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South African Journal of Industrial Engineering December 2018 Vol 29(4), pp 1-16



W. Niemann1*, T. Kotzé1 & D. Jacobs1


Article details
Submitted by authors 14 Mar 2017
Accepted for publication 17 Sep 2018
Available online 10 Dec 2018

Contact details
* Corresponding author
[email protected]

Author affiliations
1 Department of Business

Management, University of
Pretoria, South Africa



The purpose of this study was to investigate the key factors that

affect the implementation of collaborative planning, forecasting,

and replenishment (CPFR). A single case study method was adopted,

examining a critical case in the South African grocery retail sector.

Semi-structured interviews were conducted to collect data. The

study confirmed five of the six key factors affecting CPFR

implementation that have been identified in the literature. Two

new key factors, business understanding and a common goal, were

identified. The study also determined the framework that the focal

firm used to implement CPFR. The findings aid supply chain

managers in understanding and leveraging the key factors that

affect the successful implementation of CPFR. The framework can

be used for benchmarking and guiding managers through the process

of implementing CPFR.


Die doel van hierdie studie was om die belangrike faktore wat die
implementering van gesamentlike beplanning, vooruitskatting, en

aanvulling (GBVA) beïnvloed te ondersoek. ‘n Enkele gevallestudie
metode was gebruik om ‘n kritieke geval binne die Suid-Afrikaanse
kruideniersware kleinhandelsektor te ondersoek. Semi-
gestruktureerde onderhoude was uitgevoer om data in te samel. Die
studie het vyf van die ses belangrikste faktore bevestig wat GBVA
implementering beïnvloed, soos wat vervat is in die literatuur.
Twee nuwe sleutel faktore, besigheidsbegrip en ‘n gemeenskaplike
doel, was geïdentifiseer. Die studie het ook die raamwerk bepaal
wat die firma gebruik het om GBVA te implementeer. Die studie
bemagtig voorsieningskettingbestuurders om die belangrikste
faktore wat die suksesvolle implementering van GBVA beïnvloed te
verstaan en te benut. Die raamwerk kan help om ‘n normtoets te
stel en bestuurders te lei deur die proses van die GBVA


The benefits of collaborative planning, forecasting, and replenishment (CPFR) for grocery retailers
have been described as ‘ground breaking’; but what good are such cost-saving, lead time-reducing
and sales-increasing concepts if they cannot be implemented successfully [1-4]? CPFR is described
as “collaboration where two or more parties in the supply chain jointly plan a number of promotional
activities and work out synchronised forecasts, on the basis of which production and replenishment
are determined” [5, 6].

Several studies have demonstrated the improvements in supply chain performance due to CFPR [3,
7-9]. Despite the convincing results of CPFR, its implementation rate is far lower than anticipated
[10, 11]. It is widely accepted that collaboration in any industry is potentially a way of attaining a
competitive advantage [12, 13]. More recently, the term ‘collaborative advantage’ has been used


to describe the result of a competitive advantage directly attributable to collaboration among
partnering entities in an industry [14]. One possible way to overcome the challenges of overstocking,
understocking, missed sales, and expired stock that grocery retailers face is to integrate their supply
chain with that of their suppliers. The widely known and much-suggested framework to
accommodate this idea is known as collaborative planning, forecasting, and replenishment [15].

CPFR was originally coined by an international organisation, Voluntary Inter-Industry Commerce
Standards (VICS), when it was registered as a trademark in 1998 [16]. The purpose of CPFR was to
reduce inventory levels and improve customer service. In 1998, Wal-Mart and Warner-Lambert
pioneered the introduction of CPFR, and focused on Listerine products, resulting in a drastic
reduction of inventory levels and increased sales [15]. That was the starting point for Wal-Mart to
undertake this initiative with several key suppliers. Wal-Mart is currently the largest retailer in the
United States [17]. Despite the highly-accredited and beneficial framework of CPFR set out by VICS,
its full benefits are often not realised due to its complex nature [10, 13, 18]. Only a few partnering
firms, such as Wal-Mart and Warner-Lambert, have been able to reap the full benefits of CPFR [11].
Greater attention should, therefore, be given to the collaborative initiative of CPFR.

One of the key explanations for the failure to implement CPFR successfully is the lack of detailed
and comprehensive guidelines about the key factors and the implementation framework [19]. In the
global context, few studies have explored the issue of the key factors affecting CPFR implementation
[20, 21]. In the South African context, few studies on CPFR implementation exist, which leaves a
lack of consensus about its key factors or implementation framework [2]. This confirms that this
topic is still to be fully understood. These two issues are evident partly from a global perspective,
but more specifically from a South African perspective.

The purpose of this study was twofold. First it explored the key factors faced by supply chain
members in implementing effective CPFR in the South African grocery retail environment; and
second, it identified the framework that is used by a major grocery retailer in South Africa. This
study involved a qualitative case study of one of the four largest grocery retailers in South Africa.

The following research questions were addressed in this study:

 What are the key factors affecting CPFR implementation for a major grocery retailer in South

 What framework does the major grocery retailer use to implement CPFR?

This study aimed to be academically valuable in order to contribute to an understanding of the key
factors that affect the implementation process of CPFR. The stakeholders that can benefit from this
study are academics, supply chain practitioners, and retail firms. A greater understanding of these
factors can result in improvements to CPFR implementation projects by focusing on and leveraging
those key factors. This study provides an in-depth understanding of the key factors affecting the
process of implementing CPFR, considering the challenges faced in a South African context. The
findings of the study benefit the above-mentioned stakeholders in several ways. First, the study
benefits academics by expanding on the limited literature available on the key factors of CPFR
implementation by confirming five of the six key factors, and adding two additional key factors.
Second, the study benefits supply chain practitioners by exploring (from a practice-led perspective)
the key factors of CPFR implementation of a major South African grocery retailer to allow for a
greater understanding of the implementation process and to improve the implementation efficiency
of CPFR. Third, the study adds to the literature on the frameworks used to guide CPFR
implementation by recognising a unique framework that is used by a major grocery retailer in South


Aligning supply with demand in a timely manner is a longstanding challenge that has improved over
time [2, 22, 23]. Yet relevant stakeholders are still not satisfied with the state of supply and demand
alignment [2, 22, 23]. In the case of grocery retailers around the world, this challenge is particularly
relevant. The issue of reducing inventory levels, improving lead times, accurately forecasting
consumer expenditure, appropriately planning for these forecasts, delivering on time in the correct


quantity, keeping shelves full, and managing exceptional demand through promotional events are
just a few of the challenges that are still not completely overcome [19, 24]. The literature review
explores the fundamentals of supply chain collaboration, followed by the benefits of CPFR for firms.
It then explores the various frameworks for implementation, followed by the key factors affecting
CPFR implementation.

2.1 Collaboration in the supply chain

Collaboration occurs in a supply chain “when two or more independent firms work jointly to plan
and execute supply chain operations with greater success than when acting in isolation” [2, 11, 15].
The notion of collaboration is attached to the concept of synergy and its development, which
encourages joint planning and real-time exchange of information [25]. Various approaches to
collaboration in the supply chain exist, such as vendor-managed inventory (VMI), CPFR, and
consumer response (CR). This study specifically focused on CPFR due to its beneficial potential that
has proven difficult to implement successfully and, therefore, its full benefits have not always been
realised [10, 13, 18].

Collaboration between firms should only be implemented if both entities are willing and capable of
investing time and effort, and if the projected benefits are greater than can be achieved individually
[7, 24]. Considering that collaboration is now understood as one of the best ways to increase the
likelihood of achieving an enduring competitive advantage, firms should pay attention to
collaborative implementation guidelines to establish and manage efficient collaborative
relationships. Figure 1 below illustrates the steps involved in developing collaborative relationships
between firms.

Figure 1: Steps to follow in creating collaborative relationships between firms [24]

According to Lehoux, D’Amours and Langevin [24], the starting point in the four main aspects of
creating collaboration is building collaboration. This involves the selection of partners, developing
a legal framework, and managing relationships and their adjustments. The second aspect entails
implementing coordination mechanisms for information-sharing and swift negotiation processes. The
third aspect focuses on measuring performance and benefits, which entails the general assessment
of collaborative efforts and whether these efforts are sustainable and worth the effort for
collaborating members. The fourth aspect highlights the implementation of incentives — their
selection and alignment.

2.2 The development of collaborative planning, forecasting, and replenishment

Recently the focus has increasingly been on collaboration in supply chains as a process that improves
all-round cooperation among firms [26]. During the early 1990s, efficient consumer response (ECR)








developed as a powerful collaborative initiative that arose in the grocery and consumer packaged
goods (CPG) industries [25, 27]. ECR promotes the idea of sharing strategic information and
developing relationships based on trust in order to seek improvements in supply chains, ultimately
to create a greater level of customer value [25]. It was considered to be the starting point for some
additional collaborative approaches, which included continuous replenishment (CR), vendor-
managed inventory, and CPFR. These collaborative approaches all aim to develop and improve the
level of supply chain integration through the notion of information-sharing. According to VICS [16],
CPFR is “a collection of new business practices that leverage the Internet and Electronic Data
Interchange (EDI) in order to radically reduce inventories and expenses while improving customer
service”. Danese [28] defines CPFR as a programme that seeks to improve the ability to anticipate
and satisfy future demand by enhancing collaboration among firms in the supply network. CPFR is
considered to be the most promising of these collaborative approaches, because it provides a
thorough examination of factors that can create uncertainty, such as promotional activities. Beyond
that, CPFR also focuses on delivering a greater level of coordination among retailers and
manufacturers [29]. With the development of ECR, the supply chain members, retailers, and
manufacturers started to develop collective solutions to the uncertain supply chain environments in
which they were operating.

2.3 Benefits of collaborative planning, forecasting, and replenishment

By connecting marketing and sales efforts to supply chains, CPFR enables trading partners to improve
the visibility of their critical activities using a structured framework and a process of information-
sharing and joint decision-making across organisational level boundaries [13]. In the context of
supply chain management, mutual advantages are often construed as a positive return on
investments and an increased efficiency in inventory management [24, 30]. For instance, Wal-Mart
collaborated with Warner-Lambert in the hope of attaining mutual benefits from their CPFR
initiative. The mutual benefits came in the form of improving the stock levels of Listerine from 87
to 98 per cent; lead times were essentially halved from 21 to 11 days; inventory on hand was reduced
by two weeks; sales improved by 8.5 million dollars; and orders became more consistent. Aiming for
a similar return, General Electric (GE) made an effort to collaborate with its retailers to respond
efficiently to consumer demand rather than to inventory [31, 32]. GE focused on a build-to-order-
system: both members of the supply chain eliminated the expense of holding inventory and the
assembly of full truckload orders. As a result, GE ultimately reduced its marketing and distribution
costs by 12 per cent. The retailers also experienced fewer out-of-stock situations, and increased
their profit margins on products from GE.

2.4 Frameworks of collaborative planning, forecasting, and replenishment implementation

As mentioned previously, the original and most widely known framework for CPFR implementation
is the model introduced by VICS. Several studies have explored the VICS framework or have
developed a variation on the VICS framework that entails the detailed processes of CPFR
implementation in an attempt to improve the frameworks set out by a number of researchers and
practitioners [16, 33-36].

Table 1 depicts the disparities between existing frameworks for CPFR implementation that add to
the lack of consensus.

The different frameworks vary in the number of steps, yet all start the process by developing a
front-end agreement that sets out the rules of engagement, followed by the joint business plan
(JBP). Fliedner [35] describes four simple steps in the framework; the first three steps involve
working collaboratively with the retailer and supplier. VICS [16] describes the front-end agreement
and JBP to be a part of the same step. They then go on to plan the forecasts between the supplier
and retailer, which is done collaboratively, followed by generating the orders and executing them.
They end the framework with the very important step of analysing the exception and overall
performance, which is vital for improving on the next exception. This step is not specifically included
in any of the other frameworks mentioned in Table 1 above. Chang et al. [33] separate the front-
end agreement and joint business plan into two different steps. They then forecast the regular sales
and identify the unusual sales forecasts, which is done separately by the retailer and the supplier.
The supplier and retailer meet to deal collaboratively with those unusual sales forecasts. The next
step is to forecast the orders and identify unusual order forecasts. The supplier and retailer then
deal collaboratively with those unusual order forecasts and, finally, generate and execute the


orders. Fliedner [35] and VICS [16] depict collaborative work occurring throughout the framework,
while Chang et al. [33] describe step 5 and step 8 to be specific collaborative steps in the framework.
Du et al. [34] simplify the framework into three steps. The first step involves the development of a
front-end agreement and JBP. The next step involves the collaborative efforts of the retailer and
supplier generating sales and order forecasts. The last step is to generate the orders and execute
the shipments. Shu et al. [36] divide the steps in the framework into three categories: planning,
forecasting, and replenishment. This framework also sets out specific steps in which the retailer and
supplier would forecast sales and orders separately, and then resolve them collaboratively.

Table 1: Frameworks for CPFR implementation (Source: Adapted from Hollmann et al. [3])

Fliedner [35] 1. Create a front-end agreement
2. Create a joint business plan
3. Develop forecasts
4. Replenish inventory

VICS [16] 1. Strategy and planning: an arrangement and joint business plan
2. Demand and supply management: sales forecasting and order planning/forecasting
3. Execution: order generation and order fulfilment
4. Analysis: exception management and performance assessments

Chang et al.

Based on the framework of VICS [16], but includes the process of an application service that
uses market information to improve forecast accuracy:
1. Formulate a draft agreement
2. Develop a joint business plan
3. Forecast sales
4. Identify unusual sales forecasts
5. Deal collaboratively with unusual items
6. Forecast orders
7. Identify unusual order forecasts
8. Deal collaboratively with unusual items
9. Generate orders

Du et al.

Based on VICS [16] framework, but reorganises the framework into three steps:
1. Development of a collaborative agreement and preparation of a joint business plan
2. Generation of collaborative sales and order forecasts
3. Generation of orders and execution of shipments

Shu et al.

Based on VICS [16], but reorganises the framework to include three processes and eleven
1. Decompose and search for a module
2. Reach a forward collaboration agreement
3. Create a collaboration plan
1. Forecast sales
2. Confirm exceptions in sales forecasts
3. Resolve exceptions in sales forecasts
4. Forecast orders
5. Confirm exceptions in order forecasts
6. Resolve exceptions in order forecasts
1. Create orders
2. Produce and service

2.5 Key factors affecting collaborative planning, forecasting, and replenishment

It is argued that many critical factors to CPFR implementation are both inhibitors and enablers [37,
38]. By placing the phrase ‘lack of’ in front of a key factor (such as trust), the key factor is placed
in an inhibiting light; yet trust is recognised as a key enabler, and thus the term ‘key factors’ was
developed. Several key factors enable or restrain firms from implementing CPFR successfully and
completely. It is, therefore, crucial that firms understand these key factors before embarking on
collaborative supply chain initiatives such as CPFR. The failure of CPFR to be implemented
successfully on an international scale can largely be attributed to a lack of understanding of the key
factors faced during the CPFR implementation process [8, 19, 20, 21, 29, 39, 40]. By comprehensively
reviewing the existing literature, it was found that six key factors are currently recognised [8, 19,
20, 21, 29, 39, 40]. As many firms suffer from scarce resources, the identification of the most
significant factors enables managers to engage with those aspects that are most important in


successfully implementing CPFR. The next section describes the most widely recognised key factors
that affect the implementation of CPFR.

2.5.1 Technical expertise

Technical expertise − internally and externally − is a key factor that affects CPFR implementation
[19, 35]. CPFR is complex, and a full-scale implementation in a single stage can frequently lead to
disorganisation and frustration in both management and the other participants [19, 35]. Similarly,
the implementation of small-scale CPFR projects can primarily induce the growth of technical
expertise. This technical expertise can be found internally, but if not available internally, then
supply chain consulting groups can be the focal point. An important aspect is to transfer technical
expertise to internal employees, who may provide the skills to undertake future CPFR or general
collaborative supply chain initiatives.

2.5.2 Visible and effective leadership

Visible and effective leadership is a highly important key factor in CPFR implementation [19, 20,
39]. Due to its complex nature, it requires senior leadership’s full attention to plan and implement
the concept [19, 20, 39]. Enhancing this leadership by practitioners, beginning with small-scale CPFR
projects and allowing those projects to grow to full-scale projects over time [19], is a potential
solution to this factor as an inhibitor.

2.5.3 Information-sharing

A significant factor in CPFR implementation is sharing credible information [8, 19, 20, 40]. This issue
is noted as being multi-dimensional in nature, which can be amplified by behavioural, technical,
and cultural issues. Related to the aspect of information are several factors such as visibility of
inventory levels and retail strategies; readiness and timeliness of relevant information for supply
chain partners to use; availability and compatibility of information to users; and the security of
sensitive information that is supposed to be kept from competitors [21, 25, 41, 42]. The plans of a
CPFR implementation venture should define and clearly spell out issues of confidentiality and specify
what information will be shared.

2.5.4 Trust

The factor of partner trust is crucial in CPFR implementation [20, 21, 29]. Trust can only be
developed over time, but can be supplemented by a CPFR charter of specifics that spells out the
plans and expectations for CPFR ventures. The ability to create high levels of trust can be dependent
on collaborating supply chain members ensuring that promises are met and relevant information is
accurate and timely.

2.5.5 Forecasting processes and resources

Another key factor is forecasting processes and resources, because forecasting is a fundamental part
of CPFR [19, 35]. To assist in leveraging this key factor, trading partners can develop protocols for
forecasting, and select a forecasting team with representatives from all the trading partners and
stakeholders [19]. The connection of information channels to multiple trading partners in real time
also helps to leverage this factor.

2.5.6 Calculating the benefits

Another factor in CPFR implementation is the difficulty of calculating the benefits [19]. Fu et al.
[20] support this view, stating that perceived benefits are a key factor in CPFR implementation.
Despite the potential results mentioned in the literature, these results can only be attained once all
the correct preparations have been made. From a firm’s viewpoint, it is vital to align internal
activities prior to engaging in CPFR with other parties [19].

The next section details the methodological choices.


3.1 Research design

This study employed a single case study design, which is used to study a research problem by
reviewing one or more cases in a particular context [43]. Yin [44] emphasises that cases should be
current and studied in a real-life context. Case study research uses different sources of information,
often producing very descriptive findings, as it focuses on ‘how’ or ‘why’ a specific problem occurs
[45]. This approach was selected because the purpose of the study was to understand the key factors


that affect CPFR implementation in a focal firm, as opposed to a random selection of retailers and

3.2 Sampling

The unit of analysis for this study was the processes used to implement CPFR. This study was
conducted on a major South African grocery retailer with divisional headquarters in Gauteng. A
purposive sampling strategy − homogeneous sampling − was used to identify major grocery retailers
in South Africa. In this instance, the focal firm was selected based on accessibility and because, as
one of the four major grocery retailers in South Africa, the focal firm represents a critical case.
Subsequently, snowball sampling was used to identify specific individuals in the firm who were senior
managers and who were most involved in planning, forecasting, and replenishment. The sample was
further refined by selecting employees who were also the most involved in managing suppliers. This
was done by asking each of the participants after their interview to recommend a specific colleague,
according to the above criteria [46, 47]. Table 4 below presents a summary of the participants in
this study.

Table 2: Summary of participants

Pseudonym Position Firm Duration of interview
(in minutes)

P1 Divisional logistics director C1 40

P2 Divisional marketing director C1 37

P3 Group supply chain project manager C1 38

P4 Procurement manager – fresh foods C1 34

P5 Procurement manager – dry foods C1 48

P6 National procurement manager – fresh

C1 66

Average interview time in minutes 44

Total number of participants 6

Male participants 5

Female participants 1

3.3 Data collection

The main source of data was the six semi-structured individual interviews conducted with the
research participants. Guest, Bunce and Johnson [48] suggest that, for studies with high levels of
homogeneity among the population, a sample of six interviews may be sufficient to enable
development of meaningful themes and useful interpretations. Face-to-face interviews were
organised because the researcher wanted to understand and make sense of the attitudes,
behaviours, and practices of people and firms. Based on the initial literature review, an interview
guide was developed that allowed for comparability of answers and improved the reliability of the
study [44, 45]. The interviews followed a standard path, organised under broadly defined topics
centred on CPFR implementation. Open-ended questions and probing phrases were used to
encourage detailed responses. Each interview began with general introductory questions about the
background and role of the participant. Subsequently, questions were asked that focused on CPFR,
its enablers, inhibitors, and processes for implementation. Questions were adapted, either by
changing the order of questions or changing the questions themselves, depending on the direction
the interview was taking [49]. In one instance, where the researcher was unable to record one of
the interviews, detailed notes were taken throughout the course of the interview. All interviews,
except for the aforementioned one, were transcribed by the researcher within 24 hours, following
the guidelines stipulated by Eisenhardt [50]. Validation of the transcribed interviews was offered to
the participants after each interview to request feedback, clarification, comments, or final approval
[44]. The recordings were played again to compare them with the transcriptions, and corrections
were made to ensure the transcriptions were verbatim. A pilot study was conducted to test the
quality of the questions in the discussion guide. Positive feedback was received, and no major
changes were made.

Triangulation was achieved by adding information that was gathered from informal conversations
with the participants, reviewing website information online, and making several site visits to the
focal firm [51, 52]. This data was used to confirm statements obtained from the interviews, while
additional background data was obtained to fill in missing information.


3.4 Data analysis

A thematic analysis approach was used to analyse the data in this study. This is a process in which
data is analysed across a data set in order methodically to identify, organise, and understand
emerging themes in the set of data [53]. The process applied to the set of data was proposed by
Braun and Clarke [53]. First, the researcher became familiar with the data, followed by the
generation of the initial codes. The next step involved searching for themes among the codes, which
were subsequently reviewed. The reviewed themes were then named and defined, which allowed
for the final report to be produced.

3.5 Trustworthiness

To ensure the transferability and authenticity of this study, a rich and thick description of the
participants, the methodology, the sites, and the context of the study was carried out [54, 55]. Peer
debriefing was also applied to address any trustworthiness issues. This meant that the study was
investigated by an objective third party to address any trustworthiness issues. An experienced supply
chain management academic and a methodology expert were consulted to address any reliability
issues that needed correction [55].

To ensure the internal credibility of the study, a thorough review of the existing data and
frameworks was done to relate the data to the existing literature [54]. Given the sensitivity of the
information provided, due to the competitive …

The simple truth about good forecasting
Davis, Jonathan . ; London (Apr 1, 2012).

ProQuest document link

There is always a lot to be said for keeping things simple, and it is gratifying to see how robustly accurate some of

the simplest methods of asset class forecasting continue to be. The secret of building a robust long-term record,

experience suggests, lies in giving yourself a sensible time horizon (at least five years), concentrating on a few

fundamental valuation metrics and downplaying, or better still ignoring wherever possible, macroeconomic


Jeremy Grantham of GMO is one of the leading exponents of this kind of approach and recently he was able to

point to some impressive evidence of the success of his methods. His firm’s asset allocation decisions are built

around the idea that profit margins and price-earnings ratios are mean-reverting over a period of years. He has

been doing this since 1994 and the results, so he noted in his latest quarterly letter, have turned out to be

pleasingly accurate.

Looking back at the 10-year forecasts for 11 asset classes GMO made back in December 2001, he notes that the

out-turns for the 10-year period ending in December 2011 were, with minor exceptions, both ranked in more or less

the right order and not far out either in terms of annualised real returns – not a perfect track record by any means,

but one for which most economic forecasters would give their eye teeth.

Particularly noteworthy was his firm’s prediction that emerging market equities (up 11.4 per cent a year against a

forecast of 9.4 per cent) would be the star performers of the decade while the S&P 500 – which scratched out an

annualised return of just 0.4 per cent a year against his predicted minus 1.0 per cent – would languish firmly at the

bottom of the list. There were not, unsurprisingly, many firms on Wall Street publicly predicting a “lost decade” for

US equities at the time GMO was making its original forecast.

Mr Grantham points out there is nothing particularly profound about his predictive methods. The discovery that

when stocks and bonds are expensive, they tend to perform badly, and when they are cheap, do much better is

hardly breakthrough thinking. Back in 2001 the S&P 500 was trading on 30 times earnings and emerging markets

on 13 times earnings.

Yet as so often happens, not many professional forecasters drew the obvious, right conclusions. No doubt this

was partly for professional reasons. The investment business is dominated by short-term pressures and its default

position tends to be biased towards orthodoxy and bullishness.

GMO’s estimates, says Mr Grantham, “are not about nuances or PhDs. They are about ignoring the crowd, working

out simple ratios, and being patient. But if you are a professional, they would also be about colossal business risk

… The problem is that though they may be simple to produce, they are hard for professionals to implement.” GMO’s

all-too-accurate market forecasts cost it a lot of business at the time.

Another veteran of the industry who favours a keep-it-simple approach to valuations and asset allocation is Jack

Bogle, the founder of Vanguard. In his early books about the fund business, he used a relatively straightforward

variant of the cyclically adjusted p/e ratio to come up with broad 10-year forecasts for stock returns, while noting

that the current 10-year bond yield is in practice a perfectly workable and normally reliable estimate of the next

decade’s most likely return from bonds. (He was, of course, writing before the Fed and other central banks started

trying to manipulate the yield curve for their own purposes as blatantly as they are doing today).

His successors at Vanguard now use a range of sophisticated techniques, including Monte Carlo simulations, to

model ranges for future bond and equity market returns, but the underlying philosophy remains essentially the

same as that of the founder. “Our long held view,” write strategists Joseph Davis and Roger Aliaga-Diaz in

Vanguard’s 2012 annual investment outlook, “is that market valuations generally correlate with future stock

returns” while “consensus economic growth expectations and initial dividend yields do not”.

Applying this approach today, they argue there is no reason why future stock market returns should disappoint

today even if economic growth disappoints, as it tends to do in the aftermath of global financial crises. Their

central case is that over the next 10 years equities have a 50 per cent chance of matching or beating the 6 per cent

annualised real return they have achieved since 1926.

Bonds will produce lower nominal returns than their historical average, but will retain their diversification value

even as bond yields start to rise, as they are bound to do over the next decade. Implicit therefore in their view is

that the correlation between bond and equity market performance will stay low.

GMO’s blunter advice is to be underweight long- term bonds and broadly neutral on global equities (though heavily

biased in the US towards quality stocks). If you believe in the value of these simple methods, the dull but

reassuring message is that, on a 10-year view, equity markets are probably priced about right for once, which is not

a universally shared opinion.

[email protected]

Credit: By Jonathan Davis


Subject: Stock exchanges; Economic growth

Business indexing term: Subject: Stock exchanges Economic growth

Publication title:; London

Publication year: 2012

Publication date: Apr 1, 2012

Publisher: The Financial Times Limited

Place of publication: London


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The simple truth about good forecasting

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