BNCE GC01: Game Consoles
(GCs) Government Standards
Evidence Base 2009: Key Inputs
Version 1.1
This Briefing Note and referenced information is a public consultation document and will be
used to inform Government decisions. The information and analysis forms part of the
Evidence Base created by Defra’s Market Transformation Programme.
1
Introduction
• The aim of this Briefing Note is to provide details and reference sources of the
underlying data in the model, along with the key assumptions used in the model.
• There are three main sections to this Briefing Note, corresponding to the main
variables of the MTP modelling approach:
o Ownership & stock
o Sales
o Usage & lifespan
• Each section also includes an indication of the overall confidence in the dataset, to
provide a sense of the robustness of the model.
• Since preparing the data for Government Standards in 2009, new sources of evidence
have been found or been made available. They will be taken account of in future
revisions of data. New sources as follows:
o Act on CO2 study data
o Nelson EU study data
o Manufacturer (anonymous) data
•
A “Game Console” is a mains powered stand alone device which is marketed as a
product providing video game playing as its primary function through an external
screen and which has the following features:
Hardware Architecture
Central Processing Unit (CPU)
System memory
Video architecture
Network architecture
Optical drives (to be defined)
Hard drives or other internal memory (optional)
Mains connected internal or external power supply unit
•
•
•
•
•
•
•
Input devices
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• Typically hand held controllers rather than keyboards or mice
Optional Secondary functions
• Optical disk playback
• Digital picture viewing (via an external screen)
• Digital music playback
Excluded components or functionalities:
• Integrated screens
• Conventional Personal Computing (PC) operating systems
• Internal batteries for powering products over extended periods of time
2
Ownership & stock
2.1
•
•
•
•
1
Summary
Stock data is derived from sales figures since this gives the most complete and
reliable dataset. Stock has increased very rapidly over the past few years and is
expected to continue to grow.
An increasing number of households1 own game consoles, and multiple ownership is
common for heavy gamers who want to play games exclusive to particular consoles.
This could include multiple generations of one console brand, as well as multiple
brands of current consoles. This means that despite stock of 20 million in 2010,
household ownership is projected to be much less than 100% and stock will continue
to increase.
The main gamers include children aged 11-17 and men aged 21-37. The average age
of gamers is increasing as the first generation of gamers continues to age, rather
than leave the demographic. As new (young) gamers join the lower end of the
demographic the stock and household ownership rates will increase.
Table 2 shows 2009 as the most recent (calculated) stock data point. There are no
actual stock data points available.
Refer to BNXS25 UK Household and Population Figures 1970-2030 for details on figures used.
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Figure 1 Game Consoles Stock
Table 1 Game Consoles Stock
Game
consoles
(000’s)
2008
2010
2020
2030
15,819
19,912
29,859
30,727
•
Game consoles are released in generations, with subsequent generations being
graphically and computationally more powerful than the previous.
•
Each generation is expected to dominate sales for around 5 years before a new
model is introduced (however the model accounts for smaller quantities of
products continuing to be sold and remaining in stock past this 5 year threshold).
As a result, sales of legacy (older generation) products reduce considerably in
anticipation of new console launches as consumers are unwilling to buy products
which appear to be nearing obsolescence. This slow-down in sales leads to a dip
in the stock level of legacy games consoles
•
However, game console launch prices are very high and there are very few next
generation game titles available immediately. Therefore sales of the new
generation of product only spike 1-2 years after launch when prices fall. This
exacerbates the dip observed in the legacy stock levels
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Therefore, high variability as one generation replaces another can be seen
with clear dips in the stock level (See
•
2.2
•
•
2.3
Figure 1, years 2006 and 2013). In particular, the most recent generation,
including the Nintendo Wii, has led to a very sharp spike in sales. Beyond 2020,
this cycle is ignored in sales projections for simplicity, and the stock curve
becomes smooth.
Data sources – ownership & stock
There are no reliable data sources for ownership and stock (sales more reliable).
This model is a sales-based model, which calculates stock automatically using the
sales projection and the product lifespan. Real stock data is put in as a check
only, to help evaluate the output stock calculated from the model. This data
series is usually incomplete. The stock shown in the previous charts and tables
were to illustrate the full generated (rather than input) stock data series.
Methodology & key assumptions – ownership & stock
2.3.1 Historic data
Table 3 Interpolation & background calculations – ownership & stock
Year
Methodology & assumptions
1960-2008
The MTP model is a sales-based model, which calculates stock
automatically using a sales projection, the product lifespan and a sales churn
calculation to account for products purchased in previous years gradually leaving
stock. Real stock data is put in as a check only, to help evaluate the output stock
from the model. This data series is usually incomplete.
2.3.2 Future analysis
Table 4 Extrapolation & background calculations – ownership & stock
Year
Methodology & assumptions
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Year
Methodology & assumptions
2009-2030
The MTP model is a sales-based model, which calculates stock
automatically using a sales projection, the product lifespan and a sales churn
calculation to account for products purchased in previous years gradually leaving
stock. Real stock data is put in as a check only, to help evaluate the output stock
from the model. This data series is usually incomplete.
2.4
Data issues – ownership & stock
• This section flags any areas of uncertainty, both in general and for specific data
points, along with a description of how this has been dealt with in the model.
Table 2 Data issues – ownership & stock
Issue/risk
Approach
taken/rationale
Only a single stock data source was identified. Mintel (2008) Video
and computer games, leisure intelligence, August 2008.
2008 stock estimates of 28 million consoles could not be reconciled
with much lower sales calculations.
Data was not used since it is
over 30% higher than sales
data calculations. Mintel has
based stock calculation on
game consoles that no longer
appear to be in use in general
population. Usage is
calculated based on consoles
currently in-use, and therefore
stock must disregarded if it
has been stored away.
2.5
Confidence level – ownership & stock
• This section provides an indication of overall confidence in the data set (i.e. data
Data
quantity /
size of
data set
points, calculations, interpolation and projections)
• No stock or ownership data has been used
HIGH
LOW
HIGH
LOW
Source integrity / robustness of data
Figure 2 Confidence indicator for ownership data
3
3.1
Sales
Summary
As discussed in the stock section, game consoles are released in generations
around every 5 years, with sales being artificially suppressed in
anticipation of new console launches and price reductions
(therefore, sales only spike 1-2 years after launch when prices fall).
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As a result, high variability as one generation replaces another can
be seen with clear drops in sales (See
Figure 3 - Sales). The following releases are accounted for:
o Xbox 360 launched 2005, major sales volumes delayed to 2007,
o Wii launched 2006, major sales delayed to 2007,
o PS3 announced 2006, major sales 2007,
o Anticipated replacements launched 2013.
• In particular, the most recent generation including the Nintendo Wii has led to a very
sharp spike in sales. Beyond 2020, this cycle is ignored in sales projections for
simplicity.
• Convergence with traditional video recorders and players is not expected to occur to a
high degree due to the significant additional cost of purchasing a game console and
the additional complexity of operating a game console.
• Table 7 starts from 2008 as this is the most recent actual data point
•
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Figure 3 Game Consoles Sales
Table 3 Game Consoles Summary Sales
Game
consoles
(000’s)
2008
2010
2020
2030
3.2
4,210
4,554
5,500
5,500
Data sources - sales
Table 4 Sales data sources
Year
Reference
Reference
date
1975,
1980,
1983,
1986,
1987,
1989,
2000,
2013,
2015
Expert
assumption
based on
console
release dates
2009
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Author
MTP
Technical
Expert
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Justific
ation
Confidence
in sources
(High/Low)
No
available
data
Low
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Year
Reference
Reference
date
1986,
1989
The NES
precedent:
Lessons
learned at
Nintendo to
make Wii
successful
VGChartz.co
m
2008
Accessed
2009
20002008
3.3
•
Author
Justific
ation
Confidence
in sources
(High/Low)
VGCHartz
Best
available
data
Low
VGChartz
Detailed
data, long
time
series
High
Methodology & key assumptions - sales
At the point of launch of the new generation product, it is assumed that sales of
legacy generation will continue at a lower rate for approximately 2 years until the
sales of the new generation peak. From that point some sales of legacy generation
will continue as stock clearance occurs.
3.3.1 Historic data
Table 5 Interpolation & background calculations – sales data
Year
Methodology & assumptions
1975
No data available - Low sales assumed of first game console launched (100
units)
No data available - assumed total sales to have reached 50,000 units
No data available - Launch of NES (Nintendo Entertainment System) with
increased sales – assumed total sales of this and previous generation to be
167,000 units
2
UK sales calculated at approx 18% of USA sales. This ratio is used against 1986
USA NES sales from VGChartz (2008).
Launch of SNES (Super Nintendo Entertainment System), reaching a more
mainstream children and teen audience which is assumed to increase sales
approximately 400% compared to NES launch. As no data available, assumed.
otal sales of this and previous generations to have reached 827,000 units by 1987
2
UK sales calculated at approx 18% of USA sales This ratio is used against 1989
USA NES sales from VGChartz (2008)
No sales data available for legacy game consoles in the “older” sub-category of
game consoles (e.g. SNES, PS1). Assumed sales of “older” consoles to be 1
million units in 2000 as sales of next generation products begin to increase
sharply.
Data interpolated using assumed data points listed above and the VGChartz sales
data from 2000-2008 and smoothed using two sided exponential window, two
pass (kalman filter and lagrange multiplier)
1980
1983
1986
1987
1989
2000
1975-2008
2
In 2003 and 2008, UK sales of GCs were approx.18% of those in the USA – ratio calculated from
VGChartz data
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3.3.2 Future analysis
Table 6 Extrapolation & background calculations – sales data
Year
Methodology & assumptions
2013
Assumed launch of next generation of game consoles with low sales to early
adopters only, due to high sales price and few games available. This increases to
a maximum of 6.5 million in 2015 which represents a saturated market (where all
users likely to want that generation of game console, at that price, have one, and
the ownership level of GCs in general is equivalent to almost 100% of
households).
Sales reach 6.5 million – see assumption for 2013 above.
Sales stabilise at 5.5million creating stock of slightly over 30 million of actively
used game consoles, reflecting high uptake and market saturation with some
households owning multiple game consoles platforms of the same generation or
overlap with previous generations.
Data interpolated from last actual data point in 2008, and assumptions in 2013,
2015 and 2019 and smoothed using two sided exponential window, two pass
(kalman filter and lagrange multiplier)
Beyond 2020, the cycle of sales peaks due to “new generation” product launches
is ignored in sales projections for simplicity. Assumed sales are unchanged from
2019 at 5.5 million.
2015
2019
2009-2019
2020- 2030
3.4
•
Data issues - sales
This section flags any areas of uncertainty, both in general and for specific data
points, along with a description of how this has been dealt with in the model
Table 7 Data issues - sales
Issue/risk
Approach taken/rationale
Next generation game consoles may
come in sooner than 2013
No changes made. To be addressed in next revision
as there becomes greater certainty on near-future
trends.
Methodology reviewed and considered reliable.
Widespread use of data provides confidence data is
reliable.
Only one data source available, which is
not an established, widely recognised
organisation.
GfK data will be used in conjunction for future models
(depending on feasibility/sanity checking on figures).
3.5
•
•
Confidence level
This section provides an indication of overall confidence in the data set (i.e. data
points, interpolation and projections).
Small but detailed dataset from single source, using reliable methodology. VG Chartz
is a video game sales tracking website that provides weekly sales figures of console
software and hardware by region and is ranked amongst the top 5,000 websites in
the United States and serves over 3 million page impressions3. VG Chartz has
defended the credibility and reliability of its sales data, often comparing their numbers
with the ones published by NPD Group4, although sometimes the reports are altered
after NPD numbers come out (providing in-built sanity check). News organizations
such as BBC, Forbes, Fortune, The New York Post, Yahoo and The New York Times
have used VG Chartz for sales data in their publications.
3
Wikipedia
The NPD Group, founded in 1967, is a leading global provider of consumer and retail market research
information for a wide range of industries – http://www.npd.com
4
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Data
quantity /
size of
data set
HIGH
LOW
HIGH
LOW
Source integrity / robustness of data
Figure 4 Confidence indicator for sales data
4
4.1
Usage & lifespan
Summary
• Active use is assumed to be generally low (approx 0.4 hr/day) due to large number of
rarely used consoles.
• On-idle time is projected to increase from an assumed level of 1 hr/day to 1.5 hr/day
by 2013 as more downloadable content is made available to users, which makes
increased use of the console more attractive.
• Standby time is assumed to be approximately 10 hr/day because games consoles
have a “young” demographic (who are assumed to be less energy aware) so a large
proportion will not be switched off. As is common with consumer electronics, there is
no hard-off switch and the plug is often inaccessible behind the TV cabinet.
• Console lifespan represents the period for which it is actively used. This is assumed to
be five years before they begin to be replaced by new generation consoles, For
simplicity, it is assumed that this is the same for all console formats.
Table 8 Summary Lifespan
Games
consoles (yrs)
2008
2010
2020
2030
5
5
5
5
Table 9 Summary Usage (hr/yr)
2008
2010
2020
2030
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On
On-idle
Standby
156
156
156
156
365
438
548
548
3,650
3,650
3,650
3,650
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4.2
Data sources – usage & lifespan
Table 10 Usage & lifespan data sources
Year
Reference
Reference
date
Author
Justific
ation
Confidence
in sources
(High/Low)
2008
The state of
the video
gamer
2009
Nielsen
Best
available
data
Low
2008
Expert
assumption
2009
Question of
the Day: Do
You Leave
Your Game
Console
Running?
http://gizmod
o.com/50944
11/questionof-the-daydo-youleave-yourgameconsolerunning
2008
no
reliable
data
Lack of
alternativ
e hard
evidence
on usage
of these
products
low
2008
MTP
(Anson
Wu)
Gizmodo
4.3
Low
Methodology & key assumptions – usage & lifespan
• This section describes what has been done with the data listed in Table 10 along with
a rationale for any key assumptions (in particular any expert judgements listed in
Table 10) and detail of any background calculations behind the data points.
4.3.1 Historic data
Table 11 Interpolation & background calculations – usage & lifespan data
Year
Methodology & assumptions
2008
Lifespan is assumed to be constant throughout the period modelled, both for
historic and current game consoles. It is assumed to equal the length of each
generation cycle, after which it is replaced and no longer actively used, as new
(incompatible with legacy product) games with better graphics and features come
into vogue.
Whilst games consoles are able to play back DVD or Blu-ray (BD) disks (Xbox360
and PS3), the controllers are clumsy for this purpose and are not suited to a wider
audience who are more accustomed to video recorder/player remote controls.
Currently, games machines incorporating BD playback may well be used to watch
video, but this likely to change as BD devices fall rapidly in price and incorporate
additional features/content via Blu-ray live.
Sales of consoles between 2006 and 2009 have risen rapidly as the appeal of
consoles like the Wii reaches out to new audiences with new applications like Wii
Fit etc. Usage figures have been assumed to be the same for these new users, as
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Year
Methodology & assumptions
a larger percentage of the population use the games consoles.
1960-2007
2008
Lifespan is unchanged from 2008 assumption at 5 years.
Average on-time is calculated from the Nielsen report. Each games console
model type is stock weighted in the UK MTP model to calculate energy
consumption.
5
The Nielsen survey is USA based and carried out in December, over a major
holiday period. This suggests usage is high because games consoles (and other
consumer electronics) tend to be more heavily used in the USA and Christmas
and Thanksgiving. These figures therefore would imply elevated energy
consumption in the report.
Nielsen data also suggests that higher power consoles have higher usage times.
However, in the MTP model the same usage time has been used for all product
sub-categories, thereby creating a tendency for the MTP model to understate
usage of higher power consoles and overstate usage of lower powered consoles.
It is assumed that when the (overestimated) figures from the Neilsen report are
put into the MTP model (underestimate) that they compensate for one another
and no further correction is made here or elsewhere
On-idle time estimated at 1 hour. This is less than the Gizmodo survey which is
assumed to be the absolute upper bound (See data issues)
Standby time is assumed to be half the sum of the Gizmodo survey standby and
off time. This is because there is no clear distinction between off, standby and
unplugged. For clarification: The user interface in current generation consoles
uses the term “off” to refer to the mode that is represented as standby in this
model.
2008
2008
4.3.2 Future analysis
Table 12 Extrapolation & background calculations – usage & lifespan data
Year
Methodology & assumptions
2009-2030
2009 -2012
2013
Lifespan assumption unchanged from 2008 at 5 years.
Linear interpolation applied to historic 2008 and assumed 2013 usage data points.
On-idle time is assumed to increase to 1.5 hours in 2013 as more downloadable
content is available and consumed, e.g. movies, games.
On-idle time unchanged from 2013 at 1.5 hours per day
2014 -2030
4.4
Data issues – usage & lifespan
• This section flags any areas of uncertainty, both in general and for specific data
points, along with a description of how this has been dealt with in the model
5
Since this analysis was carried out, an EU specific survey has been identified. This can be used to inform
further modelling revisions.
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Table 13 Data issues – usage & lifespan
Issue/risk
Approach taken/rationale
The Gizmodo (2008) survey is an
informal small self-selected, 24hr survey
run on a technology enthusiast website.
It was taken as a response to the Natural
Resources Defense Council (NRDC
2008) assumed usage cycles. It is
assumed that this still over-estimates
usage, as most users logging on to this
site would be high use
gamers/enthusiasts (sense checked by
examining the high % of users running
6
Folding@Home continuously). Based on
UK stock data, considering that 3% of
game consoles were shown to be
running folding at home, this would
suggest around 30% of all PS3 console
users are running this (only PS3
consoles can run this facility) which is
7
very high based on published statistics.)
Data from NRDC (2008) “Lowering the
cost of play”, suggests much higher onidle and usage times than Gizmodo or
Nielsen
Data has been treated as an upper bound and
assumptions are made that are lower than this.
Usage data is very unreliable
4.5
This does not agree with Gizmodo and Nielsen data
when taking into account the high stock levels and
the large proportion of game consoles which are
rarely used. NRDC recognise the variability in usage
patterns but have highlighted usage figures from the
high-end gamer profile rather than an average across
all users.
Since usage data is very unreliable, it may be
possible to use either attachment rates (games sold
per console) or time spent connected to the game
console host site (in connected play), to provide
alternative estimates for cross-reference. The
feasibility of this could be assessed for future model
revisions.
Confidence level – usage & lifespan
• This section provides an indication of overall confidence in the data set (i.e. data
points, interpolation and projections)
• Very little data and low confidence since non-UK and unsuitable presentation.
6
Folding@home is a distributed computing project which studies protein folding, misfolding,
aggregation, and related diseases – run by Stanford University. Gamers run the folding@home
programme on their console when they are not playing games (e.g. overnight). This changes the use
pattern to increase the on-time of the game console.
7
http://folding.stanford.edu/English/Stats - in 2008, the global population of connected cpu’s was
250,000 units which includes all PC types not just games consoles, whereas for the UK alone, stock
of PS3s in 2008 was 1.5 million units
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Data
quantity /
size of
data set
HIGH
LOW
HIGH
Source integrity / robustness of data
LOW
Figure 5 Confidence indicator for usage & lifespan data
Related MTP information
•
Briefing Note BNCE_GC02: Government Standards Evidence Base 2009 –
Reference Scenario, Game Consoles (GCs)
Changes from previous version
•
•
Minor updates to clarify text in light of stakeholder responses to the 2010
Consultation 'Saving energy through better products and appliances.'
Minor changes to the template.
Consultation and further information
Stakeholders are encouraged to review this document and provide suggestions that may
improve the quality of information provided, email [email protected] quoting the
document reference, or call the MTP enquiry line on +44 (0) 845 600 8951.
For further information on related issues visit http://efficient-products.defra.gov.uk
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