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Business Operations Survey: 2013
Embargoed until 10:45am  –  02 April 2014
Data quality

Period-specific information
This section contains information that has changed since the last release. 

General information
This section contains information that does not change between releases.

Period-specific information

Reference period

The survey was posted out in August 2013. We collected information for the last financial year for which the business had data available at that point.

Response rate

We aimed for an 80 percent response rate. We achieved an actual response rate of 80.7 percent, which represented 5,667 businesses. The final estimated population size was 36,360 enterprises.

Interpreting the data

Sampling errors

Most of the tables in this release contain percentages of the total number of New Zealand businesses within each size and industry. The absolute sampling errors for the overall New Zealand business population are presented in table 1.01. These errors should be used as a guide for judging the reliability of figures in the Excel tables that accompany this release. Table 1.01 should only be used on the overall estimates that are percentages of the different types of businesses mentioned below.

Table 1.01

 Sample errors for Business Operations Survey: 2013
   Size of estimate (percentage)
 1 2 3 5 10 20 30  50 70 80 90 95 97 98 99
 Sampling error
 All businesses 0.4 0.6 0.8 1.0 1.3 1.8 2.0 2.2 2.0 1.8 1.3 1.0 0.8 0.6 0.4
 Innovators 0.6 0.9 1.0 1.3 1.8 2.4 2.8 3.1 2.8 2.4 1.8 1.3


 0.9  0.6

Table 1.02 presents the sample errors for the different size and industry groups in the survey. This table should only be used on the overall estimates that are percentages of all New Zealand businesses.

Table 1.02

Business Operations Survey: 2013 sample errors by size and industry 
Business size or industry category  Estimate size (percent)
 1 5 20 50 
Sampling error 
Business size      
6–19 employees  0.6  1.3  2.3  1.3
20–49 employees  0.7  1.5  2.7  1.5
50–99 employees  0.3  0.7  1.3  0.7
100+ employees  0.4  0.8  1.5  0.8
Agriculture, forestry, & fishing 1.3  2.8 5.1  6.4
Agriculture 1.8 3.8 7.1 8.8
Commercial fishing 1.6 3.5 6.3 7.9
Forestry and logging 2.1 4.6 8.4 10.5
Agriculture, forestry, and fishing support services 1.7 3.6 6.7


Mining 1.1  2.5  4.6  5.7
Manufacturing   0.6  1.4  2.6  3.3
     Food, beverage, & tobacco  1.7  3.8  6.9  8.6
     Textile, clothing, footwear, & leather 1.5  3.3  6.1 7.6
     Wood & paper product  2.1  4.7  8.5  10.7
     Printing, publishing, & recorded media  1.8  4 7.4  9.2
     Petroleum, coal, chemical, & associated product  1.8  4.0  7.3  9.1
     Non-metallic mineral product  1.8 3.9  7.2 9.1
     Metal product  1.8  4  7.4 9.2
     Transport & industrial machinery & equipment 1.8  4  7.4 9.2
     Other machinery & equipment 1.6  3.5  6.4 8.0
     Other manufacturing  1.9  4.2  7.8 9.7
Electricity, gas, water, & waste services  1.0  2.1  3.9 4.9
Construction  1.8  3.9  7.1 8.9
Wholesale trade  1.4  3.1  5.7 7.2
     Machinery & equipment wholesaling  1.8 3.9  7.1  8.9
     Other wholesale trade  1.9 4.2  7.8  9.7
Retail trade  1.7  3.7  6.8 8.5
Accommodation & food services  1.9  4.2  7.7  9.6
Transport, postal, & warehousing  1.8  3.9  7.2  9.0
Information media & telecommunications  1.2  2.5  4.7  5.8
     Publishing  2.3  5.1  9.3  11.6
     Motion picture  2.1  4.6  8.4  10.5
     Telecommunications  1.3  2.9  5.4 6.7
Financial & insurance services  1.3  2.8  5.1 6.4
     Finance  0.7  1.6  2.9 3.6
     Insurance  0.8 1.7  3.2 4.0
     Auxiliary  2.1  4.5  8.2  10.3
Rental, hiring, & real estate services 1.9  4.3  7.8  9.8
Professional, scientific, & technical services  1.3 2.8  5.2 6.5
     Computer systems design  1.6  3.5  6.4 8.0
     Other professional scientific  1.6  3.4  6.2


Administrative & support services  1.2  2.6  4.8 6.0
Education & training  1.4  3.3  6.0 7.5
Health care & social assistance  1.3  2.9  5.4 6.8
Arts & recreation services  1.8  3.9 7.1  8.9
Other services  2.0  4.3  7.9  9.9
Overall  0.4  1.0  1.8  2.2

The sampling errors provided in tables 1.01 and 1.02 are measured at the 95 percent confidence level.

How to use the sampling errors

For example, suppose the estimated proportion of businesses in New Zealand reporting an activity is 20 percent. This estimate is subject to a sampling error of approximately plus or minus 1.8. This means that 95 percent of the possible samples of the same size will produce an estimate between: 20 - 1.8 and 20 + 1.8, that is, between 18.2 and 21.8.

For example, suppose the estimated proportion of businesses in the agriculture, forestry, and fishing industry reporting an activity is 50 percent. This estimate is subject to a sampling error of approximately plus or minus 6.4. This means that 95 percent of the possible samples of the same size will produce an estimate between: 50 - 6.4 and 50+ 6.4, that is, between 43.6 and 56.4.

The sampling errors detailed in table 1.02 only show the sample errors for some estimates. This is because sample errors for estimates higher than 50 percent mirror those below 50 percent. For example, an estimate of 30 percent of businesses will have the same sample error as an estimate of 70 percent.

For more information refer to sampling errors, under 'General information'.

Consistency with other periods

The modular structure of the Business Operations Survey means its content changes each year as results are released. Statistics NZ works with other organisations to develop the mix of content for this survey. Table 1.03 shows how these groups contributed to the development of the survey.

Table 1.03

 Business Operations Survey module structure
  Module content 
 Module A   Module B  Module C   Module D
 2005  Business operations Innovation  Business practices   N/A
 2006  Business operations ICT  Employment practices   N/A
 2007  Business operations  Innovation  International engagement   N/A 
 2008  Business operations ICT   Business strategy and skills  N/A
 2009  Business operations  Innovation  Business practices   N/A 
 2010 Business operations ICT   Price and wage setting  Financing 
 2011 Business operations  Innovation  International engagement  N/A
 2012 Business operations   ICT Impact of regulation  N/A


Business operations  Innovation  Business practices  Skill needs and recruitment 
Note: ICT – information and communication technology; N/A – not applicable.

Table 1.04

Contribution to content
 MBIE  MED  MSI  DOL Treasury NZTE ComCom RBNZ  Vic Uni   MFE  
 2005  N  Y  Y  Y  Y  N  N  N N  N
 2006  N  Y  N  Y  Y  N  N  N N  N
 2007 N  Y  Y  N  Y  Y  Y  N N  N
 2008 N  Y  Y  Y  Y  N  N  N N
 2009  N  Y  Y  N  N  N  N  N N
 2010  N  Y  N  N  N  N  N  Y Y
 2011 N  Y Y  N  N  N  N  N N
 2012 Y N N  N  N  N N   N  Y
 2013  N  N  N  N  N  N
Note: Y – Yes; N – No; N/A – Not applicable; MBIE – Ministry of Business, Innovation and Employment, previously separate agencies of MED, DOL and MSI; MED – Ministry of Economic Development; MSI – Ministry of Science and Innovation, previously the Ministry of Research, Science & Technology; DOL – Department of Labour; NZTE – New Zealand Trade & Enterprise; ComCom – Commerce Commission; RBNZ – Reserve Bank of New Zealand; Vic Uni – Victoria University; MFE – Ministry for the Environment.

In addition, each module in the survey has its own specific objectives. The modules included in the Business Operations Survey 2013 and their objectives are listed below.

Module A: Business operations

This module aims to provide a longitudinal series of information relating to business performance. This will help development of models aimed at investigating causal relationships. As well as traditional measures of performance such as turnover and profitability, there is also a need to collect information on such areas as export intensity. The purpose of collecting business environmental information is to analyse any relationships between the environment in which a business operates and the results it achieves.

Module B: Innovation

Module B alternates between innovation (in odd years) and information and communication technology (ICT) (in even years). The objective of the innovation module is to provide information on the characteristics of innovation in New Zealand's private-sector businesses. This information will allow policies to be developed to facilitate innovation, and understand the dynamics of innovative businesses.

The innovation module runs every two years, and replaced Statistics NZ's former Innovation Survey, last run in 2003. The module was designed in accordance with OECD guidelines to develop an understanding of the contribution of all aspects of innovation to the New Zealand economy by measuring: 

  • levels of business innovation
  • how and why businesses collaborate with other businesses and institutions to innovate
  • factors affecting the ability of businesses to innovate
  • outcomes of innovation for businesses, including its effect on exports.
Module C: Business practices

This module collects data on a range of practices (including management practices and behaviours), which were collected in the Business Operations Survey 2005, and 2009. The module collected information on:

  • strategy, goals, and planning
  • customers
  • suppliers
  • information and benchmarking
  • employee practices
  • quality and process.
Module D: Skill needs and recruitment

This module collected information on businesses' experiences with skill gaps and their recruitment. Some questions were previously collected in different modules in 2008 and 2006. It also included some new questions, previously not collected. Topics of the module included:

  • vacancies
  • internal skill gaps
  • employment practices.

General information

Data source

For New Zealand's economic performance to be measured against initiatives aimed at increasing economic growth, data of a variety of measures needs to be collected.

Because of the large range of data needed, Statistics NZ developed an integrated, modular survey – the Business Operations Survey – to collect the required information and minimise the reporting load for New Zealand businesses. The survey was designed to include a range of ‘modules’ and has been run annually by Statistics NZ since 2005.

The Business Operations Survey was a postal survey. Initial contact was made to key and/or complex businesses in the survey by telephone, before the mail-out, to determine who to direct the survey to. For all other businesses, we addressed the survey form to the managing director. The survey was posted out in August and collected information for the last financial year for which the business had data available at that point.

Population and sample selection

The target population for the Business Operations Survey was live enterprise units on Statistics NZ’s Business Frame that at the population selection date:

  • were economically significant enterprises (those that have an annual GST turnover figure of greater than $30,000)
  • had six or more employees
  • had been operating for one year or more
  • were classified to ANZSIC06 codes as ‘in scope’ in list 1 below
  • were private enterprises as defined by New Zealand Institutional Sector 1996 Classification (NZISC96) as in list 2 below.

An enterprise is defined as a business or service entity operating in New Zealand, such as a company, partnership, trust, government department or agency, state-owned enterprise, university, or self-employed individual.

List 1 – ANZSIC06 codes
ANZSIC06 code – description
A – Agriculture, forestry, and fishing
B – Mining
C – Manufacturing
D – Electricity, gas, water, and waste services
E – Construction
F – Wholesale trade
G – Retail trade
H – Accommodation and food services
I – Transport, postal, and warehousing
J – Information media and telecommunications
K – Financial and insurance services
L – Rental, hiring, and real estate services
M – Professional, scientific, and technical services
N – Administrative and support services
P – Education and training
Q – Health care and social assistance
R91 – Sport and recreation activities
R92 – Gambling activities
S94 – Repair and maintenance

Out of scope
O – Public administration and safety
R89 – Heritage activities
R90 – Creative and performing arts activities
S95 – Personal and other services
S96 – Private household employing staff and undifferentiated goods and service
producing activities of households for own use

List 2 – NZISC96 codes
NZISC96 code – description
1111 – Private corporate producer enterprises
1121 – Private non-corporate producer enterprises
1211 – Producer boards
1311 – Central government enterprises
2211 – Private registered banks
2221 – Private other broad money (M3) depository organisations
2291 – Private other depository organisations nec
2311 – Private other financial organisations excluding insurance and pension funds
2411 – Private insurance and pension funds

Out of scope
1321 – Local government enterprises
21 – Central bank
2212, 2213, 2222, 2223, 2292, 2293, 2312, 2313, 2412, 2413 – Central and local government financial intermediaries
3 – General government
4 – Private non-profit organisations serving households
5 – Households
6 – Rest of world

Sample design

The sample design was a two-level stratification according to ANZSIC industry and employment size groups. This information was obtained using enterprise ANZSIC industry and employment information from Statistics NZ's Business Frame.

The first level of stratification was 36 ANZSIC groupings. Within each of the ANZSIC groups there is a further stratification by employment size group. The four employment size groups used in the sample design are:

  • 6–19 employees (small)
  • 20–29 employees (medium 1)
  • 30–49 employees (medium 2)
  • 50 or more employees (large).

The two medium groups have been amalgamated, and the large size group further broken down for this publication, as these businesses were of particular interest for some of the results.

The survey has been designed to produce aggregate statistics at a national level. This design does not facilitate statistics to be produced at a regional level.

Interpreting the data

Unit non-response

Unit (or complete) non-response occurs when units in the sample do not return the questionnaire. The initial selection weight of the remaining units in the stratum was adjusted to account for the unit non-response (no item non-response imputation would occur for the units that did not return the questionnaire).

Item non-response

Item (or partial) non-response is when units return the questionnaire but some questions are not answered. No item non-response imputation was carried out for units that did not answer 60 percent or more of the questions they were required to answer (based on questionnaire routing rules). The respondents who did not meet this criterion were classified as unit non-responses and the weights were adjusted accordingly.

Imputation of numeric questions

The imputation methods used were weighted mean imputation and donor imputation. Using the weighted mean method, a weighted mean was calculated from linked responding units for each numeric linecode within each imputation cell. Non-responding units were then imputed with the weighted mean for their imputation cell. Weighted mean imputation was used to impute totals.

Donor imputation randomly selected a donor from within each imputation cell. The non-respondent was then imputed with the value(s) from the donor. Donor imputation was used to impute components and percentages so that the distribution was maintained.

Imputation of categoric variables

For categoric imputation the method used was nearest neighbour imputation, which involved finding a donor with the most similar responses. The donor supplied responses for all categoric variables requiring imputation. If the donor unit did not respond to any of the variables requiring a response, then we chose the next best donor to supply this information. This was continued until all the variables had a response.

Accuracy of the data

Treatment of sub-industries

The sub-industries presented in this release (indented industries in the tables) should be treated with caution since they have higher sample errors than those mentioned in Table 1.02. Further disaggregation below design level results in further loss of data quality.

The Business Operations Survey results are subject to measurement errors, including both non-sample and sample errors. These errors should be considered when analysing the results from the survey.

Non-sample errors

Non-sample errors include mistakes by respondents when completing questionnaires, variation in the respondents’ interpretation of the questions asked, and errors made during the processing of the data. In addition, the survey applied imputation methodologies to cope with non-respondents. Statistics NZ adopts procedures to minimise these types of error, but they may still occur and are not quantifiable.

Given the nature of the data collected, there are limitations on the level of accuracy that can be expected from the survey. Businesses’ records may not be kept in the form required for the survey and some estimation by the respondent may be required.

Sampling errors

The estimates in this report are based on a sample of businesses. Somewhat different figures might have been obtained if a complete census of the entire business population had been taken using the same questionnaire and processing methods etc. Because the estimates are based on a sample of businesses, all estimates have a sampling error associated with them. The variability of a survey estimate, due to the random nature of the sample selection process, is measured by its sampling error.

Sampling errors vary from estimate to estimate, and with population breakdown and population size. Exact sampling errors can be produced for each variable within the Business Operations Survey upon request if required.

Consistency with other periods or datasets

Industry classification change

From 2008, the design of the survey was updated to the Australian and New Zealand Standard Industrial Classification 2006 (ANZSIC06). See the technical notes of Business Operations Survey: 2008 for more information.

Information collected

Due to the modular nature of the survey, different data is released each year from the Businesses Operations Survey. Where possible, the current information has been compared with the most recent data from previous iterations of the surveys.

Research and Development Survey

Results on research and development from the Business Operations Survey differ slightly from those from the Research and Development Survey because of differences in sample selection, target population, and reporting periods. 

The Research and Development Survey collects information from businesses, government, and higher education (universities) to gain an accurate picture of R&D activity in New Zealand. It is targeted to businesses we know perform R&D, and collects detailed information on their R&D expenditure, as well as staff, funding, type, benefits and purpose of research. Due to the expanded definition in the R&D survey of what R&D includes, and the targeted population, the expenditure in the R&D survey is higher than in the Business Operations Survey. The results from the R&D survey are considered the official measure of R&D expenditure.

The Business Operations Survey is a sample of businesses in New Zealand, regardless of if they perform R&D or not. Therefore, some R&D activity is not collected by BOS. However, the BOS survey does go to a wider selection of businesses, in industries not known to perform R&D. Therefore, BOS provides a more detailed picture of the spread of business R&D across the economy. It also provides information on related activities such as innovation, to help understand what may influence a business and their R&D activity. It is the supporting information from BOS on other activities that helps complement the R&D survey.


While all care and diligence has been used in processing, analysing, and extracting data and information in this publication, Statistics NZ gives no warranty it is error-free and will not be liable for any loss or damage suffered by the use directly, or indirectly, of the information in this publication.


Our information releases are delivered electronically by third parties. Delivery may be delayed by circumstances outside our control. Statistics NZ does not accept responsibility for any such delay.

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