tho

ugh

diffe

renc

esm

all.

pane

llists

,and

henc

eit

isno

tsur

prisi

ngth

at

Ham

pel,

biwe

ight

,trim

med

mea

n)Co

nfide

nce

(1–5

scale

)Di

ffere

nces

insu

mm

ary

meth

ods

insig

nific

ant.

statis

ticall

ysig

nific

antr

esul

tswe

reno

tach

ieved

Roun

dsLe

astc

onfid

entn

otm

ostl

ikely

toch

ange

opin

ions

Sniez

ek(1

989)

Tech

niqu

es(D

,I,D

ictato

r,Di

alecti

c)Ac

cura

cy(ab

solu

tepe

rcen

tage

erro

r)Ac

cura

cy:D

ictato

r,D

.I(

NDA)

High

confi

denc

ean

dac

cura

cywe

reco

rrelat

edin

Influ

ence

mea

sure

conc

erne

dex

tentt

owh

ichan

(repe

ated-

mea

sure

sde

sign)

Confi

denc

e(1

–7sc

ale)

Accu

racy

:D.

R(N

S)De

lphi

*.In

fluen

cein

Delp

hiwa

sco

rrelat

edin

divi

dual’

ses

timate

sdr

ewth

egr

oup

judg

men

t.

Roun

dsIn

fluen

ce(d

iffer

ence

betw

een

indi

vidu

al’s

with

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Delphi in comparison to external benchmarks, that is, trend of reduced variance is so typical that thewith respect to other techniques or means of ag- phenomenon of increased ‘consensus’, per se, nogregating judgment (for example, interacting longer appears to be an issue of experimentalgroups). interest.

In Table 2, the main findings have been coded Where some controversy does exist, however, is inaccording to how they were presented by their whether a reduction in variance over rounds reflectsauthors. In some cases, claims have been made that true consensus (reasoned acceptance of a position).an effect or relationship was found even though there Delphi has, after all, been advocated as a method ofwas no backing statistical analysis, or though a reducing group pressures to conform (e.g., Martino,statistical test was conducted but standard signifi- 1983), and both increased consensus and increasedcance levels were not reached (because of, for conformity will be manifest as a convergence ofexample, small sample sizes, e.g. Jolson & Rossow, panellists’ estimates over rounds (i.e., these factors1971). It has been argued that there are problems in are confounded). It would seem in the literature thatusing and interpreting ‘P’ figures in experiments and reduced variance has been interpreted according tothat effect sizes may be more useful statistics, the position on Delphi held by the particular author /particularly when comparing the results of indepen- s, with proponents of Delphi arguing that resultsdent studies (e.g., Rosenthal, 1978; Cohen, 1994). In demonstrate consensus, while critics have arguedmany Delphi studies, however, effect sizes are not that the ‘consensus’ is often only ‘apparent’, and thatreported in detail. Thus, Table 2 has been annotated the convergence of responses is mainly attributableto indicate whether claimed results were significant to other social-psychological factors leading to con-at the P 5 0.05 level (*); whether statistical tests formity (e.g., Sackman, 1975; Bardecki, 1984;were conducted but proved non-significant (NS); or Stewart, 1987). Clearly, if panellists are being drawnwhether there was no direct statistical analysis of the towards a central value for reasons other than aresult (NDA). Readers are invited to read whatever genuine acceptance of the rationale behind thatinterpretation they wish into claims of the statistical position, then inefficient process-loss factors are stillsignificance of findings. present in the technique.

Alternative measures of consensus have beentaken, such as ‘post-group consensus’. This concerns

5. Findings the extent to which individuals – after the Delphiprocess has been completed – individually agree

In this section, we consider the results obtained by with the final group aggregate, their own final roundthe evaluative studies as summarised in Table 2, to estimates, or the estimates of other panellists. Rohr-which the reader is referred. We will return to the baugh (1979), for example, compared individuals’details in Table 1 in our subsequent critique. post-group responses to their aggregate group re-

sponses, and seemed to show that reduction in5.1. Consensus ‘disagreement’ in Delphi groups was significantly

less than the reduction achieved with an alternativeOne of the aims of using Delphi is to achieve technique (Social Judgment Analysis). Furthermore,

greater consensus amongst panellists. Empirically, he found that there was little increase in agreementconsensus has been determined by measuring the in the Delphi groups. This latter finding seems tovariance in responses of Delphi panellists over suggest that panellists were simply altering theirrounds, with a reduction in variance being taken to estimates in order to conform to the group withoutindicate that greater consensus has been achieved. actually changing their opinions (i.e., implying con-Results from empirical studies seem to suggest that formity rather than genuine consensus).variance reduction is typical, although claims tend to Erffmeyer and Lane (1984) correlated post-groupbe simply reported unanalysed (e.g., Dalkey & individual responses to group scores and found thereHelmer, 1963), rather than supported by analysis to be significantly more ‘acceptance’ (i.e., signifi-(though see Jolson & Rossow, 1971). Indeed, the cantly higher correlations between these measures) in


an alternative structured group technique than in a ing a final round Delphi aggregate to that of the firstDelphi procedure, although there were no differences round is thus, effectively, a within-subjects com-in acceptance between the Delphi groups and a parison of techniques (Delphi versus staticizedvariety of other group techniques (see Table 2). group); when comparison occurs between Delphi andUnfortunately, no analysis was reported on the a separate staticized group then it is a between-difference between the correlations of the post-group subjects one. Clearly, the former comparison isindividual responses and the first and final round preferable, given that it controls for the highlygroup aggregate responses. variable influence of subjects. Although the com-

An alternative slant on this issue has been pro- parison of round averages should be possible invided by Bardecki (1984), who reported that – in a every study considering Delphi accuracy/quality, astudy not fully described – respondents with more number of evaluative studies have omitted to reportextreme views were more likely to drop out of a round differences (e.g., Fischer, 1981; Riggs, 1983).Delphi procedure than those with more moderate Comparisons of relative accuracy of Delphi panelsviews (i.e., nearer to the group average). This with first round aggregates and staticized groups aresuggests that consensus may be due – at least in part reported in Table 3.– to attrition. Further empirical work is needed to Evidence for Delphi effectiveness is equivocal, butdetermine the extent to which the convergence of results generally support its advantage over firstthose who do not (or cannot) drop out of a Delphi round/staticized group aggregates by a tally of 12procedure are due to either true consensus or to studies to two. Five studies have reported significantconformity pressures. increases in accuracy over Delphi rounds (Best,

´1974; Larreche & Moinpour, 1983; Erffmeyer &Lane, 1984; Erffmeyer et al., 1986; Rowe & Wright,

5.2. Increased accuracy1996), although the two papers of Erffmeyer et al.may be reports of separate analyses on the same data

Of main concern to the majority of researchers is(this is not clear). Seven more studies have produced

the ability of Delphi to lead to judgments that arequalified support for Delphi: in five cases, Delphi is

more accurate than (a) initial, pre-procedure aggre-found to be better than statistical or first round

gates (equivalent to equal-weighted staticizedaggregates more often than not, or to a degree that

groups), and (b) judgments derived from alternativedoes not reach statistical significance (e.g., Dalkey et

group procedures. In order to ensure that accuracyal., 1970; Brockhoff, 1975; Rohrbaugh, 1979; Dietz,

can be rapidly assessed, problems used in Delphi1987; Sniezek, 1989), and in two others it is shown

studies have tended to involve either short-rangeto be better under certain conditions and not others

forecasting tasks, or tasks requiring the estimation of´(i.e., in Parente et al., 1984, Delphi accuracy in-

almanac items whose quantitative values are alreadycreases over rounds for predicting ‘when’ an event

known to the experimenters and about which sub-might occur, but not ‘if’ it will occur; in Jolson &

jects are presumed capable of making educatedRossow, 1971, it increases for panels comprising

guesses. In evaluative studies, the long-range fore-‘experts’, but not for ‘non-experts’).

casting and policy formation items (etc.) that areIn contrast, two studies found no substantial

typical in Delphi applications are rarely used.difference in accuracy between Delphi and staticized

Table 2 reports the results of the evaluation ofgroups (Fischer, 1981; Sniezek, 1990), while two

Delphi with regards to the various benchmarks,others suggested Delphi accuracy was worse. Gustaf-

while Tables 3–5 collate and summarise the com-son et al. (1973) found that Delphi groups were less

parisons according to specific benchmarks.accurate than both their first round aggregates (forseven out of eight items) and than independent

5.2.1. Delphi versus staticized groups staticized groups (for six out of eight items), whileThe average estimate of Delphi panellists on the Boje and Murnighan (1982) found that Delphi panels

first round – prior to iteration or feedback – is became less accurate over rounds for three out ofequivalent to that from a staticized group. Compar- four items.


Table 3aComparisons of Delphi to staticized (round 1) groups

Study Criteria Trend of relationship Additional comments(moderating variable)

Dalkey et al. (1970) Accuracy D.R (NDA) 81 groups became moreaccurate, 61 became less

Jolson and Rossow (1971) Accuracy D.R (experts) (NDA) For both items in each caseAccuracy D,R (‘non experts’) (NDA)

Gustafson et al. (1973) Accuracy D,S (NDA) D worse than S on six of eightD,R (NDA) items, and than R on seven of

eight items

Best (1974) Accuracy D.R* For each of two items

Brockhoff (1975) Accuracy D.R (almanac items) Accuracy generally increasedD.R (forecast items) to r3, then started to decrease

Rohrbaugh (1979) Accuracy D.R (NDA) No direct comparison made, buttrend implied in results

Fischer (1981) Accuracy D5S Mean group scores werevirtually indistinguishable

Boje and Murnighan (1982) Accuracy R.D* Accuracy in D decreased overrounds for three out of four items

´Larreche and Moinpour (1983) Accuracy D.R*

´Parente et al. (1984) Accuracy D.R (WHEN items) (NDA) The findings noted here are theAccuracy D5R (IF items) (NDA) trends as noted in the paper

Erffmeyer and Lane (1984) Quality D.R* Of four procedures, D seemedto improve most over rounds

Erffmeyer et al. (1986) Quality D.R* Most improvement in earlyrounds

Dietz (1987) Accuracy D.R Error of D panels decreasedfrom r1 to r2 to r3

Sniezek (1989) Accuracy D.R Small improvement over roundsbut not significant

Sniezek (1990) Accuracy S.D (one of five items) No reported comparison ofaccuracy change over D rounds

Rowe and Wright (1996) Accuracy D (reasons f’back).R*Accuracy D (stats f’back).R*

a See Table 1 for explanation of abbreviations.

5.2.2. Delphi versus interacting groups interacting groups have been compared are presentedAnother important comparative benchmark for in Table 4.

Delphi performance is provided by interacting Research supports the relative efficacy of Delphigroups. Indeed, aspects of the design of Delphi are over interacting groups by a score of five studies tointended to pre-empt the kinds of social /psychologi- one with two ties, and with one study showingcal /political difficulties that have been found to task-specific support for both techniques. Support forhinder effective communication and behaviour in Delphi comes from Van de Ven and Delbecq (1974),

´groups. The results of studies in which Delphi and Riggs (1983), Larreche and Moinpour (1983),


Table 4aComparisons of Delphi to interacting groups


Gustafson et al. (1973) Accuracy I.D (NDA) D worse than I on five ofeight items

Van de Ven and Delbecq (1974) Number of ideas D.I*

Brockhoff (1975) Accuracy D.I (almanac items) (NDA) Comparisons were between II.D (forecast items) (NDA) and r3 of D

Fischer (1981) Accuracy D5I Mean group scores wereindistinguishable

´Larreche and Moinpour (1983) Accuracy D.I*

Riggs (1983) Accuracy D.I* Result was significant for bothhigh and low information tasks

Erffmeyer and Lane (1984) Quality D.I*

Sniezek (1989) Accuracy D.I (NDA) Small sample sizes

Sniezek (1990) Accuracy D5I No difference at P 5 0.10 levelon comparisons on the five items


Erffmeyer and Lane (1984), and Sniezek (1989). needs to be done quickly, while Delphi would be aptFischer (1981) and Sniezek (1990) found no dis- when experts cannot meet physically; but whichtinguishable differences in accuracy between the two technique is preferable when both are options?approaches, while Gustafson et al. (1973) found a Results of Delphi–NGT comparisons do not fullysmall advantage for interacting groups. Brockhoff answer this question. Although there is some evi-(1975) seemed to show that the nature of the task is dence that NGT groups make more accurate judg-important, with Delphi being more accurate than ments than Delphi groups (Gustafson et al., 1973;interacting groups for almanac items, but the reverse Van de Ven & Delbecq, 1974), other studies havebeing the case for forecasting items. found no notable differences in accuracy/quality

between them (Miner, 1979; Fischer, 1981; Boje &5.2.3. Delphi versus other procedures Murnighan, 1982), while one study has shown

Although evidence suggests that Delphi does Delphi superiority (Erffmeyer & Lane, 1984).generally lead to improved judgments over staticized Other studies have compared Delphi to: groups ingroups and unstructured interacting groups, it is which members were required to argue both for andclearly of interest to see how Delphi performs in against their individual judgments (the ‘Dialectic’comparison to groups using other structured pro- procedure – Sniezek, 1989); groups whose judg-cedures. Table 5 presents the findings of studies ments were derived from a single, group-selectedwhich have attempted such comparisons. individual (the ‘Dictator’ or ‘Best Member’ strategy

A number of studies have compared Delphi to the – Sniezek, 1989, 1990); groups that received rulesNominal Group Technique or NGT (also known as on interaction (Erffmeyer & Lane, 1984); groupsthe ‘estimate-talk-estimate’ procedure). NGT uses whose information exchange was structured accord-the basic Delphi structure, but uses it in face-to-face ing to Social Judgment Analysis (Rohrbaugh, 1979);meetings that allow discussion between rounds. and groups following a Problem Centred LeadershipClearly, there are practical situations where one (PCL) approach (Miner, 1979). The only studies thattechnique may be viable and not the other, for found any substantial differences between Delphiexample NGT would seem appropriate when a job and the comparison procedure /s are those of


Table 5aComparisons of Delphi to other structured group procedures


Gustafson et al. (1973) Accuracy NGT.D* NGT-like technique was more accuratethan D on each of eight items

Van de Ven and Delbecq (1974) [ of ideas NGT.D NGT gps generated, on average,12% more unique ideas than D gps

Miner (1979) Quality PCL.NGT.D PCL was more effective than D(P , 0.01) (see Table 2)

Rohrbaugh (1979) Accuracy D5SJ No P statistic reported due tonature of study/analysis

Fischer (1981) Accuracy D5NGT Mean group scores were similar,but NGT very slightly better than D

Boje and Murnighan (1982) Accuracy D5NGT On the four items, D was slightly moreaccurate than NGT gps on final r

Erffmeyer and Lane (1984) Quality D.NGT* Guided gps followed guidelinesD.Guided Group* on resolving conflict

Sniezek (1989) Accuracy Dictator5D5Dialectic Dialectic gps argued for and against(NDA) positions. Dictator gps chose one

member to make gp decision

Sniezek (1990) Accuracy D.BM (one BM5Dictator (above): gp choosesof five items) one member to make decision


Erffmeyer and Lane (1984), which found Delphi to poor backgrounds in the social sciences and lackedbe better than groups that were given instructions on acquaintance with appropriate research methodolo-resolving conflict, and Miner (1979), which found gies (e.g., Sackman, 1975).that the PCL approach (which involves instructing Over the past few decades, empirical evaluationsgroup leaders in appropriate group-directing skills) to of the Delphi technique have taken on a morebe significantly more ‘effective’ than Delphi. systematic and scientific nature, typified by the

controlled comparison of Delphi-like procedureswith other group and individual methods for obtain-

6. A critique of technique-comparison studies ing judgments (i.e., technique comparison). Althoughthe methodology of these studies has provoked a

Much of the criticism of early Delphi studies degree of support (e.g., Stewart, 1987), we havecentred on their ‘sloppy execution’ (e.g., Stewart, queried the relevance of the majority of this research1987). Among specific criticisms were claims that to the general question of Delphi efficacy (e.g., RoweDelphi questionnaires were poorly worded and am- et al., 1991), pointing out that most of such studiesbiguous (e.g., Hill & Fowles, 1975) and that the have used versions of Delphi somewhat removedanalysis of responses was often superficial (Linstone, from the ‘classical’ archetype of the technique1975). Reasons given for the poor conduct of early (consider Table 1).studies ranged from the technique’s ‘apparent sim- To begin with, the majority of studies have usedplicity’ encouraging people without the requisite structured first rounds in which event statements –skills to use it (Linstone & Turoff, 1975), to devised by experimenters – are simply presented tosuggestions that the early Delphi researchers had panellists for assessment, with no opportunity for


them to indicate the issues they believe to be of possess similar knowledge (indeed, certain studiesgreatest importance on the topic (via an unstructured have even tried to standardise knowledge prior to theround), and thus militating against the construction Delphi manipulation; e.g., Riggs, 1983). Indeed, theof coherent task scenarios. The concern of research- few laboratory studies that have used non-studentsers to produce simple experimental designs is com- have tended to use professionals from a singlemendable, but sometimes the consequence is over- domain (e.g., Brockhoff, 1975; Leape et al., 1992;simplification and designs / tasks /measures of uncer- Ono & Wedermeyer, 1994). This point is important:tain relevance. Indeed, because of a desire to verify if varied information is not available to be shared,rapidly the accuracy of judgments, a number of then what could possibly be the benefit of anyDelphi studies have used almanac questions involv- group-like aggregation over and above a statisticaling, for example, estimating the diameter of the aggregation procedure?planet Jupiter (e.g., as in Gustafson et al., 1973; There is some evidence that panels composed ofMulgrave & Ducanis, 1975; Boje & Murnighan, relative experts tend to benefit from a Delphi pro-1982). Unfortunately, it is difficult to imagine how cedure to a greater extent than comparative aggre-Delphi might conceivably benefit a group of un- gates of novices (e.g., Jolson & Rossow, 1971;

´knowledgeable subjects – who are largely guessing Larreche & Moinpour, 1983), suggesting that typicalthe order of magnitude of some quantitatively large laboratory studies may underestimate the value ofand unfamiliar statistic, such as the tonnage of a Delphi. Indeed, the relevance of the expertise ofcertain material shipped from New York in a certain members of a staticized group, and the extent toyear – in achieving a reasoned consideration of which their judgments are shared /correlated, haveothers’ knowledge, and thus of improving the ac- been shown to be important factors related tocuracy of their estimates. However, even when the accuracy in the theoretical model of Hogarth (1978),items are sensible (e.g., of short-term forecasting which has been empirically supported by a numbertype), their pertinence must also depend on the of studies (e.g., Einhorn, Hogarth & Klempner, 1977;relevance of the expertise of the panellists: ‘sensible’ Ashton, 1986).questions are only sensible if they relate to the The absolute and relative expertise of a set ofdomain of knowledge of the specific panellists. That individuals is also liable to interact with the effec-is, student subjects are unlikely to respond to, for tiveness of different group techniques – not onlyexample, a task involving the forecast of economic statistical groups and Delphi, but also interactingvariables, in the same way as economics experts – groups and techniques such as the NGT. Because thenot only because of lesser knowledge on the topic, nature of such relationships are unknown, it is likelybut because of differences in aspects such as their that, for example, though a Delphi-like proceduremotivation (see Bolger & Wright, 1994, for discus- might prove more effective than an NGT approach atsion of such issues). enhancing judgment with a particular set of in-

Delphi, however, was ostensibly designed for use dividuals, a panel possessing different ‘expertise’with experts, particularly in cases where the variety attributes might show the reverse trend. The un-of relevant factors (economic, technical, etc.) ensures comfortable conclusion from this line of argument isthat individual panellists have only limited knowl- that it is difficult to draw grand conclusions on theedge and might benefit from communicating with relative efficacy of Delphi from technique-compari-others possessing different information (e.g., Helmer, son studies that have made no clear attempt at1975). This use of diverse experts is, however, rarely specifying or describing the characteristics of theirfound in laboratory situations: for the sake of panels and the relevant features of the task. Further-simplification, most studies employ homogenous more, any particular demonstration of Delphi effica-samples of undergraduate or graduate students (see cy cannot be taken as an indicator of the moreTable 1), who are required to make judgments about general validity of the technique, since the demon-scenarios in which they can by no means be consid- strated effect will be partly dependent on the specificered expert, and about which they are liable to characteristics of the panel and the task.


A second major difference between laboratory tion and reductionism in order to study highlyDelphis and the Delphi ideal lies in the nature of the complex phenomena seems to be at the root of thefeedback presented to panellists (see Table 1). The problem, such that experimental Delphis have tendedfeedback recommended in the ‘classical’ Delphi to use artificial tasks (that may be easily validated),comprises medians or distributions plus arguments student subjects, and simple feedback in the place offrom panellists whose estimates fall outside the meaningful and coherent tasks, experts /profession-upper and lower quartiles (e.g., Martino, 1983). In als, and complex feedback. But simplification can gothe majority of experimental studies, however, feed- too far, and in the case of much of the Delphiback usually comprises only medians or means (e.g., research it would appear to have done so.Jolson & Rossow, 1971; Riggs, 1983; Sniezek, 1989, In order that research is conducted more fruitfully1990; Hornsby et al., 1994), or a listing of the in the future, two major recommendations wouldindividual panellists’ estimates or response distribu- appear warranted from the above discussion. Thetions (e.g., Dalkey & Helmer, 1963; Gustafson et al., first is that a more precise definition of Delphi is1973; Fischer, 1981; Taylor, Pease & Reid, 1990; needed in order to prevent the technique from beingLeape et al., 1992; Ono & Wedermeyer, 1994), or misrepresented in the laboratory. Issues that par-some combination of these (e.g., Rohrbaugh, 1979). ticularly need clarification include: the type ofAlthough feedback of reasons or rationales behind feedback that constitutes Delphi feedback; theindividuals’ estimates has sometimes taken place criteria that should be met for convergence of

´(e.g., Boje & Murnighan, 1982; Larreche & Moin- opinion to signal the cessation of polling; the selec-pour, 1983; Erffmeyer & Lane, 1984; Rowe & tion procedures that should be used to determineWright, 1996) this form of feedback is rare. This number and type of panellists, and so on. Althoughvariability of feedback, however, must be considered suggestions on these issues do exist in the literature,a crucial issue, since it is through the medium of the fact that they have largely been ignored byfeedback that information is conveyed from one researchers suggests that they have not been ex-panellist to the next, and by limiting feedback one pressed as explicitly or as strongly as they mightmust also limit the scope for improving panellist have been, and that the importance of definitionalaggregate accuracy. The issue of feedback will be precision has been underestimated by all.considered more fully in the next section: suffice it to The second recommendation is that a much greatersay here that, once more, it is apparent that sim- understanding is required of the factors that mightplified laboratory versions of Delphi tend to differ influence Delphi effectiveness, in order to preventsignificantly from the ideal in such a way that they the technique’s potential utility from being under-may limit the effectiveness of the technique. estimated through accurate representations used in

From the discussion so far it has been suggested unsympathetic experimental scenarios. It would seemthat the majority of the recent studies that have likely that such research would also help in clarify-attempted to address Delphi effectiveness have dis- ing precisely what those aspects of Delphi adminis-covered little of general consequence about Delphi. tration are that need more specific definition. ForThat research has yielded so little of substance would example, if ‘number of panellists’ was empiricallysuggest that there are definitional problems with demonstrated to have no influence on the effective-Delphi that militate against standard administrations ness of variations of Delphi, then it would be clearof the procedure (e.g., Hill & Fowles, 1975). Fur- that no particular comment or qualifier would bethermore, the lack of concern of experimenters in required on this topic in the technique definition.following even the fairly loose definitional guidelinesthat do exist suggests that there is a general lack ofappreciation of the importance of factors like the 7. Findings of process studiesnature of feedback in contingently influencing thesuccess of procedures like Delphi. The requirement Technique-comparison studies ask the question:of empirical social science research to use simplifica- ‘does Delphi work?’, and yet they use technique


forms that differ from one study to the next and that 7.1. The role of feedbackoften differ from the ideal of Delphi. Process studiesask: ‘what is it about Delphi that makes it work?’, Feedback is the means by which information isand this involves both asking and answering the passed between panellists so that individual judg-question: ‘what is Delphi?’ ment may be improved and debiasing may occur.

We believe that the emphasis of research should But there are many questions about feedback thatbe shifted from technique-comparison studies to need to be answered. For example, which individualsprocess studies. The latter should focus on the way change their judgments in response to Delphi feed-in which an initial statistical group is transformed by back – the least confident, the most dogmatic, thethe Delphi process into a final round statistical least expert? What is it about feedback that encour-group. To be more precise, the transformation of ages change? Do different types of feedback causestatistical group characteristics must come about different types of people to change? And so on.through changes in the nature of the panellists, which Although studies such as those of Dalkey andare reflected by changes over rounds in their judg- Helmer (1963) and Dalkey et al. (1970) wouldments (and participation), which are manifest as appear to have examined the role of feedback, this ischanges in the individual accuracy of the ‘group’ not the case, since feedback is confounded by themembers, their judgmental intercorrelations, and unknown role of ‘iteration’, and since only singleindeed – when panellists drop out over rounds – feedback formats were used in each study. Whateven their group size (as per Hogarth, 1978). studies like those of Scheibe et al. (1975) do reveal,

One conceptualisation of the problem is to view however, is the powerful influence of feedback: injudgment change over rounds as coming about their case, by demonstrating the pull that even falsethrough the interaction of internal factors related to feedback can have on panellists. Evidence from mostthe individual (such as personality styles and traits), Delphi studies shows that convergence towards theand external factors related to technique design and ‘group’ average is typical (see section on Consen-the general environment (such as the influence of sus).feedback type and the nature of the judgment task). However, more systematic efforts at assessing theFrom this perspective, the role of research should be role of feedback have been attempted by other

´to identify which factors are most important in authors. Parente et al. (1984), in a series of experi-explaining how and why an individual changes his / ments, used student subjects to forecast ‘if’ andher judgment, and which are related to change in the ‘when’ a number of newsworthy events would occur.desired direction (i.e., towards more accurate judg- In their third study they attempted to separate out thement). Only by understanding such relationships will iteration and feedback components by decomposingit be possible to explain the contingent differences in Delphi. They appeared to demonstrate that, althoughjudgment-enhancing utility of the various available neither iterated polling nor consensus feedback hadprocedures which include Delphi. Importantly from any apparent effect upon group ‘if’ accuracy, itera-this perspective – and unlike in technique-compari- tion alone resulted in increased accuracy for ‘when’son studies – analysis should be conducted at the a predicted event would occur – while feedbacklevel of the individual panellist, rather than at the alone did not. Similarly, Boje and Murnighan (1982)level of the nominal group, since the non-interacting found decreased accuracy over rounds for a ‘stan-nature of Delphi ensures that individual responses dard’ Delphi procedure, while a control procedureand changes are central and measurable and (unlike that simply entailed the iteration of the questionnaireinteracting groups) the ultimate group response is (with no feedback) resulted in increased accuracyeffectively ‘related to the sum of the parts’ and is not (perhaps because of the opportunity for individualsholistically ‘greater than’ these (e.g., Rowe et al., to further reflect on the problem). However, as noted1991). The results of those few studies that we earlier, Delphi studies have tended to involve only

´consider to be of the process type are collated in superficial types of feedback. In Parente et al.subsequent sections. (1984), the feedback comprised modes and medians,


while in the study of Boje and Murnighan (1982), as prescribed in the ‘classical’ definition, might leadindividuals’ justifications for their estimates were to improved Delphi performance, this is not to sayused as feedback along with the estimates themselves that ‘proper’ Delphi feedback is liable to be the best(no median or other average statistic was used). type – merely that it is liable to lead to trends in

If different types of feedback differentially injudgment change that will differ from those in manyfluence individuals to change their judgments over evaluative studies of ‘Delphi’. Indeed, given therounds, then comparisons across the various Delphi limited nature of recommended feedback in theversions become difficult. Unfortunately, there are a classic procedure, the question remains as to hownumber of reasons – empirical, intuitive and theoret- effective even that type will be, given that theical – to suggest that such differential effects do majority of individual panellists are allowed so littleexist. In Rowe and Wright (1996) we compared input (e.g., those within the upper and lower quartiles‘iteration’, ‘statistical’ feedback (means and me- are not required to justify their estimates, evendians) and ‘reasons’ feedback (with no averages) and though they might be made for different – and evenfound that the greatest degree of improvement in mutually incompatible – reasons).accuracy over rounds occurred in the ‘reasons’condition. Furthermore, we found that, although 7.2. The nature of panellistssubjects were less inclined to change their forecastswhen receiving ‘reasons’ feedback than the other A number of studies have considered the role oftypes, when they did change their forecasts they Delphi panellists and how their attributes relate totended to become more accurate – which was not the criteria such as the effectiveness (e.g., accuracy) ofcase in the ‘iteration’ and ‘statistical’ conditions. the procedure. One of the main attributes of panel-

That feedback of a more profound nature can lists is their ‘expertise’ or ‘knowledgeability’. Asimprove the performance of Delphi groups has also discussed earlier, Delphi is intended for use bybeen shown by Best (1974). He found that, for one disparate experts, and yet most empirical studiesof two task items, a Delphi group that was given have used inexpert (often student) panels. Intuitively,feedback of reasons in addition to a median and the use of experts makes sense, but what doesrange of estimates was significantly more accurate research show? A number of ‘process’ studies havethan a Delphi group that was simply provided with considered self-rated expertise, essentially to deter-the latter information. Gowan and McNichols (1993) mine whether self-ratings might be useful for select-considered the relative influences of three types of ing panels. Perhaps unsurprisingly – given theDelphi feedback: statistical, regression model, and number of ways in which self-ratings may be taken –if-then rules. They could not measure the accuracy of results have been equivocal, with a number ofjudgments (the task involved considering the econ- studies suggesting that self-assessment is a validomic viability of companies on the basis of financial procedure (e.g., Dalkey et al., 1970; Best, 1974;ratios), but they did find that (if-then) rule feedback Rowe & Wright, 1996), and others suggesting that it

´induced a significantly greater degree of ‘consensus’ is not (Brockhoff, 1975; Larreche & Moinpour,than the other types. 1983). But these results say more about the utility of

That different feedback types are differentially a particular expertise measure than the role ofrelated to factors such as accuracy, change, and experts in Delphi.consensus should be of no surprise. Indeed, in the Jolson and Rossow (1971), however, found thatfield of social psychology there has been much accuracy increased over rounds for expert groups butresearch on judgment, conformity, and opinion not for inexpert ones (though they used only twochange in interacting groups, and how these relate to groups making judgments on only two problems).the type of information exchanged (e.g., see Deutsch Similarly, Riggs (1983) found that panels were more& Gerard, 1955; Myers, 1978; Isenberg, 1986), but accurate in predicting the result of a college footballsuch concerns seem not to have infiltrated the Delphi game on which they had more information (i.e., weredomain. Although the use of ‘reasons’ in feedback, more ‘expert’) than one on which they had less


(although a more interesting comparison might have of quality is generally inappropriate (Armstrong,been of the relative improvement in the two cases). 1985, reviews studies on ‘confidence’ more broadly).Rowe and Wright (1996) found that the most accur- A more interesting conceptualisation of confidence isate Delphi panellists on first rounds changed their as a potential predictor of panellists’ propensity toestimates less over rounds than those who were change their estimates in the face of feedback.initially less accurate (and hence who were, arguab- Scheibe et al. (1975) found a positive relationshiply, less ‘expert’). Importantly, this result appears to between these factors (confidence and change), butsupport the Theory of Errors (see, for example, Rowe and Wright (1996) found no evidence for this.

´ ´Parente & Anderson-Parente, 1987), in which ac- We therefore have no consistent evidence that initialcuracy is improved over rounds as a consequence of confidence explains judgment change over Delphithe panel experts ‘holding-out’, while the less-expert rounds.panellists ‘swing’ towards the group average. The Two studies have considered the impacts of autility of expertise has been reviewed elsewhere, number of personality factors on the Delphi process.with evidence suggesting that there is an interaction Taylor et al. (1990) found no relationship betweenbetween expertise and the nature of the task, so that four demographic factors (e.g., gender and education)expertise is only helpful up to a certain level for and the ‘effectiveness’ of Delphi, or whether panel-forecasting tasks, but of greater importance for lists dropped out. Mulgrave and Ducanis (1975)estimation tasks (e.g., Welty, 1974; Armstrong, considered panellist dogmatism, finding that the most1985). More controlled experiments are required to dogmatic panellists changed judgments the most overexamine how expertise interacts with aspects of the rounds – although the authors had no explanation forDelphi technique, and how it relates to accuracy this rather counter-intuitive result and reported noimprovement over rounds. statistical analysis.

Panellist confidence has been studied from a The impact of the number of panellists has beennumber of perspectives. One conceptualisation of considered by Brockhoff (1975) (who used groups ofconfidence is as an outcome measure. For example, five, seven, nine, and 11) and Boje and MurnighanSniezek (1992) has pointed out that panel confidence (1982) (using groups of three, seven, and 11).may be the only available measure of the quality of a Neither of these studies found a consistent relation-decision (e.g., since one cannot determine the accura- ship between panel size and effectiveness criteria.cy of forecasts a priori), and from this sense it isimportant that ‘confidence’ in some way correlates toother quality measures. Although Rowe and Wright 8. Conclusion(1996) found that both confidence and accuracyincreased over rounds, they found no clear relation- This paper reviews research conducted on theship between the accuracy and confidence of the Delphi technique. In general, accuracy tends toindividual panellists. Conversely, Boje and Mur- increase over Delphi rounds, and hence tends to benighan (1982) found that while confidence increased greater than in comparative staticized groups, whileover rounds, accuracy decreased. Sniezek has also Delphi panels also tend to be more accurate thancompared panellist confidence to accuracy with unstructured interacting groups. The technique hascontradictory results (evidence for a positive rela- shown no clear advantages over other structuredtionship in Sniezek, 1989; but no evidence for such a procedures.relationship in Sniezek, 1990). Dietz (1987) attempt- Various difficulties exist in research of this tech-ed to weight panellist estimates according to how nique-comparison type, however. Our main concernconfident they were, but found that such a weighting is with the sheer variety of technique formats thatprocess gave less accurate results than a standard have been used as representative of Delphi, varyingequal-weighting one. from the technique ‘ideal’ (and from each other) on

From these inconsistent results in Delphi studies, aspects such as the type of feedback used and thewe conclude that the use of confidence as a measure nature of the panellists. If one uses a technique


Brockhoff, K. (1975). The performance of forecasting groups informat that varies from the ‘ideal’ on a factor that iscomputer dialogue and face to face discussions. In: Linstone,shown to influence the performance of the technique,H., & Turoff, M. (Eds.), The Delphi method: techniques and

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Dagenais, F. (1978). The reliability and convergence of the Delphiaccuracy/quality than might be expected to arisetechnique. The Journal of General Psychology 98, 307–308.

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Biographies: Gene ROWE is an experimental psychologist who George WRIGHT is a psychologist with an interest in thegained his PhD from the Bristol Business School at the University judgmental aspects of forecasting and decision making. He isof the West of England (UWE). After some years at UWE, then at Editor of the Journal of Behavioral Decision Making and anthe University of Surrey, he is now at The Institute of Food Associate Editor of the International Journal of Forecasting andResearch (IFR), Norwich. His research interests have ranged from the Journal of Forecasting. He has published in such journals asexpert systems and group decision support, to judgment and Management Science, Current Anthropology, Journal of Directdecision making more generally. Lately, he has been involved in Marketing, Memory and Cognition, and the International Journalresearch on risk perception and public participation mechanisms in of Information Management.risk assessment and management.

delphi technique rowe wright

Technology

delphi technique

delphi groups

potential of delphi

perspective of delphi

delphi effectiveness

technique characteristics

original concept of

statistical groups