Advanced

Fashion Forecasting Example: Hope Sweden

Wiren, Johannes (2008) MIO920
Production Management
Abstract
Hope was founded in 2001 by Ann Ringstrand and Stefan Söderberg. Since then the
company has grown rapidly. It has won many prestigious design awards and is
considered one of the most promising Swedish fashion companies. To gain control of
their expansion they needed a sales forecasting tool.
The search for a suitable method started with Hope’s sales order history. Due to very
short and irregular records showing no noticeable patterns, the information had to be
left aside and considered as of no use for forecasting future sales. A sales forecasting
benchmarking study was carried out among Hope’s competitors. It revealed how little
faith was put into forecasting when it came to fashion. Production orders are always
made upon known... (More)
Hope was founded in 2001 by Ann Ringstrand and Stefan Söderberg. Since then the
company has grown rapidly. It has won many prestigious design awards and is
considered one of the most promising Swedish fashion companies. To gain control of
their expansion they needed a sales forecasting tool.
The search for a suitable method started with Hope’s sales order history. Due to very
short and irregular records showing no noticeable patterns, the information had to be
left aside and considered as of no use for forecasting future sales. A sales forecasting
benchmarking study was carried out among Hope’s competitors. It revealed how little
faith was put into forecasting when it came to fashion. Production orders are always
made upon known demand in Hope’s segment of the industry and that is why no one
of the interrogated companies even considered forecasting. The theoretical study
depicts fashion as an unpredictable and volatile industry where few rules apply. To
unite the empirical findings of fashion articles with quantitative forecasting
techniques has due to many factors shown to be difficult. A quantitative method
requires often 20 time periods, for Hope corresponding to 10 years of history. An
article rarely lasts more than a season and it would consequently have to be linked,
subjectively, to a similar item. Furthermore the conditions are changing rapidly.
Yesterday was yesterday and today the circumstances are new. The retail buyer
function is essential to Hope’s sales forecasting. In the end it determines the sales
results. Its function was closely investigated in the pursuit of universal behaviour that
could be the foundation of a forecasting tool. The procurement investigation brought
a buyer portrait far from the analytic and calculating purchaser in the little existing
literature. Instead he was impulsive and intuitively deciding his shop’s assortment
and quantities.
According to retail buyers, sales history is of little use in the fast moving fashion
business. They do not employ mathematical models, however still their experience is
founded on in store sell-through figures. As the sales records available to Hope
include the retailers’ forecasting error, they should not be utilised.
The conclusion is that in order to improve forecasting methods, a closer relationship
with the retailers is required. Even then, other precautions are necessitated to reduce
the risk of predicting the volatile fashion market. By continuously sharing inventory
numbers, two-ways, Hope can anticipate a sell out and restart its production in time.
The importance of the forecast is thus reduced through an open and more flexible
supply chain. (Less)
Please use this url to cite or link to this publication:
author
Wiren, Johannes
supervisor
organization
course
MIO920
year
type
M1 - University Diploma
subject
other publication id
08/5313
language
English
id
1979656
date added to LUP
2011-06-17 14:21:21
date last changed
2011-06-20 11:12:50
@misc{1979656,
  abstract     = {Hope was founded in 2001 by Ann Ringstrand and Stefan Söderberg. Since then the
company has grown rapidly. It has won many prestigious design awards and is
considered one of the most promising Swedish fashion companies. To gain control of
their expansion they needed a sales forecasting tool.
The search for a suitable method started with Hope’s sales order history. Due to very
short and irregular records showing no noticeable patterns, the information had to be
left aside and considered as of no use for forecasting future sales. A sales forecasting
benchmarking study was carried out among Hope’s competitors. It revealed how little
faith was put into forecasting when it came to fashion. Production orders are always
made upon known demand in Hope’s segment of the industry and that is why no one
of the interrogated companies even considered forecasting. The theoretical study
depicts fashion as an unpredictable and volatile industry where few rules apply. To
unite the empirical findings of fashion articles with quantitative forecasting
techniques has due to many factors shown to be difficult. A quantitative method
requires often 20 time periods, for Hope corresponding to 10 years of history. An
article rarely lasts more than a season and it would consequently have to be linked,
subjectively, to a similar item. Furthermore the conditions are changing rapidly.
Yesterday was yesterday and today the circumstances are new. The retail buyer
function is essential to Hope’s sales forecasting. In the end it determines the sales
results. Its function was closely investigated in the pursuit of universal behaviour that
could be the foundation of a forecasting tool. The procurement investigation brought
a buyer portrait far from the analytic and calculating purchaser in the little existing
literature. Instead he was impulsive and intuitively deciding his shop’s assortment
and quantities.
According to retail buyers, sales history is of little use in the fast moving fashion
business. They do not employ mathematical models, however still their experience is
founded on in store sell-through figures. As the sales records available to Hope
include the retailers’ forecasting error, they should not be utilised.
The conclusion is that in order to improve forecasting methods, a closer relationship
with the retailers is required. Even then, other precautions are necessitated to reduce
the risk of predicting the volatile fashion market. By continuously sharing inventory
numbers, two-ways, Hope can anticipate a sell out and restart its production in time.
The importance of the forecast is thus reduced through an open and more flexible
supply chain.},
  author       = {Wiren, Johannes},
  language     = {eng},
  note         = {Student Paper},
  title        = {Fashion Forecasting Example: Hope Sweden},
  year         = {2008},
}